Bridges Lab Protocols - User contributions [en]

LDLR Genotyping

2026-01-26T16:02:31Z

Davebrid: /* Additional Reagents */ Added link to tail lysates

Modified from https://www.jax.org/Protocol?stockNumber=002207&protocolID=27075

* [[SOP - Ethidium Bromide]]
* [[SOP - Electrophoresis]]

== Reagents Needed ==

=== PCR Primers ===
* '''Ldlr Common Forward''': 5'-TAT GCA TCC CCA GTC TTT GG-3'
* '''Ldlr Wild-type Reverse''': 5'-CTA CCC AAC CAG CCC CTT AC-3'
* '''Ldlr Mutant Reverse''': 5'-ATA GAT TCG CCC TTG TGT CC-3'

=== Master Mix ===
* '''DreamTaq Green PCR Master Mix (2X)''' - Thermo Fisher Scientific, Cat# K1081

=== Additional Reagents ===
* Nuclease-free water
* Template DNA ([[Preparation of Tail Samples (for Genotyping)|tail lysate]] or purified genomic DNA)

== Primer Preparation ==

=== Stock Primer Preparation (100 µM) ===
# Resuspend each lyophilized primer in nuclease-free water to 100 µM concentration. Look on the tube from IDT, for example if there is 23.7 nmoles then you would resuspend in 237 µL of water
# Store at -20°C

=== Primer Master Mix (10 µM each primer) ===
For a 1 mL primer master mix:
* 100 µL of 100 µM Primer 19799
* 100 µL of 100 µM Primer 19800
* 100 µL of 100 µM Primer oIMR7770
* 700 µL nuclease-free water

'''Final concentrations in primer master mix:''' 10 µM each primer

Store at -20°C

== PCR Master Mix Preparation ==

=== Per Reaction (25 µL total volume) ===
* 12.5 µL DreamTaq Green PCR Master Mix (2X)
* 3.75 µL Primer Master Mix (10 µM each)
* 7.75 µL nuclease-free water
* 1 µL template DNA

'''Final primer concentrations in PCR:''' 1.5 µM each primer

=== For Multiple Reactions ===
Prepare master mix for (n+1) reactions, where n = number of samples:
* DreamTaq Green PCR Master Mix (2X): 12.5 µL × (n+1)
* Primer Master Mix: 3.75 µL × (n+1)
* Nuclease-free water: 7.75 µL × (n+1)

Aliquot 24 µL of master mix per tube, then add 1 µL template DNA to each

== PCR Cycling Program ==

This program takes 1:50 to run.

{| class="wikitable"
|+ '''Ldlr''' PCR Program
|-
! Step !! Temperature (°C) !! Time !! Cycles !! Notes
|-
| Initial Denaturation || 94 || 3 min || 1 ||
|-
| '''Touchdown Phase''' || || || ||
|-
| Denature || 94 || 30 sec || rowspan="3" | 10 || rowspan="3" | Decrease annealing temp by 0.5°C per cycle
|-
| Anneal || 65→60 || 30 sec
|-
| Extend || 68 || 45 sec
|-
| '''Standard Cycles''' || || || ||
|-
| Denature || 94 || 30 sec || rowspan="3" | 28 ||
|-
| Anneal || 60 || 30 sec ||
|-
| Extend || 72 || 45 sec ||
|-
| Final Extension || 72 || 5 min || 1 ||
|-
| Hold || 4 || ∞ || ||
|-
|}

== Expected Results ==

* '''Wild type:''' 351 bp
* '''Heterozygote:''' 179 bp AND 351 bp
* '''Mutant:''' 179 bp (GC-rich band)

'''Note:''' Run on 2% agarose gel. The mutant band (179 bp) is GC-rich and may appear fainter than expected.

[[ Category:Genotyping ]]
[[ Category:Mouse Work ]]
[[ Category:PCR ]]

LDLR Genotyping

2026-01-26T16:01:47Z

Davebrid: /* Stock Primer Preparation (100 µM) */ details about primer resuspension

Modified from https://www.jax.org/Protocol?stockNumber=002207&protocolID=27075

* [[SOP - Ethidium Bromide]]
* [[SOP - Electrophoresis]]

== Reagents Needed ==

=== PCR Primers ===
* '''Ldlr Common Forward''': 5'-TAT GCA TCC CCA GTC TTT GG-3'
* '''Ldlr Wild-type Reverse''': 5'-CTA CCC AAC CAG CCC CTT AC-3'
* '''Ldlr Mutant Reverse''': 5'-ATA GAT TCG CCC TTG TGT CC-3'

=== Master Mix ===
* '''DreamTaq Green PCR Master Mix (2X)''' - Thermo Fisher Scientific, Cat# K1081

=== Additional Reagents ===
* Nuclease-free water
* Template DNA (tail lysate or purified genomic DNA)

== Primer Preparation ==

=== Stock Primer Preparation (100 µM) ===
# Resuspend each lyophilized primer in nuclease-free water to 100 µM concentration. Look on the tube from IDT, for example if there is 23.7 nmoles then you would resuspend in 237 µL of water
# Store at -20°C

=== Primer Master Mix (10 µM each primer) ===
For a 1 mL primer master mix:
* 100 µL of 100 µM Primer 19799
* 100 µL of 100 µM Primer 19800
* 100 µL of 100 µM Primer oIMR7770
* 700 µL nuclease-free water

'''Final concentrations in primer master mix:''' 10 µM each primer

Store at -20°C

== PCR Master Mix Preparation ==

=== Per Reaction (25 µL total volume) ===
* 12.5 µL DreamTaq Green PCR Master Mix (2X)
* 3.75 µL Primer Master Mix (10 µM each)
* 7.75 µL nuclease-free water
* 1 µL template DNA

'''Final primer concentrations in PCR:''' 1.5 µM each primer

=== For Multiple Reactions ===
Prepare master mix for (n+1) reactions, where n = number of samples:
* DreamTaq Green PCR Master Mix (2X): 12.5 µL × (n+1)
* Primer Master Mix: 3.75 µL × (n+1)
* Nuclease-free water: 7.75 µL × (n+1)

Aliquot 24 µL of master mix per tube, then add 1 µL template DNA to each

== PCR Cycling Program ==

This program takes 1:50 to run.

{| class="wikitable"
|+ '''Ldlr''' PCR Program
|-
! Step !! Temperature (°C) !! Time !! Cycles !! Notes
|-
| Initial Denaturation || 94 || 3 min || 1 ||
|-
| '''Touchdown Phase''' || || || ||
|-
| Denature || 94 || 30 sec || rowspan="3" | 10 || rowspan="3" | Decrease annealing temp by 0.5°C per cycle
|-
| Anneal || 65→60 || 30 sec
|-
| Extend || 68 || 45 sec
|-
| '''Standard Cycles''' || || || ||
|-
| Denature || 94 || 30 sec || rowspan="3" | 28 ||
|-
| Anneal || 60 || 30 sec ||
|-
| Extend || 72 || 45 sec ||
|-
| Final Extension || 72 || 5 min || 1 ||
|-
| Hold || 4 || ∞ || ||
|-
|}

== Expected Results ==

* '''Wild type:''' 351 bp
* '''Heterozygote:''' 179 bp AND 351 bp
* '''Mutant:''' 179 bp (GC-rich band)

'''Note:''' Run on 2% agarose gel. The mutant band (179 bp) is GC-rich and may appear fainter than expected.

[[ Category:Genotyping ]]
[[ Category:Mouse Work ]]
[[ Category:PCR ]]

LDLR Genotyping

2026-01-26T16:01:08Z

Davebrid: /* PCR Primers */ Minor typo

Modified from https://www.jax.org/Protocol?stockNumber=002207&protocolID=27075

* [[SOP - Ethidium Bromide]]
* [[SOP - Electrophoresis]]

== Reagents Needed ==

=== PCR Primers ===
* '''Ldlr Common Forward''': 5'-TAT GCA TCC CCA GTC TTT GG-3'
* '''Ldlr Wild-type Reverse''': 5'-CTA CCC AAC CAG CCC CTT AC-3'
* '''Ldlr Mutant Reverse''': 5'-ATA GAT TCG CCC TTG TGT CC-3'

=== Master Mix ===
* '''DreamTaq Green PCR Master Mix (2X)''' - Thermo Fisher Scientific, Cat# K1081

=== Additional Reagents ===
* Nuclease-free water
* Template DNA (tail lysate or purified genomic DNA)

== Primer Preparation ==

=== Stock Primer Preparation (100 µM) ===
# Resuspend each lyophilized primer in nuclease-free water to 100 µM concentration
# Store at -20°C

=== Primer Master Mix (10 µM each primer) ===
For a 1 mL primer master mix:
* 100 µL of 100 µM Primer 19799
* 100 µL of 100 µM Primer 19800
* 100 µL of 100 µM Primer oIMR7770
* 700 µL nuclease-free water

'''Final concentrations in primer master mix:''' 10 µM each primer

Store at -20°C

== PCR Master Mix Preparation ==

=== Per Reaction (25 µL total volume) ===
* 12.5 µL DreamTaq Green PCR Master Mix (2X)
* 3.75 µL Primer Master Mix (10 µM each)
* 7.75 µL nuclease-free water
* 1 µL template DNA

'''Final primer concentrations in PCR:''' 1.5 µM each primer

=== For Multiple Reactions ===
Prepare master mix for (n+1) reactions, where n = number of samples:
* DreamTaq Green PCR Master Mix (2X): 12.5 µL × (n+1)
* Primer Master Mix: 3.75 µL × (n+1)
* Nuclease-free water: 7.75 µL × (n+1)

Aliquot 24 µL of master mix per tube, then add 1 µL template DNA to each

== PCR Cycling Program ==

This program takes 1:50 to run.

{| class="wikitable"
|+ '''Ldlr''' PCR Program
|-
! Step !! Temperature (°C) !! Time !! Cycles !! Notes
|-
| Initial Denaturation || 94 || 3 min || 1 ||
|-
| '''Touchdown Phase''' || || || ||
|-
| Denature || 94 || 30 sec || rowspan="3" | 10 || rowspan="3" | Decrease annealing temp by 0.5°C per cycle
|-
| Anneal || 65→60 || 30 sec
|-
| Extend || 68 || 45 sec
|-
| '''Standard Cycles''' || || || ||
|-
| Denature || 94 || 30 sec || rowspan="3" | 28 ||
|-
| Anneal || 60 || 30 sec ||
|-
| Extend || 72 || 45 sec ||
|-
| Final Extension || 72 || 5 min || 1 ||
|-
| Hold || 4 || ∞ || ||
|-
|}

== Expected Results ==

* '''Wild type:''' 351 bp
* '''Heterozygote:''' 179 bp AND 351 bp
* '''Mutant:''' 179 bp (GC-rich band)

'''Note:''' Run on 2% agarose gel. The mutant band (179 bp) is GC-rich and may appear fainter than expected.

[[ Category:Genotyping ]]
[[ Category:Mouse Work ]]
[[ Category:PCR ]]

LDLR Genotyping

2026-01-26T14:53:07Z

Davebrid: /* PCR Cycling Program */

Modified from https://www.jax.org/Protocol?stockNumber=002207&protocolID=27075

* [[SOP - Ethidium Bromide]]
* [[SOP - Electrophoresis]]

== Reagents Needed ==

=== PCR Primers ===
* '''Ldlr Common Forward: 5'-TAT GCA TCC CCA GTC TTT GG-3'
* '''Ldlr Wild-type Reverse''': 5'-CTA CCC AAC CAG CCC CTT AC-3'
* '''Ldlr Mutant Reverse''': 5'-ATA GAT TCG CCC TTG TGT CC-3'

=== Master Mix ===
* '''DreamTaq Green PCR Master Mix (2X)''' - Thermo Fisher Scientific, Cat# K1081

=== Additional Reagents ===
* Nuclease-free water
* Template DNA (tail lysate or purified genomic DNA)

== Primer Preparation ==

=== Stock Primer Preparation (100 µM) ===
# Resuspend each lyophilized primer in nuclease-free water to 100 µM concentration
# Store at -20°C

=== Primer Master Mix (10 µM each primer) ===
For a 1 mL primer master mix:
* 100 µL of 100 µM Primer 19799
* 100 µL of 100 µM Primer 19800
* 100 µL of 100 µM Primer oIMR7770
* 700 µL nuclease-free water

'''Final concentrations in primer master mix:''' 10 µM each primer

Store at -20°C

== PCR Master Mix Preparation ==

=== Per Reaction (25 µL total volume) ===
* 12.5 µL DreamTaq Green PCR Master Mix (2X)
* 3.75 µL Primer Master Mix (10 µM each)
* 7.75 µL nuclease-free water
* 1 µL template DNA

'''Final primer concentrations in PCR:''' 1.5 µM each primer

=== For Multiple Reactions ===
Prepare master mix for (n+1) reactions, where n = number of samples:
* DreamTaq Green PCR Master Mix (2X): 12.5 µL × (n+1)
* Primer Master Mix: 3.75 µL × (n+1)
* Nuclease-free water: 7.75 µL × (n+1)

Aliquot 24 µL of master mix per tube, then add 1 µL template DNA to each

== PCR Cycling Program ==

This program takes 1:50 to run.

{| class="wikitable"
|+ '''Ldlr''' PCR Program
|-
! Step !! Temperature (°C) !! Time !! Cycles !! Notes
|-
| Initial Denaturation || 94 || 3 min || 1 ||
|-
| '''Touchdown Phase''' || || || ||
|-
| Denature || 94 || 30 sec || rowspan="3" | 10 || rowspan="3" | Decrease annealing temp by 0.5°C per cycle
|-
| Anneal || 65→60 || 30 sec
|-
| Extend || 68 || 45 sec
|-
| '''Standard Cycles''' || || || ||
|-
| Denature || 94 || 30 sec || rowspan="3" | 28 ||
|-
| Anneal || 60 || 30 sec ||
|-
| Extend || 72 || 45 sec ||
|-
| Final Extension || 72 || 5 min || 1 ||
|-
| Hold || 4 || ∞ || ||
|-
|}

== Expected Results ==

* '''Wild type:''' 351 bp
* '''Heterozygote:''' 179 bp AND 351 bp
* '''Mutant:''' 179 bp (GC-rich band)

'''Note:''' Run on 2% agarose gel. The mutant band (179 bp) is GC-rich and may appear fainter than expected.

[[ Category:Genotyping ]]
[[ Category:Mouse Work ]]
[[ Category:PCR ]]

LDLR Genotyping

2026-01-26T14:52:31Z

Davebrid: /* Reagents Needed */ Updated primer names

Modified from https://www.jax.org/Protocol?stockNumber=002207&protocolID=27075

* [[SOP - Ethidium Bromide]]
* [[SOP - Electrophoresis]]

== Reagents Needed ==

=== PCR Primers ===
* '''Ldlr Common Forward: 5'-TAT GCA TCC CCA GTC TTT GG-3'
* '''Ldlr Wild-type Reverse''': 5'-CTA CCC AAC CAG CCC CTT AC-3'
* '''Ldlr Mutant Reverse''': 5'-ATA GAT TCG CCC TTG TGT CC-3'

=== Master Mix ===
* '''DreamTaq Green PCR Master Mix (2X)''' - Thermo Fisher Scientific, Cat# K1081

=== Additional Reagents ===
* Nuclease-free water
* Template DNA (tail lysate or purified genomic DNA)

== Primer Preparation ==

=== Stock Primer Preparation (100 µM) ===
# Resuspend each lyophilized primer in nuclease-free water to 100 µM concentration
# Store at -20°C

=== Primer Master Mix (10 µM each primer) ===
For a 1 mL primer master mix:
* 100 µL of 100 µM Primer 19799
* 100 µL of 100 µM Primer 19800
* 100 µL of 100 µM Primer oIMR7770
* 700 µL nuclease-free water

'''Final concentrations in primer master mix:''' 10 µM each primer

Store at -20°C

== PCR Master Mix Preparation ==

=== Per Reaction (25 µL total volume) ===
* 12.5 µL DreamTaq Green PCR Master Mix (2X)
* 3.75 µL Primer Master Mix (10 µM each)
* 7.75 µL nuclease-free water
* 1 µL template DNA

'''Final primer concentrations in PCR:''' 1.5 µM each primer

=== For Multiple Reactions ===
Prepare master mix for (n+1) reactions, where n = number of samples:
* DreamTaq Green PCR Master Mix (2X): 12.5 µL × (n+1)
* Primer Master Mix: 3.75 µL × (n+1)
* Nuclease-free water: 7.75 µL × (n+1)

Aliquot 24 µL of master mix per tube, then add 1 µL template DNA to each

== PCR Cycling Program ==

{| class="wikitable"
|+ Ldlr Genotyping PCR Program
|-
! Step !! Temperature (°C) !! Time !! Cycles !! Notes
|-
| Initial Denaturation || 94 || 3 min || 1 ||
|-
| '''Touchdown Phase''' || || || ||
|-
| Denature || 94 || 30 sec || rowspan="3" | 10 || rowspan="3" | Decrease annealing temp by 0.5°C per cycle
|-
| Anneal || 65→60 || 30 sec
|-
| Extend || 68 || 45 sec
|-
| '''Standard Cycles''' || || || ||
|-
| Denature || 94 || 30 sec || rowspan="3" | 28 ||
|-
| Anneal || 60 || 30 sec ||
|-
| Extend || 72 || 45 sec ||
|-
| Final Extension || 72 || 5 min || 1 ||
|-
| Hold || 10 || ∞ || ||
|-
|}

== Expected Results ==

* '''Wild type:''' 351 bp
* '''Heterozygote:''' 179 bp AND 351 bp
* '''Mutant:''' 179 bp (GC-rich band)

'''Note:''' Run on 2% agarose gel. The mutant band (179 bp) is GC-rich and may appear fainter than expected.

[[ Category:Genotyping ]]
[[ Category:Mouse Work ]]
[[ Category:PCR ]]

SOP - Ethidium Bromide

2026-01-24T19:39:43Z

Davebrid: /* Certification */

[[ Category: SOP ]]
[[ Category: Lab Safety ]]

==Description==
This standard operating procedure outlines the handling and use of Ethidium Bromide (EtBr). Review this document and supply the information required in order to make it specific to your laboratory. In accordance with this document, laboratories should use appropriate controls, personal protective equipment, and disposal techniques when handling EtBr.

EtBr intercalates double-stranded DNA and RNA and acts as a frameshift mutagen. It can also be used in conjunction with acridine orange to differentiate between viable, apoptotic and necrotic cells.

==Safer Alternative to Ethidium Bromide==
A recommended, safer alternative to ethidium bromide is using Gel Red as a gel staining agent for nucleic acid work (dsDNA, ssDNA or RNA) in agarose gels or polyacrylamide gels. It is not only highly sensitive but also tested to be environmentally safe and non-hazardous. Click the following link below for more details: http://www.ocs.umich.edu/pdf/GelRedFactSheet.pdf

==Potential Hazards==
*EtBr is an odorless solid that is irritating to the eyes, skin, mucous membranes and upper respiratory tract.
*EtBr is a potent mutagen and should be treated as a possible reproductive hazard and carcinogen.
*Consult the SDS and Laboratory Chemical Safety Summary for Ethidium Bromide in Prudent Practices in the Laboratory (National Academies Press).

==Engineering Controls==
Stock solutions of EtBr should be prepared in a chemical fume hood. If aerosols may be produced (dust or liquid mist), EtBr must be handled in a chemical fume hood, exhausted biological safety cabinet with negative pressure ductwork, or other exhausted enclosure. Aerosols may be produced during any open handling of dry powder, and during open or pressurized manipulations of solutions.

==Work Practice Controls==
*Set up a designated area for work with Ethidium Bromide, and label it with the following wording: “Ethidium Bromide in use. Mutagen and irritant.”
*Line the work area with a disposable plastic-backed absorbent pad.
*Keep containers closed as much as possible.
*If weighing dry powders and the balance cannot be located in a fume hood or BSC, tare a container then add the material to the container in a hood and seal the container before returning to the balance to weigh the powder.
*Change gloves regularly (at least every two hours) and wash hands at the time of the glove change. No skin contact is permitted.

==Protective Equipment==
*Standard nitrile laboratory gloves and a fully buttoned lab coat with sleeves extending to the wrists should be worn when handling EtBr (powder and solutions).
*If splashes may occur, wear goggles and a face shield. Otherwise, wear standard laboratory safety glasses.
*When using a UV light to visualize EtBr contamination, wear UV-blocking eyewear or work behind a UV shielding glass. (Most standard safety glasses will block UV, but employees should check the approval of their safety glasses.)
*In cases where the arms or torso may be exposed to liquid suspensions or dry particles, wear Tyvek sleeves and/or gowns (or other air-tight non-woven textile).

==Transportation and Storage==
*EtBr powder and solutions should be in tightly closed, shatter-resistant containers during transportation and storage. Secondary containment is advised.
*It should be stored away from strong oxidizing agents in a cool, dry place.

==Waste Disposal==
EtBr waste in concentrated or solid form is collected as chemical waste and should not be flushed down the drain or disposed of in the trash. Go to Drain Disposal for more information. Waste should be properly labeled and handled.

'''Liquids:''' Non-aqueous solutions and solutions containing EtBr concentration will be picked up by OSEH Hazardous Materials Management (OSEH-HMM). OSEH-HMM provides 1-gallon or 5-gallon pails for solid waste and gels, 1-gallon glass jugs for liquid waste, and smaller waste containers. Go to Waste Supplies for more information.

'''Contaminated sharps (needles, syringes, slides, broken glass, etc.):''' Discard in an infectious waste sharps container clearly labeled "CHEMICAL CONTAMINATED SHARPS-DO NOT AUTOCLAVE". Contact OSEH-HMM for pickup of the sharps container as infectious waste without autoclaving within 90 days or when it is 2/3 to 3/4 full.

'''Solids (contaminated gloves, centrifuge tubes, towels, etc.):''' Store in a properly labeled 1-gallon or 5-gallon pail for disposal as chemical waste. Do not use glass containers.

'''Gels:''' Gels should be disposed of as contaminated solids described above.

Because most spent, unused and expired chemicals/materials are considered hazardous wastes, they must be properly disposed of. ''Do not dispose of chemical wastes by dumping them down a sink, flushing in a toilet or discarding in regular trash containers, unless authorized by OSEH Hazardous Materials Management (HMM).'''''Bold text''' Contact OSEH-HMM at (734) 763-4568 for waste containers, labels, manifests, waste collection and for any questions regarding proper waste disposal. Also refer to OSEH’s Hazardous Waste webpage for more information.

==Exposures/Unintended contact==

'''If the employee is in need of emergency medical attention, call 911 immediately.'''

'''For an actual chemical exposure/injury:'''
*Remove contaminated clothing. Flush exposed eyes or skin with water for at least 15 minutes. Seek medical attention (see below).
*For inhalation exposure, remove all persons from the contaminated area. Get medical aid.
*If an ambulance is needed, call the University of Michigan Division of Public Safety and Security (DPSS) at 911 to request assistance.

Contact OSEH for advice on symptoms of chemical exposure, or assistance in performing an exposure assessment.

Report all work related accidents, injuries, illnesses or exposures to WorkConnections within 24 hours by completing and submitting the Illness and Injury Report Form. Follow the directions on the WorkConnections website Forms Instructions to obtain proper medical treatment and follow-up.

Complete the OSEH Laboratory Incident and Near-Miss Report form.

==TREATMENT FACILITIES:==
*U-M Occupational Health Services -- Campus Employees
Mon-Fri 7:30 am - 4:30 pm
After hours - go to UM Hospital Emergency Dept. – Urgent Care Clinic
C380 Med Inn building
1500 East Medical Center Drive, Ann Arbor (734) 764-8021
*University Health Services -- University students (non-life threatening conditions)
Mon-Fri 8 am – 4:30 pm, Sat 9 am – 12 pm
Contact for current hours as they may vary
207 Fletcher Street, Ann Arbor (734) 764-8320
*UMHS Emergency Department -- after clinic hours or on weekends
1500 East Medical Center Drive, Ann Arbor, (734) 936-6666
Click here for additional accident and injury reporting information.

==Spill Procedure==
*When a spill occurs, personal safety should always come first.
*Alert and clear everyone in the immediate area where the spill occurred.
*Small spills of EtBr solutions should be cleaned by laboratory staff. For large spills outside the fume hood, evacuate/restrict access to the laboratory and contact OSEH-HMM for assistance at (734) 763-4568.
*Individuals cleaning spills must wear appropriate protective equipment as described in the Personal Protective Equipment section of this document.
*Spills of EtBr solutions should be cleaned using absorbent pads followed by surface decontamination using soap and water. Spilled dry material should first be covered with moist absorbent pads to avoid generation of dust.
*Ensure all materials contaminated as a result of the cleanup process are collected and disposed of as hazardous waste as described in the EtBr Waste Disposal section of this document.

==Additional Spill Links:==
*www.oseh.umich.edu/pdf/chemspil.pdf
*http://www.oseh.umich.edu/emer-chemical.shtml.

'''Report all emergencies, suspicious activity, injuries, spills, and fires to the University of Michigan Division of Public Safety and Security (DPSS) by calling 911 or texting 377911. Register with the University of Michigan Emergency Alert System via Wolverine Access.
'''

==Training of Personnel==
All personnel are required to complete the General Laboratory Safety Training session (BLS025w or equivalent) via OSEH’s My LINC website. Furthermore, all personnel shall read and fully adhere to this SOP when handling EtBr.

==Certification==
I have read and understand the above SOP. I agree to contact my Supervisor or Lab manager if I plan to modify this procedure.Sign by logging in and typing <nowiki>* ~~~~</nowiki> in the list below:

*[[User:Reddj|Reddj]] ([[User talk:Reddj|talk]]) 15:48, 13 October 2016 (UTC)
*[[User:Iharvey|Iharvey]] ([[User talk:Iharvey|talk]]) 21:19, 10 November 2016 (UTC)
*[[User:Mollyec|Mollyec]] ([[User talk:Mollyec|talk]]) 16:16, 31 October 2016 (UTC)
* [[User:Elhabbal|Elhabbal]] ([[User talk:Elhabbal|talk]]) 21:49, 12 June 2017 (UTC)
* [[User:Ccousz|Ccousz]] ([[User talk:Ccousz|talk]]) 13:17, 6 June 2022 (UTC)
* [[User:Davebrid|Davebrid]] ([[User talk:Davebrid|talk]]) 19:39, 24 January 2026 (UTC)
Prior Approval required – Is this procedure hazardous enough to warrant prior approval from the Laboratory Director? ☒ YES ☐ NO

SOP - Ethidium Bromide

2026-01-24T19:39:16Z

Davebrid: /* Certification */ Signed by DB

[[ Category: SOP ]]
[[ Category: Lab Safety ]]

==Description==
This standard operating procedure outlines the handling and use of Ethidium Bromide (EtBr). Review this document and supply the information required in order to make it specific to your laboratory. In accordance with this document, laboratories should use appropriate controls, personal protective equipment, and disposal techniques when handling EtBr.

EtBr intercalates double-stranded DNA and RNA and acts as a frameshift mutagen. It can also be used in conjunction with acridine orange to differentiate between viable, apoptotic and necrotic cells.

==Safer Alternative to Ethidium Bromide==
A recommended, safer alternative to ethidium bromide is using Gel Red as a gel staining agent for nucleic acid work (dsDNA, ssDNA or RNA) in agarose gels or polyacrylamide gels. It is not only highly sensitive but also tested to be environmentally safe and non-hazardous. Click the following link below for more details: http://www.ocs.umich.edu/pdf/GelRedFactSheet.pdf

==Potential Hazards==
*EtBr is an odorless solid that is irritating to the eyes, skin, mucous membranes and upper respiratory tract.
*EtBr is a potent mutagen and should be treated as a possible reproductive hazard and carcinogen.
*Consult the SDS and Laboratory Chemical Safety Summary for Ethidium Bromide in Prudent Practices in the Laboratory (National Academies Press).

==Engineering Controls==
Stock solutions of EtBr should be prepared in a chemical fume hood. If aerosols may be produced (dust or liquid mist), EtBr must be handled in a chemical fume hood, exhausted biological safety cabinet with negative pressure ductwork, or other exhausted enclosure. Aerosols may be produced during any open handling of dry powder, and during open or pressurized manipulations of solutions.

==Work Practice Controls==
*Set up a designated area for work with Ethidium Bromide, and label it with the following wording: “Ethidium Bromide in use. Mutagen and irritant.”
*Line the work area with a disposable plastic-backed absorbent pad.
*Keep containers closed as much as possible.
*If weighing dry powders and the balance cannot be located in a fume hood or BSC, tare a container then add the material to the container in a hood and seal the container before returning to the balance to weigh the powder.
*Change gloves regularly (at least every two hours) and wash hands at the time of the glove change. No skin contact is permitted.

==Protective Equipment==
*Standard nitrile laboratory gloves and a fully buttoned lab coat with sleeves extending to the wrists should be worn when handling EtBr (powder and solutions).
*If splashes may occur, wear goggles and a face shield. Otherwise, wear standard laboratory safety glasses.
*When using a UV light to visualize EtBr contamination, wear UV-blocking eyewear or work behind a UV shielding glass. (Most standard safety glasses will block UV, but employees should check the approval of their safety glasses.)
*In cases where the arms or torso may be exposed to liquid suspensions or dry particles, wear Tyvek sleeves and/or gowns (or other air-tight non-woven textile).

==Transportation and Storage==
*EtBr powder and solutions should be in tightly closed, shatter-resistant containers during transportation and storage. Secondary containment is advised.
*It should be stored away from strong oxidizing agents in a cool, dry place.

==Waste Disposal==
EtBr waste in concentrated or solid form is collected as chemical waste and should not be flushed down the drain or disposed of in the trash. Go to Drain Disposal for more information. Waste should be properly labeled and handled.

'''Liquids:''' Non-aqueous solutions and solutions containing EtBr concentration will be picked up by OSEH Hazardous Materials Management (OSEH-HMM). OSEH-HMM provides 1-gallon or 5-gallon pails for solid waste and gels, 1-gallon glass jugs for liquid waste, and smaller waste containers. Go to Waste Supplies for more information.

'''Contaminated sharps (needles, syringes, slides, broken glass, etc.):''' Discard in an infectious waste sharps container clearly labeled "CHEMICAL CONTAMINATED SHARPS-DO NOT AUTOCLAVE". Contact OSEH-HMM for pickup of the sharps container as infectious waste without autoclaving within 90 days or when it is 2/3 to 3/4 full.

'''Solids (contaminated gloves, centrifuge tubes, towels, etc.):''' Store in a properly labeled 1-gallon or 5-gallon pail for disposal as chemical waste. Do not use glass containers.

'''Gels:''' Gels should be disposed of as contaminated solids described above.

Because most spent, unused and expired chemicals/materials are considered hazardous wastes, they must be properly disposed of. ''Do not dispose of chemical wastes by dumping them down a sink, flushing in a toilet or discarding in regular trash containers, unless authorized by OSEH Hazardous Materials Management (HMM).'''''Bold text''' Contact OSEH-HMM at (734) 763-4568 for waste containers, labels, manifests, waste collection and for any questions regarding proper waste disposal. Also refer to OSEH’s Hazardous Waste webpage for more information.

==Exposures/Unintended contact==

'''If the employee is in need of emergency medical attention, call 911 immediately.'''

'''For an actual chemical exposure/injury:'''
*Remove contaminated clothing. Flush exposed eyes or skin with water for at least 15 minutes. Seek medical attention (see below).
*For inhalation exposure, remove all persons from the contaminated area. Get medical aid.
*If an ambulance is needed, call the University of Michigan Division of Public Safety and Security (DPSS) at 911 to request assistance.

Contact OSEH for advice on symptoms of chemical exposure, or assistance in performing an exposure assessment.

Report all work related accidents, injuries, illnesses or exposures to WorkConnections within 24 hours by completing and submitting the Illness and Injury Report Form. Follow the directions on the WorkConnections website Forms Instructions to obtain proper medical treatment and follow-up.

Complete the OSEH Laboratory Incident and Near-Miss Report form.

==TREATMENT FACILITIES:==
*U-M Occupational Health Services -- Campus Employees
Mon-Fri 7:30 am - 4:30 pm
After hours - go to UM Hospital Emergency Dept. – Urgent Care Clinic
C380 Med Inn building
1500 East Medical Center Drive, Ann Arbor (734) 764-8021
*University Health Services -- University students (non-life threatening conditions)
Mon-Fri 8 am – 4:30 pm, Sat 9 am – 12 pm
Contact for current hours as they may vary
207 Fletcher Street, Ann Arbor (734) 764-8320
*UMHS Emergency Department -- after clinic hours or on weekends
1500 East Medical Center Drive, Ann Arbor, (734) 936-6666
Click here for additional accident and injury reporting information.

==Spill Procedure==
*When a spill occurs, personal safety should always come first.
*Alert and clear everyone in the immediate area where the spill occurred.
*Small spills of EtBr solutions should be cleaned by laboratory staff. For large spills outside the fume hood, evacuate/restrict access to the laboratory and contact OSEH-HMM for assistance at (734) 763-4568.
*Individuals cleaning spills must wear appropriate protective equipment as described in the Personal Protective Equipment section of this document.
*Spills of EtBr solutions should be cleaned using absorbent pads followed by surface decontamination using soap and water. Spilled dry material should first be covered with moist absorbent pads to avoid generation of dust.
*Ensure all materials contaminated as a result of the cleanup process are collected and disposed of as hazardous waste as described in the EtBr Waste Disposal section of this document.

==Additional Spill Links:==
*www.oseh.umich.edu/pdf/chemspil.pdf
*http://www.oseh.umich.edu/emer-chemical.shtml.

'''Report all emergencies, suspicious activity, injuries, spills, and fires to the University of Michigan Division of Public Safety and Security (DPSS) by calling 911 or texting 377911. Register with the University of Michigan Emergency Alert System via Wolverine Access.
'''

==Training of Personnel==
All personnel are required to complete the General Laboratory Safety Training session (BLS025w or equivalent) via OSEH’s My LINC website. Furthermore, all personnel shall read and fully adhere to this SOP when handling EtBr.

==Certification==
I have read and understand the above SOP. I agree to contact my Supervisor or Lab manager if I plan to modify this procedure.Sign by logging in and typing <nowiki>* ~~~~</nowiki> in the list below:

*[[User:Reddj|Reddj]] ([[User talk:Reddj|talk]]) 15:48, 13 October 2016 (UTC)
*[[User:Iharvey|Iharvey]] ([[User talk:Iharvey|talk]]) 21:19, 10 November 2016 (UTC)
*[[User:Mollyec|Mollyec]] ([[User talk:Mollyec|talk]]) 16:16, 31 October 2016 (UTC)
* [[User:Elhabbal|Elhabbal]] ([[User talk:Elhabbal|talk]]) 21:49, 12 June 2017 (UTC)
* [[User:Ccousz|Ccousz]] ([[User talk:Ccousz|talk]]) 13:17, 6 June 2022 (UTC)
* [[User:Davebrid|Davebrid]] ([[User talk:Davebrid|talk]])
Prior Approval required – Is this procedure hazardous enough to warrant prior approval from the Laboratory Director? ☒ YES ☐ NO

LDLR Genotyping

2026-01-24T19:38:27Z

Davebrid: formatting

Modified from https://www.jax.org/Protocol?stockNumber=002207&protocolID=27075

* [[SOP - Ethidium Bromide]]
* [[SOP - Electrophoresis]]

== Reagents Needed ==

=== PCR Primers ===
* '''Primer 19799''' (Common Forward): 5'-TAT GCA TCC CCA GTC TTT GG-3'
* '''Primer 19800''' (Wild type Reverse): 5'-CTA CCC AAC CAG CCC CTT AC-3'
* '''Primer oIMR7770''' (Mutant Reverse): 5'-ATA GAT TCG CCC TTG TGT CC-3'

=== Master Mix ===
* '''DreamTaq Green PCR Master Mix (2X)''' - Thermo Fisher Scientific, Cat# K1081

=== Additional Reagents ===
* Nuclease-free water
* Template DNA (tail lysate or purified genomic DNA)

== Primer Preparation ==

=== Stock Primer Preparation (100 µM) ===
# Resuspend each lyophilized primer in nuclease-free water to 100 µM concentration
# Store at -20°C

=== Primer Master Mix (10 µM each primer) ===
For a 1 mL primer master mix:
* 100 µL of 100 µM Primer 19799
* 100 µL of 100 µM Primer 19800
* 100 µL of 100 µM Primer oIMR7770
* 700 µL nuclease-free water

'''Final concentrations in primer master mix:''' 10 µM each primer

Store at -20°C

== PCR Master Mix Preparation ==

=== Per Reaction (25 µL total volume) ===
* 12.5 µL DreamTaq Green PCR Master Mix (2X)
* 3.75 µL Primer Master Mix (10 µM each)
* 7.75 µL nuclease-free water
* 1 µL template DNA

'''Final primer concentrations in PCR:''' 1.5 µM each primer

=== For Multiple Reactions ===
Prepare master mix for (n+1) reactions, where n = number of samples:
* DreamTaq Green PCR Master Mix (2X): 12.5 µL × (n+1)
* Primer Master Mix: 3.75 µL × (n+1)
* Nuclease-free water: 7.75 µL × (n+1)

Aliquot 24 µL of master mix per tube, then add 1 µL template DNA to each

== PCR Cycling Program ==

{| class="wikitable"
|+ Ldlr Genotyping PCR Program
|-
! Step !! Temperature (°C) !! Time !! Cycles !! Notes
|-
| Initial Denaturation || 94 || 3 min || 1 ||
|-
| '''Touchdown Phase''' || || || ||
|-
| Denature || 94 || 30 sec || rowspan="3" | 10 || rowspan="3" | Decrease annealing temp by 0.5°C per cycle
|-
| Anneal || 65→60 || 30 sec
|-
| Extend || 68 || 45 sec
|-
| '''Standard Cycles''' || || || ||
|-
| Denature || 94 || 30 sec || rowspan="3" | 28 ||
|-
| Anneal || 60 || 30 sec ||
|-
| Extend || 72 || 45 sec ||
|-
| Final Extension || 72 || 5 min || 1 ||
|-
| Hold || 10 || ∞ || ||
|-
|}

== Expected Results ==

* '''Wild type:''' 351 bp
* '''Heterozygote:''' 179 bp AND 351 bp
* '''Mutant:''' 179 bp (GC-rich band)

'''Note:''' Run on 2% agarose gel. The mutant band (179 bp) is GC-rich and may appear fainter than expected.

[[ Category:Genotyping ]]
[[ Category:Mouse Work ]]
[[ Category:PCR ]]

LDLR Genotyping

2026-01-24T19:38:11Z

Davebrid: Added SOP's

Modified from https://www.jax.org/Protocol?stockNumber=002207&protocolID=27075

[[SOP - Ethidium Bromide]]
[[SOP - Electrophoresis]]

== Reagents Needed ==

=== PCR Primers ===
* '''Primer 19799''' (Common Forward): 5'-TAT GCA TCC CCA GTC TTT GG-3'
* '''Primer 19800''' (Wild type Reverse): 5'-CTA CCC AAC CAG CCC CTT AC-3'
* '''Primer oIMR7770''' (Mutant Reverse): 5'-ATA GAT TCG CCC TTG TGT CC-3'

=== Master Mix ===
* '''DreamTaq Green PCR Master Mix (2X)''' - Thermo Fisher Scientific, Cat# K1081

=== Additional Reagents ===
* Nuclease-free water
* Template DNA (tail lysate or purified genomic DNA)

== Primer Preparation ==

=== Stock Primer Preparation (100 µM) ===
# Resuspend each lyophilized primer in nuclease-free water to 100 µM concentration
# Store at -20°C

=== Primer Master Mix (10 µM each primer) ===
For a 1 mL primer master mix:
* 100 µL of 100 µM Primer 19799
* 100 µL of 100 µM Primer 19800
* 100 µL of 100 µM Primer oIMR7770
* 700 µL nuclease-free water

'''Final concentrations in primer master mix:''' 10 µM each primer

Store at -20°C

== PCR Master Mix Preparation ==

=== Per Reaction (25 µL total volume) ===
* 12.5 µL DreamTaq Green PCR Master Mix (2X)
* 3.75 µL Primer Master Mix (10 µM each)
* 7.75 µL nuclease-free water
* 1 µL template DNA

'''Final primer concentrations in PCR:''' 1.5 µM each primer

=== For Multiple Reactions ===
Prepare master mix for (n+1) reactions, where n = number of samples:
* DreamTaq Green PCR Master Mix (2X): 12.5 µL × (n+1)
* Primer Master Mix: 3.75 µL × (n+1)
* Nuclease-free water: 7.75 µL × (n+1)

Aliquot 24 µL of master mix per tube, then add 1 µL template DNA to each

== PCR Cycling Program ==

{| class="wikitable"
|+ Ldlr Genotyping PCR Program
|-
! Step !! Temperature (°C) !! Time !! Cycles !! Notes
|-
| Initial Denaturation || 94 || 3 min || 1 ||
|-
| '''Touchdown Phase''' || || || ||
|-
| Denature || 94 || 30 sec || rowspan="3" | 10 || rowspan="3" | Decrease annealing temp by 0.5°C per cycle
|-
| Anneal || 65→60 || 30 sec
|-
| Extend || 68 || 45 sec
|-
| '''Standard Cycles''' || || || ||
|-
| Denature || 94 || 30 sec || rowspan="3" | 28 ||
|-
| Anneal || 60 || 30 sec ||
|-
| Extend || 72 || 45 sec ||
|-
| Final Extension || 72 || 5 min || 1 ||
|-
| Hold || 10 || ∞ || ||
|-
|}

== Expected Results ==

* '''Wild type:''' 351 bp
* '''Heterozygote:''' 179 bp AND 351 bp
* '''Mutant:''' 179 bp (GC-rich band)

'''Note:''' Run on 2% agarose gel. The mutant band (179 bp) is GC-rich and may appear fainter than expected.

[[ Category:Genotyping ]]
[[ Category:Mouse Work ]]
[[ Category:PCR ]]

LDLR Genotyping

2026-01-24T19:33:35Z

Davebrid: Modifieed protocol from Jax, as modified by Claude to use dreamtaq

Modified from https://www.jax.org/Protocol?stockNumber=002207&protocolID=27075

== Reagents Needed ==

=== PCR Primers ===
* '''Primer 19799''' (Common Forward): 5'-TAT GCA TCC CCA GTC TTT GG-3'
* '''Primer 19800''' (Wild type Reverse): 5'-CTA CCC AAC CAG CCC CTT AC-3'
* '''Primer oIMR7770''' (Mutant Reverse): 5'-ATA GAT TCG CCC TTG TGT CC-3'

=== Master Mix ===
* '''DreamTaq Green PCR Master Mix (2X)''' - Thermo Fisher Scientific, Cat# K1081

=== Additional Reagents ===
* Nuclease-free water
* Template DNA (tail lysate or purified genomic DNA)

== Primer Preparation ==

=== Stock Primer Preparation (100 µM) ===
# Resuspend each lyophilized primer in nuclease-free water to 100 µM concentration
# Store at -20°C

=== Primer Master Mix (10 µM each primer) ===
For a 1 mL primer master mix:
* 100 µL of 100 µM Primer 19799
* 100 µL of 100 µM Primer 19800
* 100 µL of 100 µM Primer oIMR7770
* 700 µL nuclease-free water

'''Final concentrations in primer master mix:''' 10 µM each primer

Store at -20°C

== PCR Master Mix Preparation ==

=== Per Reaction (25 µL total volume) ===
* 12.5 µL DreamTaq Green PCR Master Mix (2X)
* 3.75 µL Primer Master Mix (10 µM each)
* 7.75 µL nuclease-free water
* 1 µL template DNA

'''Final primer concentrations in PCR:''' 1.5 µM each primer

=== For Multiple Reactions ===
Prepare master mix for (n+1) reactions, where n = number of samples:
* DreamTaq Green PCR Master Mix (2X): 12.5 µL × (n+1)
* Primer Master Mix: 3.75 µL × (n+1)
* Nuclease-free water: 7.75 µL × (n+1)

Aliquot 24 µL of master mix per tube, then add 1 µL template DNA to each

== PCR Cycling Program ==

{| class="wikitable"
|+ Ldlr Genotyping PCR Program
|-
! Step !! Temperature (°C) !! Time !! Cycles !! Notes
|-
| Initial Denaturation || 94 || 3 min || 1 ||
|-
| '''Touchdown Phase''' || || || ||
|-
| Denature || 94 || 30 sec || rowspan="3" | 10 || rowspan="3" | Decrease annealing temp by 0.5°C per cycle
|-
| Anneal || 65→60 || 30 sec
|-
| Extend || 68 || 45 sec
|-
| '''Standard Cycles''' || || || ||
|-
| Denature || 94 || 30 sec || rowspan="3" | 28 ||
|-
| Anneal || 60 || 30 sec ||
|-
| Extend || 72 || 45 sec ||
|-
| Final Extension || 72 || 5 min || 1 ||
|-
| Hold || 10 || ∞ || ||
|-
|}

== Expected Results ==

* '''Wild type:''' 351 bp
* '''Heterozygote:''' 179 bp AND 351 bp
* '''Mutant:''' 179 bp (GC-rich band)

'''Note:''' Run on 2% agarose gel. The mutant band (179 bp) is GC-rich and may appear fainter than expected.

[[ Category:Genotyping ]]
[[ Category:Mouse Work ]]
[[ Category:PCR ]]

Preparation of Tail Samples (for Genotyping)

2026-01-24T19:24:07Z

Davebrid: Added link to higher purity protocol

==PBND Solution: Tail Lysis Buffer==

{| class="wikitable"
|+ Caption text
|-
! Reagent !! Final Concentration !! From Stock (for 250 mL)
|-
| Tris pH 8.0 || 10 mM || 2.5 mL of 1M
|-
| KCl || 50 mM || 12.5 mL of 1M
|-
| MgCl<sub>2</sub> || 0.1 mg/mL || 260 uL of 1M
|-
| NP40 || 0.45% || 11.25 mL of 10%
|-
| Tween 20 || 0.45% || 11.25 mL of 10%
|-
| Gelatin || 0.1 mg/mL || 25 mg
|-
|}

Add the above to ~200 mL of water, check that pH is 8.3 and then bring up to 250 mL. Store at 4 degrees

For each digestion, add 2 uL of 10 mg/mL proteinase K diluted in 50 uL PBND. Combine as a master mix and then aliquot into wells with tissue.

==Protocol==
# Combine 100uL of PBND solution with 2ul of Proteinase K and mouse tail in an eppendorf tube or in a well of a 96 well PCR plate (Proteinase K stock = 10mg/mL in ddH2O)
# Incubate at 55 degrees (16 hours - O/N)
# Incubate at 85 degrees for 60 min
# Hold at 4 degrees

If you need higher purity DNA try the protocol at [[DNA Preparation from Tail Clip]]

[[Category: Mouse Work]]
[[Category: Molecular Biology]]
[[Category: DNA]]
[[Category: Genotyping]]

DNA Preparation from Tail Clip

2026-01-24T19:23:26Z

Davebrid: Added link to other protocol for genotyping

Use Qiagen DNEasy kit for Blood and Tissue Samples. For a crude preparation, often good enough for PCR genotyping see [[Preparation of Tail Samples (for Genotyping)]]

==Protocol==

#Cut .5cm lengths of tail into a 1.5 ml microcentrifuge tube. Add 180ul Buffer ATL.
#Add 20ul proteinase K. Mix by vortexing and incubate at 56C until tissue is completely lysed. (Overnight)
#Vortex for 15s. Add 200ul Buffer Al to sample and vortex. Then add 200 ul ethanol (96-100%) and vortex.
#Pipet the mixture from step 3 into DNeasy Mini spin column. Centrifuge at 8000rpm for 1 minute. Discard flow-through and collection tube.
#Place DNeasy Mini spin column in new collection tube and add 500 ul Buffer AW1. Centrifuge for 1 minute at 8000rpm. Discard flow-through and collection tube.
#Place DNeasy Mini spin column in new collection tube and add 500 ul Buffer AW2. Centrifuge for 3 minutes at 14000rpm. Discard flow-through and collection tube.
#Place DNeasy Mini spin column in clean 1.5 microcentrifuge tube and pipet 200ul Buffer AE directly onto the DNeasy membrance. Incubate at room tempature for 1 minute and then centrifuge for 1 minute at 8000rpm to elute.

[[Category: Mouse Work]]
[[Category: Molecular Biology]]
[[Category: DNA]]
[[Category: Genotyping]]

Preparation of Tail Samples (for Genotyping)

2026-01-24T19:21:14Z

Davebrid: /* PBND Solution: Tail Lysis Buffer */ Updated calculation for PBND using stock solutions

==PBND Solution: Tail Lysis Buffer==

{| class="wikitable"
|+ Caption text
|-
! Reagent !! Final Concentration !! From Stock (for 250 mL)
|-
| Tris pH 8.0 || 10 mM || 2.5 mL of 1M
|-
| KCl || 50 mM || 12.5 mL of 1M
|-
| MgCl<sub>2</sub> || 0.1 mg/mL || 260 uL of 1M
|-
| NP40 || 0.45% || 11.25 mL of 10%
|-
| Tween 20 || 0.45% || 11.25 mL of 10%
|-
| Gelatin || 0.1 mg/mL || 25 mg
|-
|}

Add the above to ~200 mL of water, check that pH is 8.3 and then bring up to 250 mL. Store at 4 degrees

For each digestion, add 2 uL of 10 mg/mL proteinase K diluted in 50 uL PBND. Combine as a master mix and then aliquot into wells with tissue.

==Protocol==
# Combine 100uL of PBND solution with 2ul of Proteinase K and mouse tail in an eppendorf tube or in a well of a 96 well PCR plate (Proteinase K stock = 10mg/mL in ddH2O)
# Incubate at 55 degrees (16 hours - O/N)
# Incubate at 85 degrees for 60 min
# Hold at 4 degrees

[[Category: Mouse Work]]
[[Category: Molecular Biology]]
[[Category: DNA]]
[[Category: Genotyping]]

LDLR Genotyping

2026-01-20T18:11:05Z

Davebrid: Added tags

Based on https://www.jax.org/Protocol?stockNumber=002207&protocolID=27075

LDLR Genotyping Common - Fwd TAT GCA TCC CCA GTC TTT GG
LDLR Genotyping WT - Rev CTA CCC AAC CAG CCC CTT AC
LDLR Genotyping Mutant - Rev ATA GAT TCG CCC TTG TGT CC

[[ Category:Genotyping ]]
[[ Category:Mouse Work ]]
[[ Category:PCR ]]

LDLR Genotyping

2026-01-20T18:10:19Z

Davebrid: Created initial page, added primers

Analysing Data on Armis or Great Lakes using Rmd Files

2025-09-29T20:29:24Z

Davebrid: /* Creating a Batch Script */ updated log locations

== Software ==

=== On OSX ===
* Install Filezilla for file transfers https://filezilla-project.org/

=== On Windows ===
* Install Putty for command line access https://www.chiark.greenend.org.uk/~sgtatham/putty/latest.html
* Install Filezilla for file transfers https://filezilla-project.org/

== Access ==

At Michigan there are two clusters, one for human data (Armis) and one for non-PHI data (Great Lakes). Both of these are connected to a storage service called [https://arc.umich.edu/turbo/ Turbo]. These are available as part of the [https://arc.umich.edu/UMRCP/ UM Research Computing Package].

=== Permissions ===
* For access to https://datadirect.precisionhealth.umich.edu/, you need to complete these two online classes and have the VPN installed on your device. For more details on access follow [https://precisionhealth.umich.edu/tools-resources/data-access-tools/how-to-access-data-tools-analytic-environments/ these instructions].
** [https://maislinc.umich.edu/core/pillarRedirect?relyingParty=LM&url=app%2Fmanagement%2FLMS_ActDetails.aspx%3FActivityId%3D45901%26UserMode%3D0 PEERS - Human Subjects Research Protections]
** [https://maislinc.umich.edu/core/pillarRedirect?relyingParty=LM&url=%2Flearning%2Fcore%2Factivitydetails%2FViewActivityDetails%3FUserMode%3D0%26CallerURL%3D%252flearning%252fapp%252fmanagement%252fLMS_LearnerReports.aspx%253fUserMode%253d0%26ActivityId%3D45843%26SSOBroker%3D1 HIPAA Training for Self Service Tools].
** You also need an '''approved''' IRB noting that you will use the data direct self-service tools.
** To get access to Armis2 fill out [https://arc-ts.umich.edu/login-request/ this form].

You can access the server either through the command line or through a remote desktop if you prefer a GUI. There a limited functionality to Armis2 here that can also be used (see these [https://arc.umich.edu/armis2/user-guide/ instructions]).

== Deidentified Data Request ==

If you submit a deidentified data request via https://datadirect.precisionhealth.umich.edu, your data will be sent as a 7zip file to the turbo storage in a folder named for your IRB. You will be prompted to enter a password to protect this file, do not lose this password.

== Server Access ==

=== Accessing the Server - Command Line ===

On OSX open a terminal and enter <code>ssh <UNIQNAME>@armis2.arc-ts.umich.edu</code> replacing with your uniqname. Enter your level 1 password. Authenticate using Duo following the instructions. You will be placed in your home folder. Your data should be in <code>/nfs/turbo/precision-health/DataDirect/<YOUR-IRB></code>. I find it convenient to make symlinks to quickly navigate to your data folder so first find your folder name

<code>ls /nfs/turbo/precision-health/DataDirect/</code>

locate the name of your folder <FOLDER_NAME>

create the symlink

<code>ln -s /nfs/turbo/precision-health/DataDirect/<FOLDER_NAME> <LINK_NAME></code>

Now you can navigate from your home folder to your data folder by typing

<code> cd <LINK_NAME></code>

=== Accessing the Server - Remote Desktop ===

* You will need to unzip newly extracted files using the terminal (see [[Extracting Data]]).
* Now go to https://armis2.arc-ts.umich.edu/ and authenticate.
* Click on '''Interactive Apps''', then RStudio, then enter slurm account, set time and memory needed. Usually, the defaults are fine. Click Launch to open a RStudio session, wait a moment then click Launch RStudio, and ignore update.
* Analyse your data using R or Rmd files on this secure environment.
* Pull processed ('''but never raw''') data from the server using Filezilla

== Analyzing Data on the Cluster ==

=== Extracting Data ===

If you have a data archive from DataDirect it will be a password-protected 7zip file. You will need to first install 7zip in your home directory in a bin folder before extracting the archive
<pre>
mkdir bin
cd bin
wget https://www.7-zip.org/a/7z2301-linux-x64.tar.xz
tar -xf 7z2301-linux-x64.tar.xz
7zz
</pre>

If this works you should see the manual entry for 7zip.

To extract your archive move into your working directory and then use the command <code>7zz x '<ARCHIVE>.zip'</code>, entering the password you created in [[#Deidentified Data Request|Deidentified Data Request]]. This should generate a folder containing a series of csv files to be used by your R scripts.

=== Submitting Scripts to the Server ===

==== Configuring R ====
Some R packages may need to be installed in your home folder. To do this go to your home folder <code>cd ~/</code> and enter the following to load the R modules, enter an R shell, install the packages and exit out. You will only have to do this once to install the relevant R packages in your script

<pre>module load R
R
install.packages("PACKAGE_NAME")
exit()
</pre>

Follow the prompts agreeing to make a personal library and using the Michigan mirror (71)

==== Creating a Rmd Script====
I prefer to generate Rmd scripts on my own computer and then transfer them to the data folder to run (see [[#Transferring Files|Transfering Files]] to move scripts onto the server).

==== Creating a Batch Script ====
To submit a job to the server you will need to create a batch script to submit your jobs. The Armis2 and Greatlakes servers use slurm to submit jobs.
Details of how to configure a slurm file can be found [https://arc.umich.edu/armis2/slurm-user-guide here]. Each script can include multiple Rmd files. A sample script is below. Make sure to replace <USER> with your slurm user id and entering a name for the job and your email.

<pre>
#! /bin/bash
#SBATCH --job-name <JOB_NAME>
#SBATCH --nodes=1
#SBATCH --cpus-per-task=1
#SBATCH --mem-per-cpu=2G
#SBATCH --time=00:15:00
#SBATCH --account=<USER>
#SBATCH --partition=standard
#SBATCH --mail-user=<YOUR_EMAIL>
#SBATCH --mail-type=END,FAIL
#SBATCH --output=/home/logs/%u/%x-%j.log
#SBATCH --error=/home/error_logs/%u/error-%x-%j.log

module purge
module load R
module load RStudio

echo "Running from $(pwd)"

Rscript -e "rmarkdown::render('<FIRST_SCRIPT>.Rmd')"
Rscript -e "rmarkdown::render('<SECOND_SCRIPT>.Rmd')"
</pre>

Save this as a <JOB_NAME>.slurm file in your working folder on turbo. The <nowiki>mem-per-cpu</nowiki> and <nowiki>time</nowiki> commands should be adjusted to approximate how complex your job is (if it is too little memory or time you will get an update in the email response).

== Transferring Files ==

Seahorse - Mitochondrial Stress Test

2025-09-02T18:06:32Z

Davebrid: /* The Day of the Assay */ clarified what is being added to ports

[[ Category: Seahorse ]]
[[ Category: Mitochondrial Function ]]
__NOTOC__

==Materials==
* [[Seahorse XF Media]]
* XF Cartridge
* Cells in XF24 plate, either grown in the plate or seeded at a previously established density where the OCR is 40-500 mL/min.
* Injection stock solutions (1 mM Oligomycin, 1 mM FCCP, 1 mM Rotenone and 1 mM Antimycin A) made up in DMSO at 1000X. Aliquots in the -20 in '''Seahorse Reagents''' box.
* Check if the machine is free.

==Protocol==

===The Day Before the Assay===
* Hydrate a cartridge by placing 1 mL/well of XF Calibration Media into each well of a XF24 cartridge. Place in non-CO2, humidified, 37C incubator overnight to hydrate.
* Ensure that there is sufficient XF media and stock solutions.
* Prepare cells if necessary, leave in CO2 incubator overnight. Make sure to leave blank wells (typically A5, B3, C4, D2).

===The Day of the Assay===
* Prepare media by the following steps:
** Place 100mL in non-CO2, humidified, 37C incubator for ~30 minutes to warm up.
** Add the following solutions (these are standard concentrations and may be slightly different for your cell line of interest):
*** 10 mM Glucose (1 mL of a 1M stock into 100 mL)
*** 2 mM Glutamine (1 mL of a 200 mM stock)
*** 1 mM Pyruvate (100 uL of a 1M stock)
** Re-adjust the pH to 7.4 (7.35-7.45)
* Wash cells twice with 500 uL of pre-warmed media, add 500 uL final volume to each well
* Incubate for 1h in non-CO2, humidified, 37C incubator to get rid of any extra CO2
* While plate is incubating, prepare injection solutions in 1.8 mL of prepared XF Media. These are standard concentrations, and should be optimized for your system (especially FCCP)
** '''Tube A''' 18 uL Oligomycin. Will add 56 uL to each port
** '''Tube B''' 18 uL FCCP. Will add 62 uL to each port
** '''Tube C''' 9 uL Rotenone and 9 uL Antimycin A. Will add 69 uL to each port
* Add the compounds to the injection ports in the cartridge (A, bottom right; B bottom left; C top right). '''Make sure the barcode is on the right hand side.'''
* Set up your protocol, editing a similar template and saving with the date and experiment type
* Start the protocol, inserting the cartridge with the lid removed. '''Make sure the barcode is on the right hand side.'''
* Once the cartridge is calibrated insert the cell plate at the prompt. If the calibration fails, abort the run and try the calibration again

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2025-08-12T22:51:30Z

Davebrid: Davebrid moved page User:Davebridges/DeleteRecent to User:Davebrid/DeleteRecent: Automatically moved page while merging the account "Davebridges" to "Davebrid"

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Seahorse - Mitochondrial Stress Test

2025-08-12T19:07:25Z

Davebrid: /* The Day of the Assay */ Updated with volumes of reagents

[[ Category: Seahorse ]]
[[ Category: Mitochondrial Function ]]
__NOTOC__

==Materials==
* [[Seahorse XF Media]]
* XF Cartridge
* Cells in XF24 plate, either grown in the plate or seeded at a previously established density where the OCR is 40-500 mL/min.
* Injection stock solutions (1 mM Oligomycin, 1 mM FCCP, 1 mM Rotenone and 1 mM Antimycin A) made up in DMSO at 1000X. Aliquots in the -20 in '''Seahorse Reagents''' box.
* Check if the machine is free.

==Protocol==

===The Day Before the Assay===
* Hydrate a cartridge by placing 1 mL/well of XF Calibration Media into each well of a XF24 cartridge. Place in non-CO2, humidified, 37C incubator overnight to hydrate.
* Ensure that there is sufficient XF media and stock solutions.
* Prepare cells if necessary, leave in CO2 incubator overnight. Make sure to leave blank wells (typically A5, B3, C4, D2).

===The Day of the Assay===
* Prepare media by the following steps:
** Place 100mL in non-CO2, humidified, 37C incubator for ~30 minutes to warm up.
** Add the following solutions (these are standard concentrations and may be slightly different for your cell line of interest):
*** 10 mM Glucose (1 mL of a 1M stock into 100 mL)
*** 2 mM Glutamine (1 mL of a 200 mM stock)
*** 1 mM Pyruvate (100 uL of a 1M stock)
** Re-adjust the pH to 7.4 (7.35-7.45)
* Wash cells twice with 500 uL of pre-warmed media, add 500 uL final volume to each well
* Incubate for 1h in non-CO2, humidified, 37C incubator to get rid of any extra CO2
* While plate is incubating, prepare injection solutions in 1.8 mL of prepared XF Media. These are standard concentrations, and should be optimized for your system (especially FCCP)
** '''Tube A''' 18 uL Oligomycin. Will add 56 uL
** '''Tube B''' 18 uL FCCP. Will add 62 uL
** '''Tube C''' 9 uL Rotenone and 9 uL Antimycin A. Will add 69 uL
* Add the compounds to the injection ports in the cartridge (A, bottom right; B bottom left; C top right). '''Make sure the barcode is on the right hand side.'''
* Set up your protocol, editing a similar template and saving with the date and experiment type
* Start the protocol, inserting the cartridge with the lid removed. '''Make sure the barcode is on the right hand side.'''
* Once the cartridge is calibrated insert the cell plate at the prompt. If the calibration fails, abort the run and try the calibration again

User:Davebrid/DeleteRecent

2025-08-02T20:18:52Z

Davebrid:

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Rapamycin Stock Solution

2025-04-28T16:36:43Z

Davebrid: updated final concentration which was incorrect

Order from Cayman Chemical as 5 mg per vial (see [https://www.caymanchem.com/app/template/Product.vm/catalog/13346 Cayman website])

Resuspend in DMSO to 100X concentration which is 10 mM.

A 5mg vial therefore gets resuspended in '''547 uL''' based on a molecular weight of 914.2 g/mol

[[ Category: mTORC1 ]]
[[ Category: Rapamycin ]]
[[ Category: Pharmaceuticals ]]

Triglyceride and Glycerol Assay in Milk and Serum

2025-02-10T16:44:16Z

Davebrid: Added mouse work category

== Materials ==
* Sigma Triglyceride Assay Kit (Cat TR0100). Resuspend both the triglyceride (10 mL) and glycerol (40 mL) with water. Reagents are good at 4C for about a month
* Glycerol Standard (0.26 mg/mL or 2.82 mM)
* Serum or milk

==Procedure==
* Plan out plate, including a blank, samples, and space for 7 standards.
* Add 80 uL of glycerol reagent to each well.
* Add 2.5 uL of sample to each well
* Add 0, 0.5, 1, 2, 3, 4, 5 uL to each of the standard wells.
* Incubate at room temperature for 30 mins (or 5 mins at 37C if you are in a hurry)
* Read plate at 510 nM and 700 nM (for scatter)
* Add 20 uL of triglyceride reagent and wait another 30 mins at room temperature
* Re-read plate at same measures.

==Calculations==
* Use the standard curve to calculate glycerol levels (in mM) for before and after the triglyceride reagent.
* '''Glycerol''' levels are the first value
* Triglyceride levels are the mM Glycerol '''After - Before.'''
* To convert to mg/dL use the equation '''Triglycerides (mg/dL) = mM × 88.57396 g/mol'''

[[ Category: Animal Work]]
[[ Category: Assays ]]
[[ Category: Lipids ]]
[[ Category: Milk ]]
[[Category:Mouse Work]]

Monitoring Food Intake

2025-02-10T16:43:40Z

Davebrid: Added categories

*Weigh out 200g of food and place in cage. Try to avoid crumbs
*After a set number of days remove food and re-weigh it.
*Record the difference from 200g and divide by the number of days, the number of mice (and if necessary the weight of the mouse)

[[Category:Animal Work]]
[[Category:Mouse Work]]

Measuring Fasting Insulin

2025-02-10T16:43:29Z

Davebrid: added categories

==Materials==
*Insulin ELISA (Ultra Sensitive Mouse Insulin ELISA Kit from Crystal Chem catalog # 90080)

==Protocol==
#Collect serum (see [[Collecting_and_Storing_Mouse_Serum]])

[[Category:Animal Work]]
[[Category:Mouse Work]]
[[Category:Glucose]]

Insulin Tolerance Test

2025-02-10T16:43:10Z

Davebrid:

Insulin tolerance tests are a standard and common method for evaluating the insulin sensitivity of an animal. In this assay, animals are fasted to normalize blood glucose and then challenged by an intraperitoneal injection of insulin. As glucose is transported into tissues and glucose production is suppressed, glucose levels drop. A more insulin-sensitive animal will have a larger decrease in blood glucose. This has advantages over a glucose tolerance test which measures both insulin sensitivity and insulin responsiveness.

==SOP==
*[[Safety and Animal Training]]
*[[SOP - Needle Capping]]

==Materials (Bring to Room)==
*Glucometer - AccuChek Advantage
*Glucose Test Strips - AccuChek Comfort Curve or equivalent
*Scale
*Beaker for weighing mice
*echoMRI if the mice differ in body fat levels (see below)
*Syringes
*0.1 U/mL humulin in PBS (make as 10uL of 100 U/mL in 10 mL, sterile filtered). This will correspond to 1 U/kg injections. If you are using a higher or lower dose of insulin, add more or less to the 10 mL of PBS, so that injections are 10 uL/g of mass.
**This may need to be adjusted depending on the insulin sensitivity of the mice, and this is based on a normal C57BL/6J mouse on chow.
**In general for insulin resistant mice, such as those >40g on a high fat diet or such, increase the dose to 2 or 2.5U/kg.
** In general you want the insulin to decrease blood glucose by about 60-70% in the most responsive of your too group so if your response is <20% of >70% change in blood glucose you will probably have to change your dose and retry.
**The insulin is diluted from Humulin R-100 and is purchased through the veterinary staff.
*Timer

==Protocol==
*Remove food from mice for about 6h by putting them in a fresh cage. Add do not feed tag to cages, or ideally move cage to procedure room. Try to make sure that the mice are in a quiet, undisturbed temperature controlled room with the lights on.
*Typically starve the mice at 8AM and aim to start injections at 2PM
*Prepare a 1 g/10mL solution of glucose in case some animals become hypoglyemic.
*Weigh mice, mark tails if necessary with different colors for rapid identification and take fasting glucose measurement via a tail clip.
*Prepare insulin syringes with 10 uL per g mouse weight (ie for a 30g mouse, 300 uL).
*At approximately 1 min intervals, inject appropriate amount of insulin into interperitoneal cavity of the mouse.
**Immobilize mouse and restrain tail with one hand
**Aim needle between the midline and the hip bone
**Insert syringe (do not inject) into cavity
**Eject syringe.
*At desired intervals (normally 15, 30, 45, 60, 75, 90, 105 and 120 min), take blood glucose measurements from tail vein. If needed re-snip the tail vein. When measuring glucose just lift the tail of the mouse, while leaving it in the cage, rather than removing and restraining the mouse, which can be more stressful.
**If blood glucose drops below 10 mg/dL, or the animal appears catatonic, inject 300 uL of the glucose solution prepared above to rescue the mice and prevent hypoglycmic shock. Ignore the data from this mouse from that point on.
*Analyze data by both % change from fasting glucose and absolute values. Our preferred outcome is to report fasting glucose levels and report percent change as a figure
*The preferred statistical model is a mixed linear model using the time points as ordinate values and testing for a main effect or an interaction of the treatment/genotype. Use the R [https://cran.r-project.org/web/packages/lme4/lme4.pdf lme4] package for this.

===Taking into Account Differences in Fat Mass===
Since most glucose is taken up into non-fat tissues, it can be confounding if you dose based on total body weight, and the two groups differ greatly with respect to the amount of fat mass. A fat mouse and a lean mouse are likely to have very similar fat-free masses, and by giving more insulin to the fatter animal (because body weight is higher) you might make the fatter mouse seem more insulin sensitive, but really its just responding to a larger amount of insulin. In these cases the preferred practice is to '''measure fat free mass by echoMRI''', and then dose animals at approximately 1 U/kg of lean mass for a lean animal or 2.5 U/kg of lean mass for an obese animal.

[[Category:Animal Work]]
[[Category:Mouse Work]]
[[Category: Glucose]]

Glucose Tolerance Test

2025-02-10T16:42:48Z

Davebrid: added category

==SOP==
*[[SOP - Needle Capping]]
*[[Safety and Animal Training]]

==Materials (Bring to Procedure Room)==
*Glucometer - AccuChek Advantage
*Glucose Test Strips - AccuChek Comfort Curve. Order these through Materiels Service by calling 936-6077 and ordering product 2535. For information see [[https://www31.med.umich.edu/materielsvcs/catalog/details.cfm?stock=2535 here]]. collect in university hospital building, floor B2 in room B2F408 dock 5 across from central pharmacy.
*Scale
*Beaker for weighing mice
*Syringes
*10% Glucose in PBS (make as 1g in 10 mL, sterile filtered). This will correspond to 1g/kg glucose injections.
*If doing an oral glucose tolerance test need a gavage needle
*Timer

==Protocol==
#Remove food from mice for about 6h. Add do not feed tag to cages.
#Bring mice to procedure room. Put water bottle on cage.
#Weigh mice, mark tails as necessary and take fasting glucose measurement. If necessary also take blood for [[Measuring Fasting Insulin]] by filling a heparinized capillary about 2/3 full with blood.
#Prepare glucose syringes with 10 uL per g mouse weight (ie for a 30g mouse, 300 uL).
#At 1 min intervals, inject appropriate amount of glucose into interperitoneal cavity of the mouse or the mouth if doing an oral glucose tolerance test.
##Immobilize mouse and restrain tail with one hand
##'''For ipGTT''' Aim needle between the midline and the hip bone
##'''For oGTT''' Gently inert gavage needle into mouth
##Insert syringe (do not inject) into cavity/mouth
##'''For ipGTT:''' Pull up the syringe and ensure that only air is aspirated. If urine or blood appears in the syringe, start over
##Eject syringe.
#At desired intervals (normally 15, 30, 45, 60, 75, 90, and 120 min), take blood glucose measurements from the tail vein

[[Category:Animal Work]]
[[Category:Mouse Work]]
[[Category:Glucose Homeostasis]]
[[Category:Injections]]

Triglyceride and Glycerol Assay in Milk and Serum

2025-02-10T16:41:51Z

Davebrid: Added milk category

Triglyceride and Glycerol Assay in Milk and Serum

2025-02-10T16:41:24Z

Davebrid: Wrote initial page

Western Blotting

2025-01-20T17:46:54Z

Davebrid: /* Materials */ Added product numbers for some materials

==SOP==
* [[SOP_-_Irritants|SOP - Irritants]]
* [[SOP - Electrophoresis]]

==Materials==
*Protein Markers, we use SeaBlue Plus2 from Invitrogen (cat #LC5925)
*Nitrocellulose, we use BioRad 0.45 um membrane from a roll (cat #1620115) and cut to the size of a gel
*Filter Paper, we use BioRad extra thick paper (cat 1703966)
*Transfer Buffer (200 mL Methanol, 100 mL 10X [[ Transfer Buffer ]] to final 1L volume)
*Transfer Apparatus, either Bio-Rad or Invitrogen

==Protocol==
#Turn on heat block to 85 degrees
#Run SDS-PAGE gel using [[ SDS-PAGE Running Buffer ]] and prepare diluted transfer buffer
## Use a prepared gel (in the 4 degree). Remove it from the packaging, remove the white strip of tape from the bottom back, and gently pull the comb out and rinse with water. Pick a percent gel based on your expected protein size.
##Load into gel tank. Fill with SDS page Running buffer (1X) to the fill line in the front and halfway up the back. For a video on how to use these gel tanks see https://youtu.be/aedIjTtNEus
##Boil sample at 85 degrees for ~3 min
##Load 3 microliters of protein ladder (purple top) (in the 4 degree), and 10 microliters of each sample into separate wells.
## Place top on tank, plug into power source and run at 125 Volts until samples and ladder reach the bottom of the gel. (Tip: Gel runs more evenly if you start a lower V and increase once the samples have run down 1/3 of the gel.)
#Make sandwich (black side, sponge, filter paper, gel, nitrocellulose, filter paper, sponge, clear side), ensuring no bubbles between layers with black piece on bottom and layer as above. Place in apparatus so that the black sandwich touches the black transfer piece. Fill with transfer buffer.
#Transfer 4h at 75V (in cold room) or overnight at 35V (room temp with an ice pack).
#Stain for total protein with Revert total protein stain on rocker for 5 minutes --when finished pour total protein stain back in bottle for later use!
#Rinse twice in revert wash solution (60ml MeOH, 13.4 ml Acetic Acid, 126.6 ml Water)
#Scan using licor for total protein, which will be used to normalize the blot
#Rinse nitrocellulose in revert reversal solution for at least 5 and no more than 10 minutes until nitrocellulose appears clear again (.2g NaOH, 60ml MeOH, 140ml Water)
#Rinse nitrocellulose in 2% BSA (2g BSA in 100ml TBST, stored in fridge) for 1 hour
#Incubate with primary antibody (check for dilution) in 2% BSA for >1h
#Wash blot every 5 minutes for 15 min with TBST.
#Incubate with appropriate secondary antibody (10 000X) for 45min-1h (20 ml 2% BSA 1ul of both secondary antibodies, all found in fridge Ab stocks with blue dots on top)
#Wash blot every 5 minutes for 15 min with TBST.
#Rinse once or twice with double distilled water.
#Scan dry blot using the LiCor Odyssey [[Scanning and Analyzing Western Blots Using LiCor Odyssey]].

==If Using LiCor==

[[Scanning and Analyzing Western Blots Using LiCor Odyssey]]

[[ Category: Western Blotting ]]

Western Blotting

2025-01-20T16:39:17Z

Davebrid: Added link to video

==SOP==
* [[SOP_-_Irritants|SOP - Irritants]]
* [[SOP - Electrophoresis]]

==Materials==
*Transfer Buffer (200 mL Methanol, 100 mL 10X [[ Transfer Buffer ]] to final 1L volume)
*Transfer Apparatus, either Bio-Rad or Invitrogen

==Protocol==
#Turn on heat block to 85 degrees
#Run SDS-PAGE gel using [[ SDS-PAGE Running Buffer ]] and prepare diluted transfer buffer
## Use a prepared gel (in the 4 degree). Remove it from the packaging, remove the white strip of tape from the bottom back, and gently pull the comb out and rinse with water. Pick a percent gel based on your expected protein size.
##Load into gel tank. Fill with SDS page Running buffer (1X) to the fill line in the front and halfway up the back. For a video on how to use these gel tanks see https://youtu.be/aedIjTtNEus
##Boil sample at 85 degrees for ~3 min
##Load 3 microliters of protein ladder (purple top) (in the 4 degree), and 10 microliters of each sample into separate wells.
## Place top on tank, plug into power source and run at 125 Volts until samples and ladder reach the bottom of the gel. (Tip: Gel runs more evenly if you start a lower V and increase once the samples have run down 1/3 of the gel.)
#Make sandwich (black side, sponge, filter paper, gel, nitrocellulose, filter paper, sponge, clear side), ensuring no bubbles between layers with black piece on bottom and layer as above. Place in apparatus so that the black sandwich touches the black transfer piece. Fill with transfer buffer.
#Transfer 4h at 75V (in cold room) or overnight at 35V (room temp with an ice pack).
#Stain for total protein with Revert total protein stain on rocker for 5 minutes --when finished pour total protein stain back in bottle for later use!
#Rinse twice in revert wash solution (60ml MeOH, 13.4 ml Acetic Acid, 126.6 ml Water)
#Scan using licor for total protein, which will be used to normalize the blot
#Rinse nitrocellulose in revert reversal solution for at least 5 and no more than 10 minutes until nitrocellulose appears clear again (.2g NaOH, 60ml MeOH, 140ml Water)
#Rinse nitrocellulose in 2% BSA (2g BSA in 100ml TBST, stored in fridge) for 1 hour
#Incubate with primary antibody (check for dilution) in 2% BSA for >1h
#Wash blot every 5 minutes for 15 min with TBST.
#Incubate with appropriate secondary antibody (10 000X) for 45min-1h (20 ml 2% BSA 1ul of both secondary antibodies, all found in fridge Ab stocks with blue dots on top)
#Wash blot every 5 minutes for 15 min with TBST.
#Rinse once or twice with double distilled water.
#Scan dry blot using the LiCor Odyssey [[Scanning and Analyzing Western Blots Using LiCor Odyssey]].

==If Using LiCor==

[[Scanning and Analyzing Western Blots Using LiCor Odyssey]]

[[ Category: Western Blotting ]]

SOP - Electrophoresis

2025-01-20T16:33:25Z

Davebrid: Added signature

[[ Category: SOP ]]
[[ Category: Lab Safety ]]

==Description==
This standard operating procedure outlines the process of electrophoresis, including the use of equipment and chemicals necessary for the process. Review this document and supply the information required in order to make it specific to your laboratory. In accordance with this document, laboratories should use appropriate controls, personal protective equipment, and disposal techniques when performing electrophoresis.

Electrophoresis uses electrical energy to separate molecules based on their size, structure, and electrical charge.

==Potential Hazards==
Electrophoresis equipment can pose significant electrical hazard in the laboratory. Typical electrophoresis units operating at 100 volts can provide a lethal shock of 25 milliamps. Take the following precautions:

'''Power Supplies:'''
*Inspect to ensure all switches and indicators are in proper working condition and that power cords and leads are undamaged and properly insulated.
*Label equipment with warning: “Danger Electrical Hazard.”
*Connect to ground fault circuit interrupters (GFCIs).
*Use 3-prong plugs.
*Use power supplies with safety features that detect no-load, overload, sudden load change, short circuit, arc or ground leak, etc.

'''Connecting Leads:'''
*Turn off main power supply before connecting or disconnecting electrical leads.
*With dry gloved hands, connect one lead at a time using one hand only.
*Be sure that leads/banana plugs are fully seated.

'''Using Equipment:'''
*Don’t run equipment unattended.
*Keep equipment clear of unintentional grounding points and conductors (e.g., sinks or other water sources, metal plates, jewelry, aluminum foil, pipes or other electrical/metal equipment).
*Gel chamber must have a lid or cover with safety interlocks to prevent accidental contact with energized electrodes or buffer solutions.
*Gel chamber exterior must be dry with no spilled solutions. Check for leaks.
*Switch off all power and unplug the leads before opening the gel chamber lid or reaching inside the gel chamber.
�
'''Hazardous chemicals'''
Commonly used in conjunction with electrophoresis work include:
*Ethidium bromide – mutagen, irritant
*Acrylamide – carcinogen, neurotoxin, irritant
*Phenol – corrosive, toxic
*Chloroform – suspect carcinogen, toxic

Always review the Safety Data Sheet prior to working with any hazardous material.
Laboratory personnel may be exposed to thermal hazards posed by liquefied gels.

'''Ultraviolet''' (UV) light boxes are often used in visualizing ethidium bromide gels and pose potential exposures to UV radiation.

==Engineering and Work Practice Controls==
*Read and follow manufacturer’s instructions for electrophoresis equipment.
*Prepare Standard Operating Procedure relevant to health and safety.
*Consult with Lab Director prior to initial use of electrophoresis equipment. Discussion should include special hazards and safety precautions.
*Measure, mix and handle all hazardous powdered chemicals or gel prep mixtures with hazardous components (e.g., acrylamide monomer, ethidium bromide, phenol, ammonium persulfate, and formaldehyde) in a fume hood.
*Purchase pre-made gels or pre-mixed acrylamide and ethidium bromide solutions instead of making your own.
*Consider using ethidium bromide substitutes.
*Exercise caution when using microwave to liquefy gels – don’t use sealed containers, beware of superheated liquids that may froth up unexpectedly. Let hot gel preps cool to 50°-60°C before adding ethidium bromide or pouring into trays. Wear insulated gloves and point the flask opening away from you.

==Protective Equipment==
*Wear lab coat with fully extended sleeves, safety glasses or splash goggles if appropriate, nitrile gloves (latex is not effective), pants, and closed-toe shoes.
*Wear appropriate skin and eye protection for UV radiation work.

==Waste Disposal==
'''Hazardous Waste Management:''' Handle and store hazardous waste following the guidelines above for work practice controls, transportation and storage. Contact OSEH Hazardous Materials Management (HMM) at 734-763-4568 with questions and to schedule a pickup of hazardous waste. For more information regarding chemical waste, refer to the HMM section on OSEH’s website at http://www.oseh.umich.edu/hazmats/chemical.shtml.

'''Non-Hazardous Waste Management:''' Some gels may be considered non-hazardous but still present a health hazard if untreated or discarded into the normal trash. Contact HMM for proper collection and disposal.

==Exposures/Unintended Contact==

If the employee is in need of emergency medical attention, call 911 immediately.

For an actual chemical exposure/injury:
*Remove contaminated clothing. Flush exposed eyes or skin with water for at least 15 minutes. Seek medical attention (see below).
*For inhalation exposure, remove all persons from the contaminated area. Get medical aid.
*If an ambulance is needed, call the University of Michigan Division of Public Safety and Security (DPSS) at 911 to request assistance.

Contact OSEH for advice on symptoms of chemical exposure, or assistance in performing an exposure assessment.

Report all work related accidents, injuries, illnesses or exposures to WorkConnections within 24 hours by completing and submitting the Illness and Injury Report Form. Follow the directions on the WorkConnections website Forms Instructions to obtain proper medical treatment and follow-up.

Complete the OSEH Laboratory Incident and Near-Miss Report form.

==Treatment Facilities:==
*U-M Occupational Health Services -- Campus Employees
Mon-Fri 7:30 am - 4:30 pm
After hours - go to UM Hospital Emergency Dept. – Urgent Care Clinic
C380 Med Inn building
1500 East Medical Center Drive, Ann Arbor (734) 764-8021
*University Health Services -- University students (non-life threatening conditions)
Mon-Fri 8 am – 4:30 pm, Sat 9 am – 12 pm
Contact for current hours as they may vary
207 Fletcher Street, Ann Arbor (734) 764-8320
*UMHS Emergency Department -- after clinic hours or on weekends
1500 East Medical Center Drive, Ann Arbor, (734) 936-6666

Click here for more information.

==Spill Procedure==
*When a spill occurs, personal safety should always come first.
*Alert and clear everyone in the immediate area where the spill occurred.
*Follow spill procedures described in the SOP and SDS for the particular chemical spilled.

'''Report all emergencies, suspicious activity, injuries, spills, and fires to the University of Michigan Division of Public Safety and Security (DPSS) by calling 911 or texting 377911. Register with the University of Michigan Emergency Alert System via Wolverine Access.
'''

==Training of Personnel==

All personnel are required to complete the General Laboratory Safety Training session (BLS025w or equivalent) via OSEH’s My LINC website. Furthermore, all personnel shall read and fully adhere to this SOP when performing electrophoresis.

==Certification==
I have read and understand the above SOP. I agree to contact my Supervisor or Lab manager if I plan to modify this procedure. Sign by logging in and typing <nowiki>* ~~~~</nowiki> in the list below:

* [[User:Kkistler|Kkistler]] ([[User talk:Kkistler|talk]]) 21:08, 7 January 2019 (UTC)
*[[User:Reddj|Reddj]] ([[User talk:Reddj|talk]]) 15:00, 13 October 2016 (UTC)
*[[User:Iharvey|Iharvey]] ([[User talk:Iharvey|talk]]) 21:19, 10 November 2016 (UTC)
*[[User:Mollyec|Mollyec]] ([[User talk:Mollyec|talk]]) 16:15, 31 October 2016 (UTC)
*[[User:Pfeiferl|Pfeiferl]] ([[User talk:Pfeiferl|talk]]) 18:10, 5 June 2017 (UTC)
* [[User:Snyderds|Snyderds]] ([[User talk:Snyderds|talk]]) 19:12, 7 June 2017 (UTC)
* [[User:Elhabbal|Elhabbal]] ([[User talk:Elhabbal|talk]]) 21:57, 12 June 2017 (UTC)
* [[User:Allmeyer|Allmeyer]] ([[User talk:Allmeyer|talk]]) 21:50, 15 January 2020 (UTC)
* [[User:Ccousz|Ccousz]] ([[User talk:Ccousz|talk]]) 13:16, 6 June 2022 (UTC)
* [[User:Davebridges|Davebridges]] ([[User talk:Davebridges|talk]]) 16:33, 20 January 2025 (UTC)
Prior Approval required – Is this procedure hazardous enough to warrant prior approval from the Laboratory Director? ☐ YES ☒ NO

Laboratory Director - Dave Bridges Revision Date - 2016-10-13

SOP - Irritants

2025-01-20T16:32:53Z

Davebrid: /* Certification */

[[Category: SOP]]
[[Category: Lab Safety]]

==Description==
This standard operating procedure outlines the handling and use of irritant chemicals. Review this document and supply the information required in order to make it specific to your laboratory. In accordance with this document, laboratories should use appropriate controls, personal protective equipment, and disposal techniques when handling irritant chemicals.

A chemical irritant is one that is not corrosive but that causes a reversible inflammatory effect on living tissue by chemical action at the site of contact.

==Potential Hazards==
Irritants are chemicals that cause reversible inflammatory effects on living tissue by chemical action at the site of contact. A wide variety of organic and inorganic compounds are irritants; thus, skin contact with all laboratory chemicals should be avoided.
* Substances that may cause eye irritation include: YPD broth, Triton X-100, Trizma base, sodium pyrophosphate decahydrate, sodium fluoride, sodium dodecyl sulfate, poncaeu S, lithium chloride, Luria broth, glycerol, water-soluble dexamethasone, corn oil, and chloroform.
* Substances that may cause skin irritation include: Calcium chloride dehydrate, chloroform, corn oil, water-soluble dexamethasone, luria broth, lithium chloride, Meyer’s hematoxylin, limonene mount, ponceau S, sodium dodceyl sulfate, sodium pyrophosphate decahydrate, trizma base, and YPD broth.
* Substances that may cause respiratory irritation include: YPD broth, trizma base, sodium pyrophosphate decahydrate, sodium dodceyl sulfate, sodium deoxycholate, ponceau S, lithium chloride, luria broth, water soluble dexamethasone, corn oil, and calcium chloride dihydrate.

==Engineering Controls==
Use a properly functioning lab fume hood when handling irritants that can be inhaled (via mist/fume/gas/vapor). If the process does not permit the handing of such materials in a fume hood, contact Occupational Safety and Environmental Health (OSEH) at (734) 647-1143 to review the adequacy of ventilation measures.

==Work Practice Controls==
Handling processes should be designed to minimize the potential for splash, splatter, or other likely scenarios for accidental contact.

Ensure secondary containment and segregation of incompatible chemicals per guidance within the substance-specific storage guidance provided in SDS documentation.
To prevent contact with irritants, be sure to handle them carefully with the proper PPE.

For irritants that are also considered particularly hazardous substances, a designated area shall be established per other applicable SOPs.

==Personal Protective Equipment==
At minimum, safety glasses, lab coat, long pants, and closed toe shoes are to be worn when entering laboratories having hazardous chemicals.
Additionally:
* When handling hazardous chemicals or contacting potentially contaminated surfaces, protective gloves are to be worn. For proper selection of glove material, review the chemical-specific SDS.
* Goggles (not safety glasses) are appropriate for processes where splash or spray is foreseeable.
* For hazardous chemicals that are toxic via skin contact/ absorption, additional protective clothing (i.e., face shield, apron, oversleeves) is appropriate where chemical contact with body/skin is foreseeable.

==Transportation and Storage==
* Transport irritant chemicals in secondary containment, preferably a polyethylene or other non-reactive bottle carrier.
* Store in well-ventilated areas with secondary containment, such as a non-reactive plastic bin.
* Store below eye level.
* Store away from incompatibles. Review the chemical’s SDS for incompatibility information. Also refer to OSEH’s Chemical Storage webpage for more information.
* Avoid storing on the floor. If storing on the floor is necessary, use secondary containment.

==Waste Disposal==
Irritant substances intended for disposal may likely be considered hazardous wastes. Wherever possible, attempt to design research in a manner that reduces the quantity of waste generated. Contact OSEH’s Hazardous Materials Management (HMM) at (734) 763-4568 for waste containers, labels, manifests, and waste collection. Also refer to OSEH’s Hazardous Waste webpage for more information.

==Exposures/Unintended Contact==

If the employee is in need of emergency medical attention, call 911 immediately.

===For an actual chemical exposure/injury,===
* Flush exposed eyes or skin with water for at least 15 minutes, then seek medical attention (see below).
* Consult SDS for guidance on appropriate first aid. Where medical attention is required, be sure to bring along SDS(s) of chemical(s) to aid medical staff in proper diagnosis and treatment.
Contact OSEH for advice on symptoms of chemical exposure, or assistance in performing an exposure assessment.

Report all work related accidents, injuries, illnesses or exposures to WorkConnections within 24 hours by completing and submitting the Illness and Injury Report Form. Follow the directions on the WorkConnections website Forms Instructions to obtain proper medical treatment and follow-up.

Complete the OSEH Laboratory Incident and Near-Miss Report form.

===TREATMENT FACILITIES:===
===U-M Occupational Health Services -- Campus Employees===
Mon-Fri 7:30 am - 4:30 pm
After hours - go to UM Hospital Emergency Dept. – Urgent Care Clinic
C380 Med Inn building
1500 East Medical Center Drive, Ann Arbor (734) 764-8021
===University Health Services -- University students (non-life threatening conditions)===
Mon-Fri 8 am – 4:30 pm, Sat 9 am – 12 pm
Contact for current hours as they may vary
207 Fletcher Street, Ann Arbor (734) 764-8320
===UMHS Emergency Department -- after clinic hours or on weekends===
1500 East Medical Center Drive, Ann Arbor, (734) 936-6666
Click here for more information.

==Spill Procedure==
Prompt response to chemical spills is critical to protect worker health & safety and to mitigate adverse effects to the environment. For further guidance, refer to chemical-specific MSDS.

A minor (small) chemical spill is one that the laboratory staff is capable of handling safely without the assistance of safety and emergency personnel, i.e., less than 1 gallon or 3.5 liters. A major/large chemical spill requires active assistance from emergency personnel.

===MINOR CHEMICAL SPILL===
* Alert people in immediate area of spill.
* If spilled material is flammable, turn off ignition and heat sources. Don’t light Bunsen burners or turn on other switches.
* Open outside windows, if possible.
* Wear protective equipment, including safety goggles, gloves and long-sleeve lab coat.
* Avoid breathing vapors from spill.
* Confine spill to as small an area as possible.
* Do not wash spill down the drain.
* Use appropriate spill kits/sorbents to absorb spill. Collect contaminated materials and residues and place in container. For powdered chemicals sweep carefully to avoid generation of dust or, if appropriate, use moist sorbent pads or wet the powder with a suitable solvent and then wipe with a dry cloth. Contact OSEH-HMM (734) 763-4568 for proper disposal.
* Clean spill area with water.

===MAJOR CHEMICAL SPILL===
* Attend to injured or contaminated persons and remove them from exposure.
* Alert people in the laboratory to evacuate.
* If spilled material is flammable, turn off ignition and heat sources. Don’t light Bunsen burners or turn on other switches.
* Call University of Michigan Division of Public Safety and Security (DPSS) at 911 immediately for assistance.
* Close doors to affected area.
* Post warnings to keep people from entering the area.
* Have person available that has knowledge of incident and laboratory to assist emergency personnel.

Additional Spill Links:
* www.oseh.umich.edu/pdf/chemspil.pdf
* http://www.oseh.umich.edu/emer-chemical.shtml.

Report all emergencies, suspicious activity, injuries, spills, and fires to the University of Michigan Division of Public Safety and Security (DPSS) by calling 911 or texting 377911. Register with the University of Michigan Emergency Alert System via Wolverine Access.

==Training of Personnel==
All personnel are required to complete the General Laboratory Safety Training session (BLS025w or equivalent) via OSEH’s My LINC website. Furthermore, all personnel shall read and fully adhere to this SOP when handling irritant chemicals.

==Certification==
I have read and understand the above SOP. I agree to contact my Supervisor or Lab manager if I plan to modify this procedure. Sign by logging in and typing <nowiki>* ~~~~</nowiki> in the list below:

* [[User:Kkistler|Kkistler]] ([[User talk:Kkistler|talk]]) 21:09, 7 January 2019 (UTC)
*[[User:Iharvey|Iharvey]] ([[User talk:Iharvey|talk]]) 21:27, 10 November 2016 (UTC)
*[[User:Mollyec|Mollyec]] ([[User talk:Mollyec|talk]]) 16:14, 31 October 2016 (UTC)
* [[User:Snyderds|Snyderds]] ([[User talk:Snyderds|talk]]) 19:52, 7 June 2017 (UTC)
*[[User:Reddj|Reddj]] ([[User talk:Reddj|talk]]) 14:05, 9 June 2017 (UTC)
* [[User:Elhabbal|Elhabbal]] ([[User talk:Elhabbal|talk]]) 22:15, 12 June 2017 (UTC)
* [[User:Allmeyer|Allmeyer]] ([[User talk:Allmeyer|talk]]) 21:57, 15 January 2020 (UTC)
* [[User:Ccousz|Ccousz]] ([[User talk:Ccousz|talk]]) 13:17, 6 June 2022 (UTC)
* [[User:Davebridges|Davebridges]] ([[User talk:Davebridges|talk]]) 16:32, 20 January 2025 (UTC)
Prior Approval required – Is this procedure hazardous enough to warrant prior approval from the Laboratory Director? ☐ YES X NO
Laboratory Director - Dave Bridges Revision Date - 2016-10-19

SOP - Irritants

2025-01-20T16:32:31Z

Davebrid: /* Certification */ Added certification

[[Category: SOP]]
[[Category: Lab Safety]]

==Description==
This standard operating procedure outlines the handling and use of irritant chemicals. Review this document and supply the information required in order to make it specific to your laboratory. In accordance with this document, laboratories should use appropriate controls, personal protective equipment, and disposal techniques when handling irritant chemicals.

A chemical irritant is one that is not corrosive but that causes a reversible inflammatory effect on living tissue by chemical action at the site of contact.

==Potential Hazards==
Irritants are chemicals that cause reversible inflammatory effects on living tissue by chemical action at the site of contact. A wide variety of organic and inorganic compounds are irritants; thus, skin contact with all laboratory chemicals should be avoided.
* Substances that may cause eye irritation include: YPD broth, Triton X-100, Trizma base, sodium pyrophosphate decahydrate, sodium fluoride, sodium dodecyl sulfate, poncaeu S, lithium chloride, Luria broth, glycerol, water-soluble dexamethasone, corn oil, and chloroform.
* Substances that may cause skin irritation include: Calcium chloride dehydrate, chloroform, corn oil, water-soluble dexamethasone, luria broth, lithium chloride, Meyer’s hematoxylin, limonene mount, ponceau S, sodium dodceyl sulfate, sodium pyrophosphate decahydrate, trizma base, and YPD broth.
* Substances that may cause respiratory irritation include: YPD broth, trizma base, sodium pyrophosphate decahydrate, sodium dodceyl sulfate, sodium deoxycholate, ponceau S, lithium chloride, luria broth, water soluble dexamethasone, corn oil, and calcium chloride dihydrate.

==Engineering Controls==
Use a properly functioning lab fume hood when handling irritants that can be inhaled (via mist/fume/gas/vapor). If the process does not permit the handing of such materials in a fume hood, contact Occupational Safety and Environmental Health (OSEH) at (734) 647-1143 to review the adequacy of ventilation measures.

==Work Practice Controls==
Handling processes should be designed to minimize the potential for splash, splatter, or other likely scenarios for accidental contact.

Ensure secondary containment and segregation of incompatible chemicals per guidance within the substance-specific storage guidance provided in SDS documentation.
To prevent contact with irritants, be sure to handle them carefully with the proper PPE.

For irritants that are also considered particularly hazardous substances, a designated area shall be established per other applicable SOPs.

==Personal Protective Equipment==
At minimum, safety glasses, lab coat, long pants, and closed toe shoes are to be worn when entering laboratories having hazardous chemicals.
Additionally:
* When handling hazardous chemicals or contacting potentially contaminated surfaces, protective gloves are to be worn. For proper selection of glove material, review the chemical-specific SDS.
* Goggles (not safety glasses) are appropriate for processes where splash or spray is foreseeable.
* For hazardous chemicals that are toxic via skin contact/ absorption, additional protective clothing (i.e., face shield, apron, oversleeves) is appropriate where chemical contact with body/skin is foreseeable.

==Transportation and Storage==
* Transport irritant chemicals in secondary containment, preferably a polyethylene or other non-reactive bottle carrier.
* Store in well-ventilated areas with secondary containment, such as a non-reactive plastic bin.
* Store below eye level.
* Store away from incompatibles. Review the chemical’s SDS for incompatibility information. Also refer to OSEH’s Chemical Storage webpage for more information.
* Avoid storing on the floor. If storing on the floor is necessary, use secondary containment.

==Waste Disposal==
Irritant substances intended for disposal may likely be considered hazardous wastes. Wherever possible, attempt to design research in a manner that reduces the quantity of waste generated. Contact OSEH’s Hazardous Materials Management (HMM) at (734) 763-4568 for waste containers, labels, manifests, and waste collection. Also refer to OSEH’s Hazardous Waste webpage for more information.

==Exposures/Unintended Contact==

If the employee is in need of emergency medical attention, call 911 immediately.

===For an actual chemical exposure/injury,===
* Flush exposed eyes or skin with water for at least 15 minutes, then seek medical attention (see below).
* Consult SDS for guidance on appropriate first aid. Where medical attention is required, be sure to bring along SDS(s) of chemical(s) to aid medical staff in proper diagnosis and treatment.
Contact OSEH for advice on symptoms of chemical exposure, or assistance in performing an exposure assessment.

Report all work related accidents, injuries, illnesses or exposures to WorkConnections within 24 hours by completing and submitting the Illness and Injury Report Form. Follow the directions on the WorkConnections website Forms Instructions to obtain proper medical treatment and follow-up.

Complete the OSEH Laboratory Incident and Near-Miss Report form.

===TREATMENT FACILITIES:===
===U-M Occupational Health Services -- Campus Employees===
Mon-Fri 7:30 am - 4:30 pm
After hours - go to UM Hospital Emergency Dept. – Urgent Care Clinic
C380 Med Inn building
1500 East Medical Center Drive, Ann Arbor (734) 764-8021
===University Health Services -- University students (non-life threatening conditions)===
Mon-Fri 8 am – 4:30 pm, Sat 9 am – 12 pm
Contact for current hours as they may vary
207 Fletcher Street, Ann Arbor (734) 764-8320
===UMHS Emergency Department -- after clinic hours or on weekends===
1500 East Medical Center Drive, Ann Arbor, (734) 936-6666
Click here for more information.

==Spill Procedure==
Prompt response to chemical spills is critical to protect worker health & safety and to mitigate adverse effects to the environment. For further guidance, refer to chemical-specific MSDS.

A minor (small) chemical spill is one that the laboratory staff is capable of handling safely without the assistance of safety and emergency personnel, i.e., less than 1 gallon or 3.5 liters. A major/large chemical spill requires active assistance from emergency personnel.

===MINOR CHEMICAL SPILL===
* Alert people in immediate area of spill.
* If spilled material is flammable, turn off ignition and heat sources. Don’t light Bunsen burners or turn on other switches.
* Open outside windows, if possible.
* Wear protective equipment, including safety goggles, gloves and long-sleeve lab coat.
* Avoid breathing vapors from spill.
* Confine spill to as small an area as possible.
* Do not wash spill down the drain.
* Use appropriate spill kits/sorbents to absorb spill. Collect contaminated materials and residues and place in container. For powdered chemicals sweep carefully to avoid generation of dust or, if appropriate, use moist sorbent pads or wet the powder with a suitable solvent and then wipe with a dry cloth. Contact OSEH-HMM (734) 763-4568 for proper disposal.
* Clean spill area with water.

===MAJOR CHEMICAL SPILL===
* Attend to injured or contaminated persons and remove them from exposure.
* Alert people in the laboratory to evacuate.
* If spilled material is flammable, turn off ignition and heat sources. Don’t light Bunsen burners or turn on other switches.
* Call University of Michigan Division of Public Safety and Security (DPSS) at 911 immediately for assistance.
* Close doors to affected area.
* Post warnings to keep people from entering the area.
* Have person available that has knowledge of incident and laboratory to assist emergency personnel.

Additional Spill Links:
* www.oseh.umich.edu/pdf/chemspil.pdf
* http://www.oseh.umich.edu/emer-chemical.shtml.

Report all emergencies, suspicious activity, injuries, spills, and fires to the University of Michigan Division of Public Safety and Security (DPSS) by calling 911 or texting 377911. Register with the University of Michigan Emergency Alert System via Wolverine Access.

==Training of Personnel==
All personnel are required to complete the General Laboratory Safety Training session (BLS025w or equivalent) via OSEH’s My LINC website. Furthermore, all personnel shall read and fully adhere to this SOP when handling irritant chemicals.

==Certification==
I have read and understand the above SOP. I agree to contact my Supervisor or Lab manager if I plan to modify this procedure. Sign by logging in and typing <nowiki>* ~~~~</nowiki> in the list below:

* [[User:Kkistler|Kkistler]] ([[User talk:Kkistler|talk]]) 21:09, 7 January 2019 (UTC)
*[[User:Iharvey|Iharvey]] ([[User talk:Iharvey|talk]]) 21:27, 10 November 2016 (UTC)
*[[User:Mollyec|Mollyec]] ([[User talk:Mollyec|talk]]) 16:14, 31 October 2016 (UTC)
* [[User:Snyderds|Snyderds]] ([[User talk:Snyderds|talk]]) 19:52, 7 June 2017 (UTC)
*[[User:Reddj|Reddj]] ([[User talk:Reddj|talk]]) 14:05, 9 June 2017 (UTC)
* [[User:Elhabbal|Elhabbal]] ([[User talk:Elhabbal|talk]]) 22:15, 12 June 2017 (UTC)
* [[User:Allmeyer|Allmeyer]] ([[User talk:Allmeyer|talk]]) 21:57, 15 January 2020 (UTC)
* [[User:Ccousz|Ccousz]] ([[User talk:Ccousz|talk]]) 13:17, 6 June 2022 (UTC)
* [[User:Davebridges|Davebridges]] ([[User talk:Davebridges|talk]])
Prior Approval required – Is this procedure hazardous enough to warrant prior approval from the Laboratory Director? ☐ YES X NO
Laboratory Director - Dave Bridges Revision Date - 2016-10-19

Western Blotting

2025-01-20T16:31:55Z

Davebrid: /* SOP */ Added links to SOPs

==SOP==
* [[SOP_-_Irritants|SOP - Irritants]]
* [[SOP - Electrophoresis]]

==Materials==
*Transfer Buffer (200 mL Methanol, 100 mL 10X [[ Transfer Buffer ]] to final 1L volume)
*Transfer Apparatus, either Bio-Rad or Invitrogen

==Protocol==
#Turn on heat block to 85 degrees
#Run SDS-PAGE gel using [[ SDS-PAGE Running Buffer ]] and prepare diluted transfer buffer
## Use a prepared 4-12% tris gel (in the 4 degree). Remove it from the packaging, remove the white strip of tape from the bottom back, and gently pull the comb out and rinse with water.
##Load into gel tank. Fill with SDS page Running buffer (1X) to the fill line in the front and halfway up the back
##Boil sample at 85 degrees for ~3 min
##Load 3 microliters of protein ladder (purple top) (in the 4 degree), and 10 microliters of each sample into separate wells.
## Place top on tank, plug into power source and run at 125 Volts until samples and ladder reach the bottom of the gel. (Tip: Gel runs more evenly if you start a lower V and increase once the samples have run down 1/3 of the gel.)
#Make sandwich (black side, sponge, filter paper, gel, nitrocellulose, filter paper, sponge, clear side), ensuring no bubbles between layers with black piece on bottom and layer as above. Place in apparatus so that the black sandwich touches the black transfer piece. Fill with transfer buffer.
#Transfer 4h at 75V (in cold room) or overnight at 35V (room temp with an ice pack).
#Stain for total protein with Revert total protein stain on rocker for 5 minutes --when finished pour total protein stain back in bottle for later use!
#Rinse twice in revert wash solution (60ml MeOH, 13.4 ml Acetic Acid, 126.6 ml Water)
#Scan using licor for total protein, which will be used to normalize the blot
#Rinse nitrocellulose in revert reversal solution for at least 5 and no more than 10 minutes until nitrocellulose appears clear again (.2g NaOH, 60ml MeOH, 140ml Water)
#Rinse nitrocellulose in 2% BSA (2g BSA in 100ml TBST, stored in fridge) for 1 hour
#Incubate with primary antibody (check for dilution) in 2% BSA for >1h
#Wash blot every 5 minutes for 15 min with TBST.
#Incubate with appropriate secondary antibody (10 000X) for 45min-1h (20 ml 2% BSA 1ul of both secondary antibodies, all found in fridge Ab stocks with blue dots on top)
#Wash blot every 5 minutes for 15 min with TBST.
#Rinse once or twice with double distilled water.
#Scan dry blot using the LiCor Odyssey [[Scanning and Analyzing Western Blots Using LiCor Odyssey]].

==If Using LiCor==

[[Scanning and Analyzing Western Blots Using LiCor Odyssey]]

[[ Category: Western Blotting ]]

Determining Cortisol Levels in Human Hair

2025-01-16T17:34:40Z

Davebrid: /* Addition of the reagents */ added break for overnight

== Materials ==
* Hair samples collected and stored at -20
* Cayman Chemicals Cortisol Assay Kit (catalog 500360)
* Clean scissors and tweezers
* Spray bottle of methanol
* Glass slide with 1cm intervals marked

== Procedure ==

=== Preparation of hair samples ===
* Stick one side of the hair sample on a plate, use tweezers to grip the hair, use scissors to cut 1 cm hair sample.
* Weigh the hair sample, and add 400uL hexane per mg hair sample. '''Record the weight of the hair by weighing the empty 2 mL tube, adding the hair and re-weighing it.'''
* Place 35 mg of hair into a clean tissue homogenizer tube, add 1.5 ml of hexane, and incubate at room temperature for 2 minutes.
* Remove hexane from the tube and dry the hair under a gentle stream of nitrogen.
* Cap the tube and flash freeze the hair sample with liquid nitrogen.
* Use homogenizer to grind the hair sample at 6,800 rpm, 5x20s cycles, pausing for 30 seconds between the cycles.
* Add 1.8 ml of methanol, vortex, and rock '''overnight''' on a shaker at room temperature.
---
* Collect methanol into a clean test tube. Second tubes (2mL)
* Evaporate methanol under a gentle stream of nitrogen at 37°C.
* Reconstitute in 400 µl of ELISA Buffer (1X) and analyze in the assay

=== Preparation of the assay reagents ===
==== ELISA Buffer (1X) Preparation ====
* Dilute the contents of one vial of ELISA Buffer Concentrate (10X) (Item No.400060) with 90 ml of ultrapure water. Be certain to rinse the vial to remove any salts that may have precipitated.
* Wash Buffer (1X) Preparation (Item No. 400062)
* Dilute to a total volume of 2L with ultrapure water and add 1 ml of Polysorbate 20.

==== Preparation of Cortisol ELISA Standard ====
* Equilibrate a pipette tip by repeatedly filling and expelling the tip with the Cortisol ELISA Standard (Item No. 400364) several times.
* Using the equilibrated pipette tip, transfer 100 µl of the standard into a clean test tube, then dilute with 900 µl ultrapure water → 40 ng/ml.
* Obtain eight clean test tubes and label them #1-8.
* Aliquot 900 µl ELISA Buffer (1X) to tube #1 and 600 µl ELISA Buffer (1X) to tubes #2-8.
* Transfer 100 µl of the bulk standard (40 ng/ml) to tube #1 and mix thoroughly.
* Dilute the standard by removing 400 µl from tube #1 and placing it in tube #2, mix thoroughly.
* Remove 400 µl from tube #2 and place it into tube #3, mix thoroughly. Repeat this process for tubes #4-8.
* Diluted standards should not be stored for more than 24 hours

==== Preparation of Cortisol-AChE Tracer ====
* Reconstitute the Cortisol-AChE Tracer (Item No. 10005272) with 6 ml of ELISA Buffer (1X).

==== Preparation of Cortisol ELISA Monoclonal Antibody ====
* Reconstitute the Cortisol ELISA Monoclonal Antibody (Item No. 400362) with 6 ml of ELISA Buffer (1X).

=== Setting up an assay plate ===
* Draw out a 96 well grid (8 x 12) labelling where you intend to put the blanks, standards,

==== Addition of the reagents ====
* Add 100 µl ELISA Buffer (1X) to NSB wells.
* Add 50 µl ELISA Buffer (1X) to blank wells.
* Add 50 µl from standard tube #8 to both of the lowest standard wells. Add 50 µl from standard tube #7 to each of the next standard wells. Continue with this procedure until all the standards are aliquoted. (The same pipette tip should be used to aliquot all the standards. Before pipetting each standard, be sure to equilibrate the pipette tip in that standard.)
* Add 50 µl of sample per well. Each sample should be assayed in duplicate (triplicate recommended).
* Using the multichannel pipet add 50 µl Cortisol-AChE Tracer to each well except the TA and the blank wells.
* Using the multichannel pipet add 50 µl Cortisol ELISA Monoclonal Antibody to each well except the TA, NSB and the blank wells, within 15 min of addition of the tracer.
* Cover each plate with a 96-Well Cover Sheet (Item No. 400012) and incubate overnight at 4°C.
---
* Reconstitute Ellman’s Reagent (Item No. 400050) immediately before use. Reconstitute 100 dtn vial with 20 ml of ultrapure water. Reconstitute 250 dtn vial with 50 ml of ultrapure water.
* Empty the wells and rinse five times with ~300 µl Wash Buffer (1X).
* Add 200 µl of Ellman’s Reagent to each well.
* Add 5 µl of the reconstituted tracer to the TA wells.
* Cover the plate with the 96-Well Cover Sheet. Optimum development is obtained by using an orbital shaker equipped with a large, flat cover to allow the plate(s) to develop in the dark at room temperature. This assay typically develops (i.e., B0 wells ≥0.6 A.U. (Blk subtracted)) in 90-120 minute

=== Reading the plate ===
* Wipe the bottom of the plate with a clean tissue to remove fingerprints, dirt, etc.
* Remove the cover sheet being careful to keep Ellman’s Reagent from splashing on the cover.
* Read the plate at a wavelength between 405 and 420 nm. The absorbance may be checked periodically until the B0 wells have reached a minimum of 0.3 A.U. (Blk subtracted). The plate should be read when the absorbance of the B0 wells is in the range of 0.3-1.0 A.U. (Blk subtracted). If the absorbance of the wells exceeds 1.5 A.U., wash the plate, add fresh Ellman’s Reagent, and let it develop again.

Determining Cortisol Levels in Human Hair

2025-01-16T17:34:13Z

Davebrid: /* Materials */

== Materials ==
* Hair samples collected and stored at -20
* Cayman Chemicals Cortisol Assay Kit (catalog 500360)
* Clean scissors and tweezers
* Spray bottle of methanol
* Glass slide with 1cm intervals marked

== Procedure ==

=== Preparation of hair samples ===
* Stick one side of the hair sample on a plate, use tweezers to grip the hair, use scissors to cut 1 cm hair sample.
* Weigh the hair sample, and add 400uL hexane per mg hair sample. '''Record the weight of the hair by weighing the empty 2 mL tube, adding the hair and re-weighing it.'''
* Place 35 mg of hair into a clean tissue homogenizer tube, add 1.5 ml of hexane, and incubate at room temperature for 2 minutes.
* Remove hexane from the tube and dry the hair under a gentle stream of nitrogen.
* Cap the tube and flash freeze the hair sample with liquid nitrogen.
* Use homogenizer to grind the hair sample at 6,800 rpm, 5x20s cycles, pausing for 30 seconds between the cycles.
* Add 1.8 ml of methanol, vortex, and rock '''overnight''' on a shaker at room temperature.
---
* Collect methanol into a clean test tube. Second tubes (2mL)
* Evaporate methanol under a gentle stream of nitrogen at 37°C.
* Reconstitute in 400 µl of ELISA Buffer (1X) and analyze in the assay

=== Preparation of the assay reagents ===
==== ELISA Buffer (1X) Preparation ====
* Dilute the contents of one vial of ELISA Buffer Concentrate (10X) (Item No.400060) with 90 ml of ultrapure water. Be certain to rinse the vial to remove any salts that may have precipitated.
* Wash Buffer (1X) Preparation (Item No. 400062)
* Dilute to a total volume of 2L with ultrapure water and add 1 ml of Polysorbate 20.

==== Preparation of Cortisol ELISA Standard ====
* Equilibrate a pipette tip by repeatedly filling and expelling the tip with the Cortisol ELISA Standard (Item No. 400364) several times.
* Using the equilibrated pipette tip, transfer 100 µl of the standard into a clean test tube, then dilute with 900 µl ultrapure water → 40 ng/ml.
* Obtain eight clean test tubes and label them #1-8.
* Aliquot 900 µl ELISA Buffer (1X) to tube #1 and 600 µl ELISA Buffer (1X) to tubes #2-8.
* Transfer 100 µl of the bulk standard (40 ng/ml) to tube #1 and mix thoroughly.
* Dilute the standard by removing 400 µl from tube #1 and placing it in tube #2, mix thoroughly.
* Remove 400 µl from tube #2 and place it into tube #3, mix thoroughly. Repeat this process for tubes #4-8.
* Diluted standards should not be stored for more than 24 hours

==== Preparation of Cortisol-AChE Tracer ====
* Reconstitute the Cortisol-AChE Tracer (Item No. 10005272) with 6 ml of ELISA Buffer (1X).

==== Preparation of Cortisol ELISA Monoclonal Antibody ====
* Reconstitute the Cortisol ELISA Monoclonal Antibody (Item No. 400362) with 6 ml of ELISA Buffer (1X).

=== Setting up an assay plate ===
* Draw out a 96 well grid (8 x 12) labelling where you intend to put the blanks, standards,

==== Addition of the reagents ====
* Add 100 µl ELISA Buffer (1X) to NSB wells.
* Add 50 µl ELISA Buffer (1X) to blank wells.
* Add 50 µl from standard tube #8 to both of the lowest standard wells. Add 50 µl from standard tube #7 to each of the next standard wells. Continue with this procedure until all the standards are aliquoted. (The same pipette tip should be used to aliquot all the standards. Before pipetting each standard, be sure to equilibrate the pipette tip in that standard.)
* Add 50 µl of sample per well. Each sample should be assayed in duplicate (triplicate recommended).
* Using the multichannel pipet add 50 µl Cortisol-AChE Tracer to each well except the TA and the blank wells.
* Using the multichannel pipet add 50 µl Cortisol ELISA Monoclonal Antibody to each well except the TA, NSB and the blank wells, within 15 min of addition of the tracer.
* Cover each plate with a 96-Well Cover Sheet (Item No. 400012) and incubate overnight at 4°C.
* Reconstitute Ellman’s Reagent (Item No. 400050) immediately before use. Reconstitute 100 dtn vial with 20 ml of ultrapure water. Reconstitute 250 dtn vial with 50 ml of ultrapure water.
* Empty the wells and rinse five times with ~300 µl Wash Buffer (1X).
* Add 200 µl of Ellman’s Reagent to each well.
* Add 5 µl of the reconstituted tracer to the TA wells.
* Cover the plate with the 96-Well Cover Sheet. Optimum development is obtained by using an orbital shaker equipped with a large, flat cover to allow the plate(s) to develop in the dark at room temperature. This assay typically develops (i.e., B0 wells ≥0.6 A.U. (Blk subtracted)) in 90-120 minute

=== Reading the plate ===
* Wipe the bottom of the plate with a clean tissue to remove fingerprints, dirt, etc.
* Remove the cover sheet being careful to keep Ellman’s Reagent from splashing on the cover.
* Read the plate at a wavelength between 405 and 420 nm. The absorbance may be checked periodically until the B0 wells have reached a minimum of 0.3 A.U. (Blk subtracted). The plate should be read when the absorbance of the B0 wells is in the range of 0.3-1.0 A.U. (Blk subtracted). If the absorbance of the wells exceeds 1.5 A.U., wash the plate, add fresh Ellman’s Reagent, and let it develop again.

General Statistics

2024-10-16T00:12:48Z

Davebrid: Fixed tags on this page

[[ Category: General ]]
[[ Category: Data ]]
[[ Category: Statistics ]]
= General Statistical Methods =

There are several important concepts that we will adhere to in our group. These involve design considerations, execution considerations and analysis concerns. The standard for our field is null hypothesis significance testing, which means that we are generally comparing our data to a null hypothesis, generating an '''effect size''' and a '''p-value'''. As a general rule, we report both of these both within our Rmd/qmd scripts, and in our publications.

We generally use an <math display="inline">\alpha</math> of <math display="inline">p<0.05</math> to determine significance, which means that (if true) we are rejecting the null hypothesis. This is known as null hypothesis significance testing.

An alternative approach is to use a Bayesian approach, described in more detail in [https://bridgeslab.github.io/Lab-Documents/Experimental%20Policies/bayesian-analyses.html this document]

<span id="pairwise-testing"></span>
= Pairwise Testing =

If you have two groups (and two groups only) that you want to know if they are different, you will normally want to do a pairwise test. This is '''not''' the case if you have paired data (before and after for example). The most common of these is something called a Student’s ''t''-test, but this test has two key assumptions:

* The data are normally distributed
* The two groups have equal variance

<span id="testing-the-assumptions"></span>
== Testing the Assumptions ==

Best practice is to first test for normality, and if that test passes, to then test for equal variance

<span id="testing-normality"></span>
=== Testing Normality ===

To test normality, we use a Shapiro-Wilk test (details on [https://en.wikipedia.org/wiki/Shapiro%E2%80%93Wilk_test Wikipedia] on each of your two groups). Below is an example where there are two groups:

<div class="cell">

<syntaxhighlight lang="r">#create seed for reproducibility
set.seed(1265)
test.data <- tibble(Treatment=c(rep("Experiment",6), rep("Control",6)),
Result = rnorm(n=12, mean=10, sd=3))
#test.data$Treatment <- as.factor(test.data$Treatment)
kable(test.data, caption="The test data used in the following examples")</syntaxhighlight>
<div class="cell-output-display">

{| class="wikitable"
|+ The test data used in the following examples
|-
! style="text-align: left;"| Treatment
! style="text-align: right;"| Result
|-
| style="text-align: left;"| Experiment
| style="text-align: right;"| 11.26
|-
| style="text-align: left;"| Experiment
| style="text-align: right;"| 8.33
|-
| style="text-align: left;"| Experiment
| style="text-align: right;"| 9.94
|-
| style="text-align: left;"| Experiment
| style="text-align: right;"| 11.83
|-
| style="text-align: left;"| Experiment
| style="text-align: right;"| 6.56
|-
| style="text-align: left;"| Experiment
| style="text-align: right;"| 11.41
|-
| style="text-align: left;"| Control
| style="text-align: right;"| 8.89
|-
| style="text-align: left;"| Control
| style="text-align: right;"| 11.59
|-
| style="text-align: left;"| Control
| style="text-align: right;"| 9.39
|-
| style="text-align: left;"| Control
| style="text-align: right;"| 8.74
|-
| style="text-align: left;"| Control
| style="text-align: right;"| 6.31
|-
| style="text-align: left;"| Control
| style="text-align: right;"| 7.82
|}

</div>

</div>
Each of the two groups, in this case '''Test''' and '''Control''' must have Shapiro-Wilk tests done separately. Some sample code for this is below (requires dplyr to be loaded):

<div class="cell">

<syntaxhighlight lang="r">#filter only for the control data
control.data <- filter(test.data, Treatment=="Control")
#The broom package makes the results of the test appear in a table, with the tidy command
library(broom)

#run the Shapiro-Wilk test on the values
shapiro.test(control.data$Result) %>% tidy %>% kable(caption="Shapiro-Wilk test for normality of control data")</syntaxhighlight>
<div class="cell-output-display">

{| class="wikitable"
|+ Shapiro-Wilk test for normality of control data
|-
! style="text-align: right;"| statistic
! style="text-align: right;"| p.value
! style="text-align: left;"| method
|-
| style="text-align: right;"| 0.968
| style="text-align: right;"| 0.88
| style="text-align: left;"| Shapiro-Wilk normality test
|}

</div>
<syntaxhighlight lang="r">experiment.data <- filter(test.data, Treatment=="Experiment")
shapiro.test(test.data$Result) %>% tidy %>% kable(caption="Shapiro-Wilk test for normality of the test data")</syntaxhighlight>
<div class="cell-output-display">

{| class="wikitable"
|+ Shapiro-Wilk test for normality of the test data
|-
! style="text-align: right;"| statistic
! style="text-align: right;"| p.value
! style="text-align: left;"| method
|-
| style="text-align: right;"| 0.93
| style="text-align: right;"| 0.377
| style="text-align: left;"| Shapiro-Wilk normality test
|}

</div>

</div>
Based on these results, since both p-values are >0.05 we do not reject the presumption of normality and can go on. If one or more of the p-values were less than 0.05 we would then use a Mann-Whitney test (also known as a Wilcoxon rank sum test) will be done, see below for more details.

<span id="testing-for-equal-variance"></span>
=== Testing for Equal Variance ===

We generally use the [https://cran.r-project.org/web/packages/car/index.html car] package which contains code for [https://en.wikipedia.org/wiki/Levene%27s_test Levene’s Test] to see if two groups can be assumed to have equal variance. For more details see @car:

<div class="cell">

<syntaxhighlight lang="r">#load the car package
library(car)</syntaxhighlight>
<div class="cell-output cell-output-stderr">

<pre>Loading required package: carData</pre>

</div>
<div class="cell-output cell-output-stderr">

<pre>
Attaching package: 'car'</pre>

</div>
<div class="cell-output cell-output-stderr">

<pre>The following object is masked from 'package:dplyr':

recode</pre>

</div>
<syntaxhighlight lang="r">#runs the test, grouping by the Treatment variable
leveneTest(Result ~ Treatment, data=test.data) %>% tidy %>% kable(caption="Levene's test on test data")</syntaxhighlight>
<div class="cell-output cell-output-stderr">

<pre>Warning in leveneTest.default(y = y, group = group, ...): group coerced to
factor.</pre>

</div>
<div class="cell-output-display">

{| class="wikitable"
|+ Levene’s test on test data
|-
! style="text-align: right;"| statistic
! style="text-align: right;"| p.value
! style="text-align: right;"| df
! style="text-align: right;"| df.residual
|-
| style="text-align: right;"| 0.368
| style="text-align: right;"| 0.558
| style="text-align: right;"| 1
| style="text-align: right;"| 10
|}

</div>

</div>
<span id="performing-the-appropriate-pairwise-test"></span>
== Performing the Appropriate Pairwise Test ==

The logic to follow is:

* If the Shapiro-Wilk test passes, do Levene’s test. If it fails for either group, move on to a '''Wilcoxon Rank Sum Test'''.
* If Levene’s test ''passes'', do a Student’s ''t'' Test, which assumes equal variance.
* If Levene’s test ''fails'', do a Welch’s ''t'' Test, which does not assume equal variance.

<span id="students-t-test"></span>
=== Student’s ''t'' Test ===

<div class="cell">

<syntaxhighlight lang="r">#The default for t.test in R is Welch's, so you need to set the var.equal variable to be TRUE
t.test(Result~Treatment,data=test.data, var.equal=T) %>% tidy %>% kable(caption="Student's t test for test data")</syntaxhighlight>
<div class="cell-output-display">

{| class="wikitable"
|+ Student’s t test for test data
|-
! style="text-align: right;"| estimate
! style="text-align: right;"| estimate1
! style="text-align: right;"| estimate2
! style="text-align: right;"| statistic
! style="text-align: right;"| p.value
! style="text-align: right;"| parameter
! style="text-align: right;"| conf.low
! style="text-align: right;"| conf.high
! style="text-align: left;"| method
! style="text-align: left;"| alternative
|-
| style="text-align: right;"| -1.1
| style="text-align: right;"| 8.79
| style="text-align: right;"| 9.89
| style="text-align: right;"| -0.992
| style="text-align: right;"| 0.345
| style="text-align: right;"| 10
| style="text-align: right;"| -3.56
| style="text-align: right;"| 1.37
| style="text-align: left;"| Two Sample t-test
| style="text-align: left;"| two.sided
|}

</div>

</div>
<span id="welchs-t-test"></span>
=== Welch’s ''t'' Test ===

<div class="cell">

<syntaxhighlight lang="r">#The default for t.test in R is Welch's, so you need to set the var.equal variable to be FALSE, or leave the default
t.test(Result~Treatment,data=test.data, var.equal=F) %>% tidy %>% kable(caption="Welch's t test for test data")</syntaxhighlight>
<div class="cell-output-display">

{| class="wikitable"
|+ Welch’s t test for test data
|-
! style="text-align: right;"| estimate
! style="text-align: right;"| estimate1
! style="text-align: right;"| estimate2
! style="text-align: right;"| statistic
! style="text-align: right;"| p.value
! style="text-align: right;"| parameter
! style="text-align: right;"| conf.low
! style="text-align: right;"| conf.high
! style="text-align: left;"| method
! style="text-align: left;"| alternative
|-
| style="text-align: right;"| -1.1
| style="text-align: right;"| 8.79
| style="text-align: right;"| 9.89
| style="text-align: right;"| -0.992
| style="text-align: right;"| 0.345
| style="text-align: right;"| 9.72
| style="text-align: right;"| -3.57
| style="text-align: right;"| 1.38
| style="text-align: left;"| Welch Two Sample t-test
| style="text-align: left;"| two.sided
|}

</div>

</div>
<span id="wilcoxon-rank-sum-test"></span>
=== Wilcoxon Rank Sum Test ===

<div class="cell">

<syntaxhighlight lang="r"># no need to specify anything about variance
wilcox.test(Result~Treatment,data=test.data) %>% tidy %>% kable(caption="Mann-Whitney test for test data")</syntaxhighlight>
<div class="cell-output-display">

{| class="wikitable"
|+ Mann-Whitney test for test data
|-
! style="text-align: right;"| statistic
! style="text-align: right;"| p.value
! style="text-align: left;"| method
! style="text-align: left;"| alternative
|-
| style="text-align: right;"| 12
| style="text-align: right;"| 0.394
| style="text-align: left;"| Wilcoxon rank sum exact test
| style="text-align: left;"| two.sided
|}

</div>

</div>
<span id="corrections-for-multiple-observations"></span>
= Corrections for Multiple Observations =

The best illustration I have seen for the need for multiple observation corrections is this cartoon from XKCD (see http://xkcd.com/882/):

<div class="figure">

[[File:http://imgs.xkcd.com/comics/significant.png|Significance by XKCD. Image is from http://imgs.xkcd.com/comics/significant.png]]

</div>
Any conceptually coherent set of observations must therefore be corrected for multiple observations. In most cases, we will use the method of @Benjamini1995 since our p-values are not entirely independent. Some sample code for this is here:

<div class="cell">

<syntaxhighlight lang="r">p.values <- c(0.023, 0.043, 0.056, 0.421, 0.012)
data.frame(unadjusted = p.values, adjusted=p.adjust(p.values, method="BH")) %>%
kable(caption="Effects of adjusting p-values by the method of Benjamini-Hochberg")</syntaxhighlight>
<div class="cell-output-display">

{| class="wikitable"
|+ Effects of adjusting p-values by the method of Benjamini-Hochberg
|-
! style="text-align: right;"| unadjusted
! style="text-align: right;"| adjusted
|-
| style="text-align: right;"| 0.023
| style="text-align: right;"| 0.057
|-
| style="text-align: right;"| 0.043
| style="text-align: right;"| 0.070
|-
| style="text-align: right;"| 0.056
| style="text-align: right;"| 0.070
|-
| style="text-align: right;"| 0.421
| style="text-align: right;"| 0.421
|-
| style="text-align: right;"| 0.012
| style="text-align: right;"| 0.057
|}

</div>

</div>
<span id="session-information"></span>
= Session Information =

<div class="cell">

<syntaxhighlight lang="r">sessionInfo()</syntaxhighlight>
<div class="cell-output cell-output-stdout">

<pre>R version 4.4.1 (2024-06-14)
Platform: x86_64-apple-darwin20
Running under: macOS Sonoma 14.7

Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/lib/libRlapack.dylib; LAPACK version 3.12.0

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

time zone: America/Detroit
tzcode source: internal

attached base packages:
[1] stats graphics grDevices utils datasets methods base

other attached packages:
[1] car_3.1-2 carData_3.0-5 broom_1.0.6 dplyr_1.1.4 tidyr_1.3.1
[6] knitr_1.48

loaded via a namespace (and not attached):
[1] vctrs_0.6.5 cli_3.6.3 rlang_1.1.4 xfun_0.47
[5] purrr_1.0.2 generics_0.1.3 jsonlite_1.8.8 glue_1.7.0
[9] backports_1.5.0 htmltools_0.5.8.1 fansi_1.0.6 rmarkdown_2.28
[13] abind_1.4-8 evaluate_0.24.0 tibble_3.2.1 fastmap_1.2.0
[17] yaml_2.3.10 lifecycle_1.0.4 compiler_4.4.1 htmlwidgets_1.6.4
[21] pkgconfig_2.0.3 rstudioapi_0.16.0 digest_0.6.37 R6_2.5.1
[25] tidyselect_1.2.1 utf8_1.2.4 pillar_1.9.0 magrittr_2.0.3
[29] withr_3.0.1 tools_4.4.1 </pre>

</div>

</div>
<span id="references"></span>
= References =

<div id="refs">

</div>

General Statistics

2024-10-16T00:10:30Z

Davebrid: Updated general statistics wiki page

<div class="cell">

<syntaxhighlight lang="r">library(knitr)
#figures makde will go to directory called figures, will make them as both png and pdf files
opts_chunk$set(fig.path='figures/',dev=c('png','pdf'))
options(scipen = 2, digits = 3)
# set echo and message to TRUE if you want to display code blocks and code output respectively

knitr::knit_hooks$set(inline = function(x) {
knitr:::format_sci(x, 'md')
})

superpose.eb <- function (x, y, ebl, ebu = ebl, length = 0.08, ...)
arrows(x, y + ebu, x, y - ebl, angle = 90, code = 3,
length = length, ...)

se <- function(x) sd(x, na.rm=T)/sqrt(length(x))

#load these packages, nearly always needed
library(tidyr)
library(dplyr)</syntaxhighlight>
<div class="cell-output cell-output-stderr">

<pre>
Attaching package: 'dplyr'</pre>

</div>
<div class="cell-output cell-output-stderr">

<pre>The following objects are masked from 'package:stats':

filter, lag</pre>

</div>
<div class="cell-output cell-output-stderr">

<pre>The following objects are masked from 'package:base':

intersect, setdiff, setequal, union</pre>

</div>
<syntaxhighlight lang="r"># sets maize and blue color scheme
color.scheme <- c('#00274c', '#ffcb05')</syntaxhighlight>

</div>
<span id="general-statistical-methods"></span>
= General Statistical Methods =

There are several important concepts that we will adhere to in our group. These involve design considerations, execution considerations and analysis concerns. The standard for our field is null hypothesis significance testing, which means that we are generally comparing our data to a null hypothesis, generating an '''effect size''' and a '''p-value'''. As a general rule, we report both of these both within our Rmd/qmd scripts, and in our publications.

We generally use an <math display="inline">\alpha</math> of <math display="inline">p<0.05</math> to determine significance, which means that (if true) we are rejecting the null hypothesis. This is known as null hypothesis significance testing.

An alternative approach is to use a Bayesian approach, described in more detail in [https://bridgeslab.github.io/Lab-Documents/Experimental%20Policies/bayesian-analyses.html this document]

<span id="pairwise-testing"></span>
= Pairwise Testing =

If you have two groups (and two groups only) that you want to know if they are different, you will normally want to do a pairwise test. This is '''not''' the case if you have paired data (before and after for example). The most common of these is something called a Student’s ''t''-test, but this test has two key assumptions:

* The data are normally distributed
* The two groups have equal variance

<span id="testing-the-assumptions"></span>
== Testing the Assumptions ==

Best practice is to first test for normality, and if that test passes, to then test for equal variance

<span id="testing-normality"></span>
=== Testing Normality ===

To test normality, we use a Shapiro-Wilk test (details on [https://en.wikipedia.org/wiki/Shapiro%E2%80%93Wilk_test Wikipedia] on each of your two groups). Below is an example where there are two groups:

<div class="cell">

<syntaxhighlight lang="r">#create seed for reproducibility
set.seed(1265)
test.data <- tibble(Treatment=c(rep("Experiment",6), rep("Control",6)),
Result = rnorm(n=12, mean=10, sd=3))
#test.data$Treatment <- as.factor(test.data$Treatment)
kable(test.data, caption="The test data used in the following examples")</syntaxhighlight>
<div class="cell-output-display">

{| class="wikitable"
|+ The test data used in the following examples
|-
! style="text-align: left;"| Treatment
! style="text-align: right;"| Result
|-
| style="text-align: left;"| Experiment
| style="text-align: right;"| 11.26
|-
| style="text-align: left;"| Experiment
| style="text-align: right;"| 8.33
|-
| style="text-align: left;"| Experiment
| style="text-align: right;"| 9.94
|-
| style="text-align: left;"| Experiment
| style="text-align: right;"| 11.83
|-
| style="text-align: left;"| Experiment
| style="text-align: right;"| 6.56
|-
| style="text-align: left;"| Experiment
| style="text-align: right;"| 11.41
|-
| style="text-align: left;"| Control
| style="text-align: right;"| 8.89
|-
| style="text-align: left;"| Control
| style="text-align: right;"| 11.59
|-
| style="text-align: left;"| Control
| style="text-align: right;"| 9.39
|-
| style="text-align: left;"| Control
| style="text-align: right;"| 8.74
|-
| style="text-align: left;"| Control
| style="text-align: right;"| 6.31
|-
| style="text-align: left;"| Control
| style="text-align: right;"| 7.82
|}

</div>

</div>
Each of the two groups, in this case '''Test''' and '''Control''' must have Shapiro-Wilk tests done separately. Some sample code for this is below (requires dplyr to be loaded):

<div class="cell">

<syntaxhighlight lang="r">#filter only for the control data
control.data <- filter(test.data, Treatment=="Control")
#The broom package makes the results of the test appear in a table, with the tidy command
library(broom)

#run the Shapiro-Wilk test on the values
shapiro.test(control.data$Result) %>% tidy %>% kable(caption="Shapiro-Wilk test for normality of control data")</syntaxhighlight>
<div class="cell-output-display">

{| class="wikitable"
|+ Shapiro-Wilk test for normality of control data
|-
! style="text-align: right;"| statistic
! style="text-align: right;"| p.value
! style="text-align: left;"| method
|-
| style="text-align: right;"| 0.968
| style="text-align: right;"| 0.88
| style="text-align: left;"| Shapiro-Wilk normality test
|}

</div>
<syntaxhighlight lang="r">experiment.data <- filter(test.data, Treatment=="Experiment")
shapiro.test(test.data$Result) %>% tidy %>% kable(caption="Shapiro-Wilk test for normality of the test data")</syntaxhighlight>
<div class="cell-output-display">

{| class="wikitable"
|+ Shapiro-Wilk test for normality of the test data
|-
! style="text-align: right;"| statistic
! style="text-align: right;"| p.value
! style="text-align: left;"| method
|-
| style="text-align: right;"| 0.93
| style="text-align: right;"| 0.377
| style="text-align: left;"| Shapiro-Wilk normality test
|}

</div>

</div>
Based on these results, since both p-values are >0.05 we do not reject the presumption of normality and can go on. If one or more of the p-values were less than 0.05 we would then use a Mann-Whitney test (also known as a Wilcoxon rank sum test) will be done, see below for more details.

<span id="testing-for-equal-variance"></span>
=== Testing for Equal Variance ===

We generally use the [https://cran.r-project.org/web/packages/car/index.html car] package which contains code for [https://en.wikipedia.org/wiki/Levene%27s_test Levene’s Test] to see if two groups can be assumed to have equal variance. For more details see @car:

<div class="cell">

<syntaxhighlight lang="r">#load the car package
library(car)</syntaxhighlight>
<div class="cell-output cell-output-stderr">

<pre>Loading required package: carData</pre>

</div>
<div class="cell-output cell-output-stderr">

<pre>
Attaching package: 'car'</pre>

</div>
<div class="cell-output cell-output-stderr">

<pre>The following object is masked from 'package:dplyr':

recode</pre>

</div>
<syntaxhighlight lang="r">#runs the test, grouping by the Treatment variable
leveneTest(Result ~ Treatment, data=test.data) %>% tidy %>% kable(caption="Levene's test on test data")</syntaxhighlight>
<div class="cell-output cell-output-stderr">

<pre>Warning in leveneTest.default(y = y, group = group, ...): group coerced to
factor.</pre>

</div>
<div class="cell-output-display">

{| class="wikitable"
|+ Levene’s test on test data
|-
! style="text-align: right;"| statistic
! style="text-align: right;"| p.value
! style="text-align: right;"| df
! style="text-align: right;"| df.residual
|-
| style="text-align: right;"| 0.368
| style="text-align: right;"| 0.558
| style="text-align: right;"| 1
| style="text-align: right;"| 10
|}

</div>

</div>
<span id="performing-the-appropriate-pairwise-test"></span>
== Performing the Appropriate Pairwise Test ==

The logic to follow is:

* If the Shapiro-Wilk test passes, do Levene’s test. If it fails for either group, move on to a '''Wilcoxon Rank Sum Test'''.
* If Levene’s test ''passes'', do a Student’s ''t'' Test, which assumes equal variance.
* If Levene’s test ''fails'', do a Welch’s ''t'' Test, which does not assume equal variance.

<span id="students-t-test"></span>
=== Student’s ''t'' Test ===

<div class="cell">

<syntaxhighlight lang="r">#The default for t.test in R is Welch's, so you need to set the var.equal variable to be TRUE
t.test(Result~Treatment,data=test.data, var.equal=T) %>% tidy %>% kable(caption="Student's t test for test data")</syntaxhighlight>
<div class="cell-output-display">

{| class="wikitable"
|+ Student’s t test for test data
|-
! style="text-align: right;"| estimate
! style="text-align: right;"| estimate1
! style="text-align: right;"| estimate2
! style="text-align: right;"| statistic
! style="text-align: right;"| p.value
! style="text-align: right;"| parameter
! style="text-align: right;"| conf.low
! style="text-align: right;"| conf.high
! style="text-align: left;"| method
! style="text-align: left;"| alternative
|-
| style="text-align: right;"| -1.1
| style="text-align: right;"| 8.79
| style="text-align: right;"| 9.89
| style="text-align: right;"| -0.992
| style="text-align: right;"| 0.345
| style="text-align: right;"| 10
| style="text-align: right;"| -3.56
| style="text-align: right;"| 1.37
| style="text-align: left;"| Two Sample t-test
| style="text-align: left;"| two.sided
|}

</div>

</div>
<span id="welchs-t-test"></span>
=== Welch’s ''t'' Test ===

<div class="cell">

<syntaxhighlight lang="r">#The default for t.test in R is Welch's, so you need to set the var.equal variable to be FALSE, or leave the default
t.test(Result~Treatment,data=test.data, var.equal=F) %>% tidy %>% kable(caption="Welch's t test for test data")</syntaxhighlight>
<div class="cell-output-display">

{| class="wikitable"
|+ Welch’s t test for test data
|-
! style="text-align: right;"| estimate
! style="text-align: right;"| estimate1
! style="text-align: right;"| estimate2
! style="text-align: right;"| statistic
! style="text-align: right;"| p.value
! style="text-align: right;"| parameter
! style="text-align: right;"| conf.low
! style="text-align: right;"| conf.high
! style="text-align: left;"| method
! style="text-align: left;"| alternative
|-
| style="text-align: right;"| -1.1
| style="text-align: right;"| 8.79
| style="text-align: right;"| 9.89
| style="text-align: right;"| -0.992
| style="text-align: right;"| 0.345
| style="text-align: right;"| 9.72
| style="text-align: right;"| -3.57
| style="text-align: right;"| 1.38
| style="text-align: left;"| Welch Two Sample t-test
| style="text-align: left;"| two.sided
|}

</div>

</div>
<span id="wilcoxon-rank-sum-test"></span>
=== Wilcoxon Rank Sum Test ===

<div class="cell">

<syntaxhighlight lang="r"># no need to specify anything about variance
wilcox.test(Result~Treatment,data=test.data) %>% tidy %>% kable(caption="Mann-Whitney test for test data")</syntaxhighlight>
<div class="cell-output-display">

{| class="wikitable"
|+ Mann-Whitney test for test data
|-
! style="text-align: right;"| statistic
! style="text-align: right;"| p.value
! style="text-align: left;"| method
! style="text-align: left;"| alternative
|-
| style="text-align: right;"| 12
| style="text-align: right;"| 0.394
| style="text-align: left;"| Wilcoxon rank sum exact test
| style="text-align: left;"| two.sided
|}

</div>

</div>
<span id="corrections-for-multiple-observations"></span>
= Corrections for Multiple Observations =

The best illustration I have seen for the need for multiple observation corrections is this cartoon from XKCD (see http://xkcd.com/882/):

<div class="figure">

[[File:http://imgs.xkcd.com/comics/significant.png|Significance by XKCD. Image is from http://imgs.xkcd.com/comics/significant.png]]

</div>
Any conceptually coherent set of observations must therefore be corrected for multiple observations. In most cases, we will use the method of @Benjamini1995 since our p-values are not entirely independent. Some sample code for this is here:

<div class="cell">

<syntaxhighlight lang="r">p.values <- c(0.023, 0.043, 0.056, 0.421, 0.012)
data.frame(unadjusted = p.values, adjusted=p.adjust(p.values, method="BH")) %>%
kable(caption="Effects of adjusting p-values by the method of Benjamini-Hochberg")</syntaxhighlight>
<div class="cell-output-display">

{| class="wikitable"
|+ Effects of adjusting p-values by the method of Benjamini-Hochberg
|-
! style="text-align: right;"| unadjusted
! style="text-align: right;"| adjusted
|-
| style="text-align: right;"| 0.023
| style="text-align: right;"| 0.057
|-
| style="text-align: right;"| 0.043
| style="text-align: right;"| 0.070
|-
| style="text-align: right;"| 0.056
| style="text-align: right;"| 0.070
|-
| style="text-align: right;"| 0.421
| style="text-align: right;"| 0.421
|-
| style="text-align: right;"| 0.012
| style="text-align: right;"| 0.057
|}

</div>

</div>
<span id="session-information"></span>
= Session Information =

<div class="cell">

<syntaxhighlight lang="r">sessionInfo()</syntaxhighlight>
<div class="cell-output cell-output-stdout">

<pre>R version 4.4.1 (2024-06-14)
Platform: x86_64-apple-darwin20
Running under: macOS Sonoma 14.7

Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/lib/libRlapack.dylib; LAPACK version 3.12.0

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

time zone: America/Detroit
tzcode source: internal

attached base packages:
[1] stats graphics grDevices utils datasets methods base

other attached packages:
[1] car_3.1-2 carData_3.0-5 broom_1.0.6 dplyr_1.1.4 tidyr_1.3.1
[6] knitr_1.48

loaded via a namespace (and not attached):
[1] vctrs_0.6.5 cli_3.6.3 rlang_1.1.4 xfun_0.47
[5] purrr_1.0.2 generics_0.1.3 jsonlite_1.8.8 glue_1.7.0
[9] backports_1.5.0 htmltools_0.5.8.1 fansi_1.0.6 rmarkdown_2.28
[13] abind_1.4-8 evaluate_0.24.0 tibble_3.2.1 fastmap_1.2.0
[17] yaml_2.3.10 lifecycle_1.0.4 compiler_4.4.1 htmlwidgets_1.6.4
[21] pkgconfig_2.0.3 rstudioapi_0.16.0 digest_0.6.37 R6_2.5.1
[25] tidyselect_1.2.1 utf8_1.2.4 pillar_1.9.0 magrittr_2.0.3
[29] withr_3.0.1 tools_4.4.1 </pre>

</div>

</div>
<span id="references"></span>
= References =

<div id="refs">

</div>

Safety and Animal Training

2024-09-09T19:24:35Z

Davebrid: /* Human Subject Data */

These are the classes that lab staff need to take at Michigan:

==General Lab Safety==
These are offered through MyLink at https://maislinc.umich.edu/. All lab personnel need to take these

* EHS_BLS025w ONLINE REQUIRED General Laboratory Safety Training (online)
* EHS_BLS023w Centrifuge & Rotor Safety Training (online)
* BLS013w ONLINE REQUIRED Autoclave Standard Operating Procedures (online)

If you will be working with blood you will need to take

* BLS101w ONLINE REQUIRED Bloodborne Pathogens (online)

If you will be working with radioactive materials, you will have to take this course as well:

* RSS006 REQUIRED Radiation Safety Orientation (classroom)
* RSS103w REQUIRED ONLINE REQUIRED Radionuclide Users Annual Refresher Training (to be completed every CALENDAR year)
If you will be working with any viruses you will have to take this course as well:

* BLS008 REQUIRED Working Safely with Viral Vectors (classroom)

If you plan to breed animals, you can also take this course:

*ULAM-10125 Breeding Colony Management for Rats and Mice (online)

If you will be working at a core facility such as a clinical research unit

* BLS001 - TAB Hazard Communication for Employees Working in Research Support Units, Labs and Shops

==Animals==
If you will be working with animals you will have to take these classes. They are all offered through ULAM MLearning (https://animalcare.umich.edu/training/). This requires a level 2 password.

* ULAM-10000 Orientation (online)
* ULAM-10100 Intro Mouse/Rat (online)
* ULAM-10131 Animal Room Procedures pt.1 (online)
* ULAM-10132 Animal Room Procedures pt.2 (on zoom)
* ULAM-10105a Lab Mouse Workshop (on zoom)
* ULAM-10105b Lab Mouse Workshop (classroom)
* ULAM-10050 Hazards pt.1 (online)
* ULAM-10055 Hazards pt.2 (classroom)

==Human Subject Data==
If you will be working with Human data you will have to take these classes. They are all offered through MLearning (https://michmed.csod.com/samldefault.aspx). This requires a levels 2 password.

* PRIV-10001 HIPAA Training for All Workforce Members (online)
* PEERRS (online)
* DCE101 U-M Data Protection and Responsible Use (online, for HSIP)
* MiChart Research Access eLearning Research Certification (MC-RE20001V)(Online)
* MiChart Inpatient Allied Health HOD Certification (MC-HD70003A)(Online)

==Lab Standard Operating Procedures==
For lab specific safety training please review the SOP's and sign them if you will be using any of them. All lab SOP's are available [[:Category: SOP|here]]

[[ Category: Lab Safety ]]
[[ Category: Training ]]
[[Category: SOP]]

Safety and Animal Training

2024-09-09T19:19:07Z

Davebrid: /* Animals */ Updated course names for animal training

These are the classes that lab staff need to take at Michigan:

==General Lab Safety==
These are offered through MyLink at https://maislinc.umich.edu/. All lab personnel need to take these

* EHS_BLS025w ONLINE REQUIRED General Laboratory Safety Training (online)
* EHS_BLS023w Centrifuge & Rotor Safety Training (online)
* BLS013w ONLINE REQUIRED Autoclave Standard Operating Procedures (online)

If you will be working with blood you will need to take

* BLS101w ONLINE REQUIRED Bloodborne Pathogens (online)

If you will be working with radioactive materials, you will have to take this course as well:

* RSS006 REQUIRED Radiation Safety Orientation (classroom)
* RSS103w REQUIRED ONLINE REQUIRED Radionuclide Users Annual Refresher Training (to be completed every CALENDAR year)
If you will be working with any viruses you will have to take this course as well:

* BLS008 REQUIRED Working Safely with Viral Vectors (classroom)

If you plan to breed animals, you can also take this course:

*ULAM-10125 Breeding Colony Management for Rats and Mice (online)

If you will be working at a core facility such as a clinical research unit

* BLS001 - TAB Hazard Communication for Employees Working in Research Support Units, Labs and Shops

==Animals==
If you will be working with animals you will have to take these classes. They are all offered through ULAM MLearning (https://animalcare.umich.edu/training/). This requires a level 2 password.

* ULAM-10000 Orientation (online)
* ULAM-10100 Intro Mouse/Rat (online)
* ULAM-10131 Animal Room Procedures pt.1 (online)
* ULAM-10132 Animal Room Procedures pt.2 (on zoom)
* ULAM-10105a Lab Mouse Workshop (on zoom)
* ULAM-10105b Lab Mouse Workshop (classroom)
* ULAM-10050 Hazards pt.1 (online)
* ULAM-10055 Hazards pt.2 (classroom)

==Human Subject Data==
If you will be working with Human data you will have to take these classes. They are all offered through MLearning (https://trainingportal.med.umich.edu/). This requires a levels 2 password.

* PRIV-10001 HIPAA Training for All Workforce Members (online)
* PEERRS (online)
* DCE101 U-M Data Protection and Responsible Use (online, for HSIP)
* MiChart Research Access eLearning Research Certification (MC-RE20001V)(Online)
* MiChart Inpatient Allied Health HOD Certification (MC-HD70003A)(Online)

==Lab Standard Operating Procedures==
For lab specific safety training please review the SOP's and sign them if you will be using any of them. All lab SOP's are available [[:Category: SOP|here]]

[[ Category: Lab Safety ]]
[[ Category: Training ]]
[[Category: SOP]]

Safety and Animal Training

2024-08-27T23:25:42Z

Davebrid: /* Animals */ Updated link

These are the classes that lab staff need to take at Michigan:

==General Lab Safety==
These are offered through MyLink at https://maislinc.umich.edu/. All lab personnel need to take these

* EHS_BLS025w ONLINE REQUIRED General Laboratory Safety Training (online)
* EHS_BLS023w Centrifuge & Rotor Safety Training (online)
* BLS013w ONLINE REQUIRED Autoclave Standard Operating Procedures (online)

If you will be working with blood you will need to take

* BLS101w ONLINE REQUIRED Bloodborne Pathogens (online)

If you will be working with radioactive materials, you will have to take this course as well:

* RSS006 REQUIRED Radiation Safety Orientation (classroom)
* RSS103w REQUIRED ONLINE REQUIRED Radionuclide Users Annual Refresher Training (to be completed every CALENDAR year)
If you will be working with any viruses you will have to take this course as well:

* BLS008 REQUIRED Working Safely with Viral Vectors (classroom)

If you plan to breed animals, you can also take this course:

*ULAM-10125 Breeding Colony Management for Rats and Mice (online)

If you will be working at a core facility such as a clinical research unit

* BLS001 - TAB Hazard Communication for Employees Working in Research Support Units, Labs and Shops

==Animals==
If you will be working with animals you will have to take these classes. They are all offered through ULAM MLearning (https://animalcare.umich.edu/training/). This requires a levels 2 password.

* ULAM-10000 Orientation (online)
* ULAM-10050 Hazards pt.1 (online)
* ULAM-10055 Hazards pt.2 (classroom)
* ULAM-10100 Intro Mouse/Rat (online)
* ULAM-10131 Animal Room Procedures pt.1 (online)
* ULAM-10132 Animal Room Procedures pt.2 (classroom)
* ULAM-10105 Lab Mouse Workshop (classroom)

==Human Subject Data==
If you will be working with Human data you will have to take these classes. They are all offered through MLearning (https://trainingportal.med.umich.edu/). This requires a levels 2 password.

* PRIV-10001 HIPAA Training for All Workforce Members (online)
* PEERRS (online)
* DCE101 U-M Data Protection and Responsible Use (online, for HSIP)
* MiChart Research Access eLearning Research Certification (MC-RE20001V)(Online)
* MiChart Inpatient Allied Health HOD Certification (MC-HD70003A)(Online)

==Lab Standard Operating Procedures==
For lab specific safety training please review the SOP's and sign them if you will be using any of them. All lab SOP's are available [[:Category: SOP|here]]

[[ Category: Lab Safety ]]
[[ Category: Training ]]
[[Category: SOP]]

Power Analysis

2024-08-21T16:38:17Z

Davebrid: Wrote page for power analysis, from Lab Documents repository

Commonly we want to know how to design our experiments (''a priori''), or how estimate how big of an effect we could have seen (''a posteriori''). We use two different methods for doing these kinds of analyses. One is using the [https://github.com/heliosdrm/pwr pwr package] in R. Alternatively sometimes we use [https://www.psychologie.hhu.de/arbeitsgruppen/allgemeine-psychologie-und-arbeitspsychologie/gpower.html G*Power], a standalone software with somewhat more functionality. Here we will focus on pwr, which is sufficient for most of our needs.

= Some Definitions =

; Effect Size
: The effect you expect to see, generally given as Cohen's ''d'' which is calculated as expected difference between groups divided by the standard deviation <math>d=\frac{mean(group1)-mean(group2)}{sd}</math>. If you are asking for the correlation between two parameters it is related to interested in the correlation coefficient rather than the difference between groups (r), you can use this formula <math>d= \frac{2r}{\sqrt{1 - r^2}}</math>
; Power
: The likelihood of being able to observe the effect size (if such an effect exists). Generally for prospective design purposes we use a power of 0.8. This is the same as one minus the false negative rate (FNR; the likelihood that an effect exists, but we cannot detect it, sometimes refered to as <math>\beta</math>), so <math>Power = 1-FNR</math>. Therefore conventionally <math>\beta=0.2</math>. Therefore retrospectively the power says that for some particular effect size, n, and false positive rate, how likely we were to observe that effect.
; False Positive Rate
: The likelihood that we think there is a difference, when there is none, conventionally set as <math>\alpha=0.05</math>.
; Sample Size
: The number used, be it number of participants, number of experimntal animals. '''Not''' the number of technical replicates

These four parameters are related to each other such that if you know three of them, you can calculate the fourth. Some examples:

{|
! Missing Value
! Use Case
|-
| n
| Calculate how many needed in a group
|-
| Power
| Calculate likelihood of seeing an effect
|-
| Effect size
| Calculate detectable difference
|}

= Power Analysis =

::: {.cell}

<pre class="r cell-code">library(pwr)
#desired effect size in standard deviations
effect.size <- 5 # expected difference in absolute terms
assay.sd <- 3 # the standard deviation of the assay, in the same units as the effect size
effect.size.sd <- effect.size/assay.sd
#desired false positive rate
fpr <- 0.05
#desired power (inverse of false negative rate)
power <- 0.8
#calculate required n
required.animals <- pwr.t.test(d=effect.size.sd,
power=power,
sig.level=fpr,
alternative="greater",
type="two.sample")$n</pre>
:::

The assumptions set in this analysis are:

* The desired effect size is 5. This is what we want to power our analysis to be able to detect.
* The standard deviation of the measurement is 3, in the same units as the effect size.
* Therefore Cohen's ''d'' is 1.6666667 or the number of standard deviations we want to be able to detect.
* The acceptable false positive rate is 0.05. This is the percent chance that we observe something that is not actually true.
* The acceptable false negative rate is 0.2. This is the percent chance that we miss something that is actually true.
* The power of our analysis is set at 0.8.

== Calculate Number of Animals ==

At a standard power of 0.8 with a false positive rate of 0.05 and a desired effect size of a 5 difference in percent fat mass we would need '''5.283492''' animals in each group.

== Calculate Detectable Effect Size ==

::: {.cell}

<pre class="r cell-code">required.animals.effect <- round(required.animals)
effective.d <- pwr.t.test(power=power,
n=required.animals.effect,
sig.level=fpr,
alternative="greater",
type="two.sample")$d</pre>
:::

Based on the design above we should expect to detect an effect size of 1.7245893 standard deviations with 0.8 power, 5 animals and a FPR of 0.05.

== Calculate Effective Power ==

::: {.cell}

<pre class="r cell-code">required.animals.power <- round(required.animals)
effective.power <- pwr.t.test(d=effect.size.sd,
n=required.animals.power,
sig.level=fpr,
alternative="greater",
type="two.sample")$power</pre>
:::

Based on the design above we have a 77.5993902% chance of seeing a difference of 1.6666667 with 5 animals and a FPR of 0.05.

The plot below shows how likely we are to detect a difference (the power) as we vary the number of animals (x-axis) and the desired effect size.

::: {.cell}

<pre class="r cell-code">animals <- seq(1:20) #animal range to test
effect.sizes <- seq(1,9,by=1) # effect size range to test
power.table <- expand.grid(animals=animals,effect.sizes=effect.sizes)
power.table$effect.sizes.sd <- power.table$effect.sizes/assay.sd

for (effect.size.sd in power.table$effect.sizes.sd){
for (n.test in power.table$animals){
power.table[power.table$animals==n.test&power.table$effect.sizes.sd==effect.size.sd,'power'] <-
pwr.t.test(d=effect.size.sd,
n=n.test,
sig.level=fpr,
alternative="greater",
type="two.sample")$power
}
}

library(ggplot2)
library(RColorBrewer)

power.table$effect.sizes.sd <- as.factor(format(round(power.table$effect.sizes.sd,2),nsmall=2))
p <- ggplot(power.table, aes(y=power,x=animals))
p + geom_line(aes(col=effect.sizes.sd)) +
labs(y="Power",
x="Animals",
title="Effective power relative to animal numbers",
subtitle=paste("Based on false positive rate of ", fpr)) +
geom_hline(yintercept=0.8, lty=2) +
scale_colour_manual("Effect Sizes \n(Number of SD)", values=brewer.pal(10,'Blues'))</pre>
::: {.cell-output-display} [[File:power-analysis_files/figure-html/effect-size-plot-1.png|672px]] ::: :::

= Session Information =

::: {.cell}

<pre class="r cell-code">sessionInfo()</pre>
::: {.cell-output .cell-output-stdout}

<pre>R version 4.4.1 (2024-06-14)
Platform: x86_64-apple-darwin20
Running under: macOS Monterey 12.7.6

Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/lib/libRlapack.dylib; LAPACK version 3.12.0

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

time zone: America/Detroit
tzcode source: internal

attached base packages:
[1] stats graphics grDevices utils datasets methods base

other attached packages:
[1] RColorBrewer_1.1-3 ggplot2_3.5.1 pwr_1.3-0

loaded via a namespace (and not attached):
[1] vctrs_0.6.5 cli_3.6.3 knitr_1.48 rlang_1.1.4
[5] xfun_0.46 generics_0.1.3 jsonlite_1.8.8 labeling_0.4.3
[9] glue_1.7.0 colorspace_2.1-1 htmltools_0.5.8.1 scales_1.3.0
[13] fansi_1.0.6 rmarkdown_2.27 grid_4.4.1 evaluate_0.24.0
[17] munsell_0.5.1 tibble_3.2.1 fastmap_1.2.0 yaml_2.3.10
[21] lifecycle_1.0.4 compiler_4.4.1 dplyr_1.1.4 pkgconfig_2.0.3
[25] farver_2.1.2 digest_0.6.36 R6_2.5.1 tidyselect_1.2.1
[29] utf8_1.2.4 pillar_1.9.0 magrittr_2.0.3 withr_3.0.0
[33] tools_4.4.1 gtable_0.3.5 </pre>
::: :::

General Statistics

2024-08-11T19:09:06Z

Davebrid: Updated to match github version

[[ Category: General ]]
[[ Category: Data ]]
[[ Category: Statistics ]]

= General Statistical Methods =

There are several important concepts that we will adhere to in our group. These involve design considerations, execution considerations and analysis concerns. The standard for our field is null hypothesis significance testing, which means that we are generally comparing our data to a null hypothesis, generating an '''effect size''' and a '''p-value'''. As a general rule, we report both of these both within our Rmd scripts, and in our publications.

We generally use an <math>\alpha</math> of <math>p<0.05</math> to determine significance, which means that (if true) we are rejecting the null hypothesis.

== Experimental Design ==

Where possible, prior to performing an experiment or study perform a power analysis. This is mainly to determine the appropriate sample sizes. To do this, you need to know a few of things:

* Either the sample size or the difference. The difference is provided in standard deviations. This means that you need to know the standard deviation of your measurement in question. It is a good idea to keep a log of these for your data, so that you can approximate what this is. If you hope to detect a correlation you will need to know the expected correlation coefficient.
* The desired false positive rate (normally 0.05). This is the rate at which you find a difference where there is none. This is also known as the type I error rate.
* The desired power (normally 0.8). This indicates that 80% of the time you will detect the effect if there is one. This is also known as 1 minus the false negative rate or 1 minus the Type II error rate.

We use the R package '''pwr''' to do a power analysis (Champely, 2020). Here is an example:

=== Pairwise Comparasons ===

<pre class="r">require(pwr)
false.negative.rate <- 0.05
statistical.power <- 0.8
sd <- 3.5 #this is calculated from known measurements
difference <- 3 #you hope to detect a difference
pwr.t.test(d = difference, sig.level = false.negative.rate, power=statistical.power)</pre>
<pre>##
## Two-sample t test power calculation
##
## n = 3.07
## d = 3
## sig.level = 0.05
## power = 0.8
## alternative = two.sided
##
## NOTE: n is number in *each* group</pre>
This tells us that in order to see a difference of at least 3, with at standard devation of 3.5 we need at least '''3''' observations in each group.

=== Correlations ===

The following is an example for detecting a correlation.

<pre class="r">require(pwr)
false.negative.rate <- 0.05
statistical.power <- 0.8
correlation.coefficient <- 0.6 #note that this is the r, to get the R2 value you will have to square this result.
pwr.r.test(r = correlation.coefficient, sig.level = false.negative.rate, power=statistical.power)</pre>
<pre>##
## approximate correlation power calculation (arctangh transformation)
##
## n = 18.6
## r = 0.6
## sig.level = 0.05
## power = 0.8
## alternative = two.sided</pre>
This tells us that in order to detect a correlation coefficient of at least 0.6 (or an R^2 of 0.36) you need more than '''18''' observations.

= Pairwise Testing =

If you have two groups (and two groups only) that you want to know if they are different, you will normally want to do a pairwise test. This is '''not''' the case if you have paired data (before and after for example). The most common of these is something called a Student's ''t''-test, but this test has two key assumptions:

* The data are normally distributed
* The two groups have equal variance

== Testing the Assumptions ==

Best practice is to first test for normality, and if that test passes, to then test for equal variance

=== Testing Normality ===

To test normality, we use a Shapiro-Wilk test (details on [https://en.wikipedia.org/wiki/Shapiro%E2%80%93Wilk_test Wikipedia] on each of your two groups). Below is an example where there are two groups:

<pre class="r">#create seed for reproducibility
set.seed(1265)
test.data <- tibble(Treatment=c(rep("Experiment",6), rep("Control",6)),
Result = rnorm(n=12, mean=10, sd=3))
#test.data$Treatment <- as.factor(test.data$Treatment)
kable(test.data, caption="The test data used in the following examples")</pre>
{|
|+ The test data used in the following examples
! Treatment
!align="right"| Result
|-
| Experiment
|align="right"| 11.26
|-
| Experiment
|align="right"| 8.33
|-
| Experiment
|align="right"| 9.94
|-
| Experiment
|align="right"| 11.83
|-
| Experiment
|align="right"| 6.56
|-
| Experiment
|align="right"| 11.41
|-
| Control
|align="right"| 8.89
|-
| Control
|align="right"| 11.59
|-
| Control
|align="right"| 9.39
|-
| Control
|align="right"| 8.74
|-
| Control
|align="right"| 6.31
|-
| Control
|align="right"| 7.82
|}

Each of the two groups, in this case '''Test''' and '''Control''' must have Shapiro-Wilk tests done separately. Some sample code for this is below (requires dplyr to be loaded):

<pre class="r">#filter only for the control data
control.data <- filter(test.data, Treatment=="Control")
#The broom package makes the results of the test appear in a table, with the tidy command
library(broom)

#run the Shapiro-Wilk test on the values
shapiro.test(control.data$Result) %>% tidy %>% kable</pre>
{|
!align="right"| statistic
!align="right"| p.value
! method
|-
|align="right"| 0.968
|align="right"| 0.88
| Shapiro-Wilk normality test
|}

<pre class="r">experiment.data <- filter(test.data, Treatment=="Experiment")
shapiro.test(test.data$Result) %>% tidy %>% kable</pre>
{|
!align="right"| statistic
!align="right"| p.value
! method
|-
|align="right"| 0.93
|align="right"| 0.377
| Shapiro-Wilk normality test
|}

Based on these results, since both p-values are >0.05 we do not reject the presumption of normality and can go on. If one or more of the p-values were less than 0.05 we would then use a Mann-Whitney test (also known as a Wilcoxon rank sum test) will be done, see below for more details.

=== Testing for Equal Variance ===

We generally use the [https://cran.r-project.org/web/packages/car/index.html car] package which contains code for [https://en.wikipedia.org/wiki/Levene%27s_test Levene's Test] to see if two groups can be assumed to have equal variance:

<pre class="r">#load the car package
library(car)

#runs the test, grouping by the Treatment variable
leveneTest(Result ~ Treatment, data=test.data) %>% tidy %>% kable</pre>
{|
!align="right"| statistic
!align="right"| p.value
!align="right"| df
!align="right"| df.residual
|-
|align="right"| 0.368
|align="right"| 0.558
|align="right"| 1
|align="right"| 10
|}

== Performing the Appropriate Pairwise Test ==

The logic to follow is:

* If the Shapiro-Wilk test passes, do Levene's test. If it fails for either group, move on to a '''Wilcoxon Rank Sum Test'''.
* If Levene's test ''passes'', do a Student's ''t'' Test, which assumes equal variance.
* If Levene's test ''fails'', do a Welch's ''t'' Test, which does not assume equal variance.

=== Student's ''t'' Test ===

<pre class="r">#The default for t.test in R is Welch's, so you need to set the var.equal variable to be TRUE
t.test(Result~Treatment,data=test.data, var.equal=T) %>% tidy %>% kable</pre>
{|
!align="right" width="8%"| estimate
!align="right" width="9%"| estimate1
!align="right" width="9%"| estimate2
!align="right" width="9%"| statistic
!align="right" width="7%"| p.value
!align="right" width="9%"| parameter
!align="right" width="8%"| conf.low
!align="right" width="9%"| conf.high
!width="16%"| method
!width="11%"| alternative
|-
|align="right"| -1.1
|align="right"| 8.79
|align="right"| 9.89
|align="right"| -0.992
|align="right"| 0.345
|align="right"| 10
|align="right"| -3.56
|align="right"| 1.37
| Two Sample t-test
| two.sided
|}

=== Welch's ''t'' Test ===

<pre class="r">#The default for t.test in R is Welch's, so you need to set the var.equal variable to be FALSE, or leave the default
t.test(Result~Treatment,data=test.data, var.equal=F) %>% tidy %>% kable</pre>
{|
!align="right" width="8%"| estimate
!align="right" width="9%"| estimate1
!align="right" width="9%"| estimate2
!align="right" width="9%"| statistic
!align="right" width="7%"| p.value
!align="right" width="9%"| parameter
!align="right" width="8%"| conf.low
!align="right" width="9%"| conf.high
!width="20%"| method
!width="10%"| alternative
|-
|align="right"| -1.1
|align="right"| 8.79
|align="right"| 9.89
|align="right"| -0.992
|align="right"| 0.345
|align="right"| 9.72
|align="right"| -3.57
|align="right"| 1.38
| Welch Two Sample t-test
| two.sided
|}

=== Wilcoxon Rank Sum Test ===

<pre class="r"># no need to specify anything about variance
wilcox.test(Result~Treatment,data=test.data) %>% tidy %>% kable</pre>
{|
!align="right"| statistic
!align="right"| p.value
! method
! alternative
|-
|align="right"| 12
|align="right"| 0.394
| Wilcoxon rank sum exact test
| two.sided
|}

= Corrections for Multiple Observations =

The best illustration I have seen for the need for multiple observation corrections is this cartoon from XKCD (see http://xkcd.com/882/):

[[File:http://imgs.xkcd.com/comics/significant.png|frame|none|alt=Significance by XKCD. Image is from http://imgs.xkcd.com/comics/significant.png|caption Significance by XKCD. Image is from http://imgs.xkcd.com/comics/significant.png]]

Any conceptually coherent set of observations must therefore be corrected for multiple observations. In most cases, we will use the method of Benjamini and Hochberg since our p-values are not entirely independent. Some sample code for this is here:

<pre class="r">p.values <- c(0.023, 0.043, 0.056, 0.421, 0.012)
data.frame(unadjusted = p.values, adjusted=p.adjust(p.values, method="BH"))</pre>
<pre>## unadjusted adjusted
## 1 0.023 0.0575
## 2 0.043 0.0700
## 3 0.056 0.0700
## 4 0.421 0.4210
## 5 0.012 0.0575</pre>
= Session Information =

<pre class="r">sessionInfo()</pre>
<pre>## R version 4.4.1 (2024-06-14)
## Platform: x86_64-apple-darwin20
## Running under: macOS Monterey 12.7.6
##
## Matrix products: default
## BLAS: /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/lib/libRblas.0.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/lib/libRlapack.dylib; LAPACK version 3.12.0
##
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
##
## time zone: America/Detroit
## tzcode source: internal
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] car_3.1-2 carData_3.0-5 broom_1.0.6
## [4] pwr_1.3-0 knitcitations_1.0.12 dplyr_1.1.4
## [7] tidyr_1.3.1 knitr_1.48
##
## loaded via a namespace (and not attached):
## [1] jsonlite_1.8.8 compiler_4.4.1 tidyselect_1.2.1 Rcpp_1.0.13
## [5] xml2_1.3.6 stringr_1.5.1 jquerylib_0.1.4 yaml_2.3.10
## [9] fastmap_1.2.0 R6_2.5.1 plyr_1.8.9 generics_0.1.3
## [13] backports_1.5.0 tibble_3.2.1 RefManageR_1.4.0 lubridate_1.9.3
## [17] bslib_0.8.0 pillar_1.9.0 rlang_1.1.4 utf8_1.2.4
## [21] stringi_1.8.4 cachem_1.1.0 xfun_0.46 sass_0.4.9
## [25] bibtex_0.5.1 timechange_0.3.0 cli_3.6.3 withr_3.0.0
## [29] magrittr_2.0.3 digest_0.6.36 lifecycle_1.0.4 vctrs_0.6.5
## [33] evaluate_0.24.0 glue_1.7.0 abind_1.4-5 fansi_1.0.6
## [37] rmarkdown_2.27 purrr_1.0.2 httr_1.4.7 tools_4.4.1
## [41] pkgconfig_2.0.3 htmltools_0.5.8.1</pre>
= References =

<a name=bib-pwr></a>[[#cite-pwr|[1]]] S. Champely. ''pwr: Basic Functions for Power Analysis''. R package version 1.3-0. 2020. URL: https://CRAN.R-project.org/package=pwr.

Data Management

2024-08-11T19:08:00Z

Davebrid: Updated to match github version

[[ Category: General ]]
[[ Category: Data ]]
[[ Category: Statistics ]]
Most of the data we generate in the lab is numeric data, so it is very important that we are consistent in the way we record and structure our saved data. Below are some best practices on how to save and store your data in our group.

= Raw Data =

Data can be ''raw'' or ''processed''. It is the best practice to save files in the most raw format possible, preferably a '''csv file'''. As an example, a datafile might contain absorbance readings, that are converted by a standard curve into protein amounts. The raw data is the absorbances, the protein amounds would be processed data. Raw data is the most valuable and should be saved in that form. Sometimes you may have data that you know you are going to exclude. Include this in the raw data, and exclude it during the analysis with a note describing why.

== What Should Data Look Like? ==

Data shoiuld be '''tidy'''. This means that there should be continuous rows which contain columns that describe the conditions related to that data. If there are missing values, leave them as blank and do not enter as zero. For more details about tidy data read this paper: @Wickham2014.

== What Format Should I Save Raw Data In? ==

The preferred format is a CSV file. This is a ''non-proprietary'' open format. This is important because it is the smallest file size and allows anyone to view/open your data without needing any proprietary software like Microsoft Excel. This may seem like a minor concern, but 20 years from now someone may want to open your data and Excel may be difficult to find. You can still use Excel if you prefer to record raw data, but make sure you Save it as a CSV file. To make a CSV file from Microsoft Excel click on File -> Save As... then under File Format select CSV UTF-8 from the dropdown list. UTF-8 is the character encoding. Excel may prompt you to see if you are sure. It is also a good practice to make raw data files '''read only'''. To do this on an Apple computer, right click on it, go to Get Info then check the "Locked" checkbox. This prevents you from inadvertently changing raw data.

== Where Do I Store Data? ==

'''All data''' needs to be stored on our shared drives. Most of this data should be on the U-drive (except for human data or data on GreatLakes, see below). These folders are secure, and backed up. You can't forget it on the bus, or drop it in the sewer by accident. Data should only be on USB sticks when you are moving between computers and should only be on your laptop when you do not have internet connectivity. You can organize your folder anyway you like, but some good subfolders might be:

* Data
* Writing
* Diagrams

Keep experimental results in the Data folder, which you should organize into subfolders as appropriate. When you do an experiment, create a folder describing that experiment (for example Effects of Rapamycin on Glycolysis). Inside that folder create a new subfolder for each replicate of that experiment. Everything about that replicate should be in the subfolder(s) including raw and processed data and analysis files.

'''Human data''' must be stored in HIPAA compliant folders. These are restricted to those individuals with IRB access to those folders. For data from Michigan Precision Health, this data is on Armis2, the secure storage system.

=== What About Other Experimental Details? ===

Oftentimes a csv file is insufficient to totally describe what was done, and other details about the experiment. For each experiment create a file that describes the raw data. This should be contained in the Rmd file that analyses the data, but if this is not possible, create a README.md file that describes the files and their contents. Think of this as an online version of your experimental notes and should describe what datafiles were generated, what the columns indicate and anything you may need to know about analysing the data. There are more details about how to structure your Rmarkdown files below.

== How Do We Convert Raw Data into Graphs or Statistical Outputs? ==

While it may seem convenient to have the raw data, and analysed data all in the same file, we prefer instead to have an analysis layer between raw data and the output. For our lab, this is done using Rmarkdown or [https://quarto.org/docs/computations/r.html Quarto] files (such as this one). This is a script file that will combine normal writing (in markdown format, see https://daringfireball.net/projects/markdown/syntax for syntax) and all the relevant analysis steps. This is useful for many reasons, the main one is reproducibility. By using a script, it is very clear how you get from raw data to your eventual outputs, and can be re-run if you want to add a new graph or test easily. Scripts can also be easily copied and modified to a similar experiment. For example if you are repeating an experiment the Rmarkdown file could be copied over to the new experiment folder (with new raw data). Think of the raw data as a chunk of steak, the script as a meat grinder and the processed data as a hamburger. Remember, its impossible to make a steak from a hamburger, but its easy to go the other direction.

= Processed Data =

Processed data could be calculated data, or figures. These are created by the Rmarkdown or Quarto file, and are over-written every time the analysis is re-run.

== What Sections Should My Rmarkdown/Quarto Files Contain? ==

There is a lot of details about the syntax of your Rmarkdown file here:

Generally your Rmarkdown files should have these sections. If you want a template as a starting point try using this one https://raw.githubusercontent.com/BridgesLab/Lab-Documents/master/Experimental%20Policies/Rmarkdown-template.Rmd

'''Purpose''': Make a brief description of why you did the experiment, ideally explicitly stating your hypothesis.

'''Experimental Details''': Link to the protocol used (permalink preferred) for the experiment and include any notes relevant to your analysis. This might include specifics not in the general protocol such as cell lines, treatment doses etc.

'''Raw Data''': Describe your raw data files, including what the columns mean (and what units they are in).

'''Analysis''': Describing the analysis as you intersperse code chunks

'''Interpretation''': A brief summary of what the interpretation of these results were

'''Session Information''': A block with the sessionInfo() command printing out

'''References''': If needed, using Rmarkdown citation tools (see this link for more information: http://rmarkdown.rstudio.com/authoring_bibliographies_and_citations.html)

=== How Do I Load Raw Data into R ===

The preferred package for reading csv files is called '''readr'''. This is a useful package that can read in a variety of formats including CSV. The syntax is fairly simple:

<pre class="r">library(readr) #loads the readr package
filename <- 'testfile.csv' #make this a separate line, you can use any variable you want
data <- read_csv(filename)</pre>
<pre>## Rows: 60 Columns: 3
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (1): supp
## dbl (2): len, dose
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.</pre>
As shown above, readr tries to guess the datatype in each column as above. This can be over-ridden by explicitly stating column format in the read_csv command. Think carefully about whether data should be an integer, character or factor. For grouping factors, its best to explicitly state levels and reference values immediately after the data import. More details about loading data can be found here: http://r4ds.had.co.nz/data-import.html.

Immediately after you load your data in the Rmarkdown file have a block of text such as this:

<pre>These data can be found in /Users/davebrid/Documents/GitHub/Lab-Documents/Experimental Policies in a file named testfile.csv. This script was most recently updated on Sun Aug 11 15:03:55 2024.</pre>
This will render as this:

These data can be found in /Users/davebrid/Documents/GitHub/Lab-Documents/Experimental Policies in a file named testfile.csv. This script was most recently updated on Sun Aug 11 15:03:55 2024.

This clearly indicates where to find the file, and when it was most recently updated. This is helpful for when printing out your Rmarkdown files and finding the data from your notes on the data server.

Safety and Animal Training

2024-06-25T13:05:41Z

Davebrid: /* General Lab Safety */ Added CRU details

These are the classes that lab staff need to take at Michigan:

==General Lab Safety==
These are offered through MyLink at https://maislinc.umich.edu/. All lab personnel need to take these

* EHS_BLS025w ONLINE REQUIRED General Laboratory Safety Training (online)
* EHS_BLS023w Centrifuge & Rotor Safety Training (online)
* BLS013w ONLINE REQUIRED Autoclave Standard Operating Procedures (online)

If you will be working with blood you will need to take

* BLS101w ONLINE REQUIRED Bloodborne Pathogens (online)

If you will be working with radioactive materials, you will have to take this course as well:

* RSS006 REQUIRED Radiation Safety Orientation (classroom)
* RSS103w REQUIRED ONLINE REQUIRED Radionuclide Users Annual Refresher Training (to be completed every CALENDAR year)
If you will be working with any viruses you will have to take this course as well:

* BLS008 REQUIRED Working Safely with Viral Vectors (classroom)

If you plan to breed animals, you can also take this course:

*ULAM-10125 Breeding Colony Management for Rats and Mice (online)

If you will be working at a core facility such as a clinical research unit

* BLS001 - TAB Hazard Communication for Employees Working in Research Support Units, Labs and Shops

==Animals==
If you will be working with animals you will have to take these classes. They are all offered through ULAM MLearning (https://trainingportal.med.umich.edu/). This requires a levels 2 password.

* ULAM-10000 Orientation (online)
* ULAM-10050 Hazards pt.1 (online)
* ULAM-10055 Hazards pt.2 (classroom)
* ULAM-10100 Intro Mouse/Rat (online)
* ULAM-10131 Animal Room Procedures pt.1 (online)
* ULAM-10132 Animal Room Procedures pt.2 (classroom)
* ULAM-10105 Lab Mouse Workshop (classroom)

==Human Subject Data==
If you will be working with Human data you will have to take these classes. They are all offered through MLearning (https://trainingportal.med.umich.edu/). This requires a levels 2 password.

* PRIV-10001 HIPAA Training for All Workforce Members (online)
* PEERRS (online)
* DCE101 U-M Data Protection and Responsible Use (online, for HSIP)
* MiChart Research Access eLearning Research Certification (MC-RE20001V)(Online)
* MiChart Inpatient Allied Health HOD Certification (MC-HD70003A)(Online)

==Lab Standard Operating Procedures==
For lab specific safety training please review the SOP's and sign them if you will be using any of them. All lab SOP's are available [[:Category: SOP|here]]

[[ Category: Lab Safety ]]
[[ Category: Training ]]
[[Category: SOP]]

Using Snakemake on the HPC Cluster

2024-05-16T20:00:57Z

Davebrid: Switched back

== Setup ==

* Install snakemake via mamba/conda (see https://snakemake.readthedocs.io/en/stable/getting_started/installation.html)
* In the working folder create a snakemake environment with <pre>mamba activate snakemake</pre>
* Install the cluster-generic tool to submit snakemake files to a cluster from pip with <pre>pip install snakemake-executor-plugin-cluster-generic</pre>
* Create a generic profile in ~/.config/snakemake/testprofile/config.yaml such as:

<pre>
executor: slurm
jobs: 100

default-resources:
mem_mb: max(1.5 * input.size_mb, 100)
account: <ACCOUNT_NAME>
partition: <PARTITION NAME>
set-threads:
myrule: max(input.size_mb / 5, 2)
set-resources:
myrule:
mem_mb: attempt * 200
</pre>

== Executing a Snakefile Workflow ==
* Create a Snakefile (see
** You can over-ride resources with that flag otherwise it will use the values in testprofile
* Run the Snakefile with this command <pre>snakemake --profile testprofile -j 1 --executor cluster-generic --cluster-generic-submit-cmd "batch" ... </pre>

Using Snakemake on the HPC Cluster

2024-05-16T19:59:53Z

Davebrid: Changed to code tags

== Setup ==

* Install snakemake via mamba/conda (see https://snakemake.readthedocs.io/en/stable/getting_started/installation.html)
* In the working folder create a snakemake environment with <code>mamba activate snakemake</cpde>
* Install the cluster-generic tool to submit snakemake files to a cluster from pip with <code>pip install snakemake-executor-plugin-cluster-generic</code>
* Create a generic profile in ~/.config/snakemake/testprofile/config.yaml such as:

<code>
executor: slurm
jobs: 100

default-resources:
mem_mb: max(1.5 * input.size_mb, 100)
account: <ACCOUNT_NAME>
partition: <PARTITION NAME>
set-threads:
myrule: max(input.size_mb / 5, 2)
set-resources:
myrule:
mem_mb: attempt * 200
</code>

== Executing a Snakefile Workflow ==
* Create a Snakefile (see
** You can over-ride resources with that flag otherwise it will use the values in testprofile
* Run the Snakefile with this command <code>snakemake --profile testprofile -j 1 --executor cluster-generic --cluster-generic-submit-cmd "batch" ... </code>

Using Snakemake on the HPC Cluster

2024-05-16T19:50:10Z

Davebrid: Created initial coding example for snakemake

== Setup ==

* Install snakemake via mamba/conda (see https://snakemake.readthedocs.io/en/stable/getting_started/installation.html)
* In the working folder create a snakemake environment with <pre>mamba activate snakemake</pre>
* Create a generic profile in ~/.config/snakemake/testprofile/config.yaml such as:

<pre>
executor: slurm
jobs: 100

default-resources:
mem_mb: max(1.5 * input.size_mb, 100)
account: <ACCOUNT_NAME>
partition: <PARTITION NAME>
set-threads:
myrule: max(input.size_mb / 5, 2)
set-resources:
myrule:
mem_mb: attempt * 200
</pre>
* Create a Snakefile (see
** You can over-ride resources with that flag otherwise it will use the values in testprofile
* Run the Snakefile with this command <pre>snakemake --profile testprofile -j 1 --executor cluster-generic --cluster-generic-submit-cmd "batch" ... </pre>

Serum Total Cholesterol Assay

2024-01-18T16:06:47Z

Davebrid: Created intitial protocol

== Materials ==
* Serum, need at most 10 uL per mouse, at little as 2 uL per mouse. See [[Collecting_and_Storing_Mouse_Serum]]
* Infinity cholesterol reagent (Thermo Cat# TR13421)
* Cholesterol standard (Pointe Scientific). Also make a 10x dilution.
* Clear 96 well plate (we use Thermo Cat# 130188)
* Plate reader

== Protocol ==
* Draw out plate including samples, plan for 2-3 replicates for each sample
** Include plans for standard curve, using 2, 4, 6, 8 uL of 10x diluted cholesterol standard, and 1, 1.5, 2 uL of the undiluted cholesterol standard
* Add 100 uL cholesterol reagent to each well using the multichannel pipet.
* Start a timer
* Add 2 uL serum to each well
* In the middle of the time add the standards
* The assay takes 15 minutes to develop at room temperature, and is stable for 30 minutes. That means if the timer hits 30 minutes you wont be able to finish in time, so stop and start the plate.
* Once all samples are added, incubate plate at room temperature for 30 minutes
* Measure absorbance at 500 nm

== Calculations ==
* Draw a standard curve of Cholesterol amount (in ug) versus absorbance
* From the slope of that curve (or a linear model) calculate the amount of cholesterol per well, divide that by two
* Average the replicates. Repeat if technical variation is too high