RNA-seq Pipeline for Known Transcripts: Difference between revisions

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~~RNA-Seq pipeline – known transcripts~~

==Reference Pages==

~~1. Run FASTQ to assess quality of reads from sequencer and:~~

* http://seqanswers.com/wiki/How-to/RNASeq_analysis

~~a. Filter for quality, if applicable~~

~~b. Trim, if applicable~~

c. http://~~www.bioinformatics~~.~~bbsrc.ac.uk~~/~~projects~~/~~fastqc~~/

2. Run ~~bowtie-build~~ to ~~generate Burroughs Wheeler transformed reference genome (.ebwt format).~~

==Sequence Quality and Trimming==

a. http://~~bowtie-bio~~.~~sourceforge~~.~~net/index~~.~~shtml (bowtie, tophat, and cufflinks are here)~~.

# Run FASTQC to assess quality of reads from sequencer and:

b. ~~[Optional input~~ and ~~parameter settings are in square brackets~~.]

# FASTQC available at http://www.bioinformatics.bbsrc.ac.uk/projects/fastqc/

c. ~~<Required parameters are in greater than~~/~~less than brackets~~.>

## Open run_fastqc on a windows machine. Individually open each sequence file and allow it to analyse. Save this report.

d. ~~This BW transformed reference genome can be created once then used repeatedly in the future~~.

## Check this report to decide if sequences need to be trimmed or discarded. See http://bioinfo.cipf.es/courses/mda11/lib/exe/fetch.php?media=ngs_qc_tutorial_mda_val_2011.pdf for sample results and an explanation of the quality report

e. ~~$ is~~ the ~~command prompt.~~

~~$ bowtie~~-~~build~~ [-~~f specifies reference genome is~~ in ~~fasta~~ format] <~~path to input reference genome~~ (e.g. /~~ccmb~~/~~CoreBA~~/~~BioinfCore~~/~~Common~~/~~DATA~~/~~BowtieData~~/~~H_Sapiens~~/~~hg19~~.~~fa)~~> <~~base name for reference genome output~~ .~~ebwt files (e~~.~~g hg19)~~>

===Filter Sequences Using FastX-Toolkit===

# If samples are barcoded use Fastx barcode splitter (see http://hannonlab.cshl.edu/fastx_toolkit/commandline.html#fastx_barcode_splitter_usage for more details):

<pre>

/usr/local/bin/fastx_barcode_splitter.pl --bcfile FILE --prefix PREFIX [--suffix SUFFIX] [--bol|--eol] [--mismatches N] [--exact] [--partial N] [--help] [--quiet] [--debug]

</pre>

* This requires a barcode file in the format where BC# is the barcode number and the nucleotide names are the barcodes:

<pre>

#This line is a comment (starts with a 'number' sign)

BC1 GATCT

BC2 ATCGT

BC3 GTGAT

BC4 TGTCT

</pre>

* This file is the FILE for the --bcfile option

* Example command where s_2_100.txt is the original file, mybarcodes.txt is the barcode file, 2 mismatches are allowed (default is 1). This will generate files /tmp/bla_BC#.txt:

<pre>

cat s_2_100.txt | /usr/local/bin/fastx_barcode_splitter.pl --bcfile mybarcodes.txt --bol --mismatches 2 --prefix /tmp/bla_ --suffix ".txt"

</pre>

# Filter for quality, if applicable

# Trim, if applicable using Fast-x. The following keeps 100% of the reads with a quality of 25 or greater:

<pre>

fastq_quality_filter -v -q 25 -p 100 -i control-reads.txt -o control-reads-quality25.txt

</pre>

3. Run tophat to align reads to the reference genome. I’ve included a pseudo command line as well as a “real” command line.

==Align Reads==

This can be done with either TopHat or Bowtie, so choose one of the following. The reference genomes are located in the following locations:

<pre>

/database/davebrid/RNAseq/reference-genomes/hg19

/database/davebrid/RNAseq/reference-genomes/mm9

</pre>

These reference alignments are pre-built UCSC genomes and downloaded from ftp://ftp.cbcb.umd.edu/pub/data/bowtie_indexes/

===Align Reads to Reference Genome with Bowtie===

Run bowtie to align reads to reference genomes. The following generates a sam formatted alignment using the best quality flag for reads aligned to hg19

<pre>

bowtie --sam --best /database/davebrid/RNAseq/reference-genomes/hg19/hg19 control-reads-quality25.txt control-aligned-quality25.sam

</pre>

===Align Reads to Reference Genome with Tophat===

Run tophat to align reads to the reference genome. I’ve included a pseudo command line as well as a “real” command line.

<pre>

$ tophat [-p #processors -o ./output_directory] <./reference genome in both .ebwt and fasta formats (e.g. /ccmb/CoreBA/BioinfCore/Common/DATA/BowtieData/H_Sapiens/hg19)> <reads file to be aligned (e.g. s_1_1_sequence.fastq)>

$ tophat -p 5 -o ./HG19/tophat_out_hg19_001_trimmed /ccmb/CoreBA/BioinfCore/Common/DATA/BowtieData/H_Sapiens/hg19 ./HG19/Rich_trim/A_1_16_85.fastq

</pre>

4. Run cuffcompare to create .gtf format reference genome from a generic reference genome. Note that cuffcompare adds the tss_id and p_id columns that you will need in cuffdiff. This .gtf reference can be created once then used repeatedly in the future.

==Use Cuffcompare to Generate .gtf Reference==

Run cuffcompare to create .gtf format reference genome from a generic reference genome. Note that cuffcompare adds the tss_id and p_id columns that you will need in cuffdiff. This .gtf reference can be created once then used repeatedly in the future.

<pre>

$ cuffcompare [-o ./output_directory] < input file twice (e.g. /ccmb/CoreBA/BioinfCore/Common/DATA/CufflinksData_hg19/hg19.gtf /ccmb/CoreBA/BioinfCore/Common/DATA/CufflinksData_hg19/hg19.gtf )>

$ cuffcompare -o ./cuffcompare_out /ccmb/CoreBA/BioinfCore/Common/DATA/CufflinksData_hg19/hg19_genes.gtf /ccmb/CoreBA/BioinfCore/Common/DATA/CufflinksData_hg19/hg19_genes.gtf

</pre>

==Use Cuffdiff to Identify Differentially Expressed Transcripts==

5. Run cuffdiff to identify differentially abundant transcripts.

Run cuffdiff to identify differentially abundant transcripts.

<pre>

$ cuffdiff [-p #processors -o ./output_directory –L label1,label2,etc. –T (for time series data) –N (use upper quantile normalization –compatible_hits_norm (use reference hits in normalization) –b (use reference transcripts to reduce bias, include path to file e.g. /ccmb/CoreBA/BioinfCore/Common/DATA/BowtieData/H_Sapiens/hg19.fa) –u (improve multi-read weighting) ] <transcripts.gtf (produced by cuffcompare) sample_A_accepted_hits1.bam, sample_A_accepted_hits2.bam,etc (all produced by tophat) sample_B_accepted_hits1.bam,sample_B_accepted_hits2.bam, etc>

$ cuffdiff -o ./HG19/Cuffdiff_out_options_b_u_N_compatible/ -p 14 -L Control,PUF_kd --no-update-check -b /ccmb/CoreBA/BioinfCore/Common/DATA/BowtieData/H_Sapiens/hg19.fa -u -N --compatible-hits-norm /ccmb/CoreBA/BioinfCore/Projects/Goldstrohm_McEachin/HG19/cuffcompare_out.combined.gtf /ccmb/CoreBA/BioinfCore/Projects/Goldstrohm_McEachin/HG19/tophat_out_hg19_001_trimmed/accepted_hits.bam /ccmb/CoreBA/BioinfCore/Projects/Goldstrohm_McEachin/HG19/tophat_out_hg19_002_trimmed/accepted_hits.bam

</pre>

[[Category: Bioinformatics]]

[[Category: Transcription]]

[[Category: RNA-seq]]

[[Category: Next Generation Sequencing]]

@@ Line 1: / Line 1: @@
-RNA-Seq pipeline – known transcripts
+==Reference Pages==
-.	Run FASTQ to assess quality of reads from sequencer and:
+* http://seqanswers.com/wiki/How-to/RNASeq_analysis
-a.	Filter for quality, if applicable
-b.	Trim, if applicable
-c.	http://www.bioinformatics.bbsrc.ac.uk/projects/fastqc/
-.	Run bowtie-build to generate Burroughs Wheeler transformed reference genome (.ebwt format).
+==Sequence Quality and Trimming==
-a.	http://bowtie-bio.sourceforge.net/index.shtml (bowtie, tophat, and cufflinks are here).
+# Run FASTQC to assess quality of reads from sequencer and:
-b.	[Optional input and parameter settings are in square brackets.]
+# FASTQC available at http://www.bioinformatics.bbsrc.ac.uk/projects/fastqc/
-c.	<Required parameters are in greater than/less than brackets.>
+## Open run_fastqc on a windows machine.  Individually open each sequence file and allow it to analyse.  Save this report.
-d.	 This BW transformed reference genome can be created once then used repeatedly in the future.
+## Check this report to decide if sequences need to be trimmed or discarded.  See http://bioinfo.cipf.es/courses/mda11/lib/exe/fetch.php?media=ngs_qc_tutorial_mda_val_2011.pdf for sample results and an explanation of the quality report
-e.	$ is the command prompt.
-$ bowtie-build [-f specifies reference genome is in fasta format] <path to input reference genome (e.g. /ccmb/CoreBA/BioinfCore/Common/DATA/BowtieData/H_Sapiens/hg19.fa)> <base name for reference genome output .ebwt files (e.g hg19)>
+===Filter Sequences Using FastX-Toolkit===
+# If samples are barcoded use Fastx barcode splitter (see http://hannonlab.cshl.edu/fastx_toolkit/commandline.html#fastx_barcode_splitter_usage for more details):
+<pre>
+/usr/local/bin/fastx_barcode_splitter.pl --bcfile FILE --prefix PREFIX [--suffix SUFFIX] [--bol|--eol] [--mismatches N] [--exact] [--partial N] [--help] [--quiet] [--debug]
+</pre>
+* This requires a barcode file in the format where BC# is the barcode number and the nucleotide names are the barcodes:
+<pre>
+#This line is a comment (starts with a 'number' sign)
+BC1 GATCT
+BC2 ATCGT
+BC3 GTGAT
+BC4 TGTCT
+</pre>
+* This file is the FILE for the --bcfile option
+* Example command where s_2_100.txt is the original file, mybarcodes.txt is the barcode file, 2 mismatches are allowed (default is 1).  This will generate files /tmp/bla_BC#.txt:
+<pre>
+cat s_2_100.txt | /usr/local/bin/fastx_barcode_splitter.pl --bcfile mybarcodes.txt --bol --mismatches 2 --prefix /tmp/bla_ --suffix ".txt"
+</pre>
+# Filter for quality, if applicable
+# Trim, if applicable using Fast-x.  The following keeps 100% of the reads with a quality of 25 or greater:
+<pre>
+fastq_quality_filter -v -q 25 -p 100  -i  control-reads.txt -o control-reads-quality25.txt
+</pre>
-.	Run tophat to align reads to the reference genome. I’ve included a pseudo command line as well as a “real” command line.
+==Align Reads==
+This can be done with either TopHat or Bowtie, so choose one of the following.  The reference genomes are located in the following locations:
+<pre>
+/database/davebrid/RNAseq/reference-genomes/hg19
+/database/davebrid/RNAseq/reference-genomes/mm9
+</pre>
+These reference alignments are pre-built UCSC genomes and downloaded from ftp://ftp.cbcb.umd.edu/pub/data/bowtie_indexes/
+===Align Reads to Reference Genome with Bowtie===
+Run bowtie to align reads to reference genomes.  The following generates a sam formatted alignment using the best quality flag for reads aligned to hg19
+<pre>
+bowtie --sam --best /database/davebrid/RNAseq/reference-genomes/hg19/hg19 control-reads-quality25.txt control-aligned-quality25.sam
+</pre>
+===Align Reads to Reference Genome with Tophat===
+Run tophat to align reads to the reference genome. I’ve included a pseudo command line as well as a “real” command line.
+<pre>
 $ tophat [-p #processors -o ./output_directory] <./reference genome in both .ebwt and fasta formats (e.g. /ccmb/CoreBA/BioinfCore/Common/DATA/BowtieData/H_Sapiens/hg19)> <reads file to be aligned (e.g. s_1_1_sequence.fastq)>
 $ tophat -p 5 -o ./HG19/tophat_out_hg19_001_trimmed /ccmb/CoreBA/BioinfCore/Common/DATA/BowtieData/H_Sapiens/hg19 ./HG19/Rich_trim/A_1_16_85.fastq
+</pre>
-.	Run cuffcompare to create .gtf format reference genome from a generic reference genome. Note that cuffcompare adds the tss_id and p_id columns that you will need in cuffdiff. This .gtf reference can be created once then used repeatedly in the future.
+==Use Cuffcompare to Generate .gtf Reference==
+Run cuffcompare to create .gtf format reference genome from a generic reference genome. Note that cuffcompare adds the tss_id and p_id columns that you will need in cuffdiff. This .gtf reference can be created once then used repeatedly in the future.
+<pre>
 $ cuffcompare [-o ./output_directory] < input file twice (e.g. /ccmb/CoreBA/BioinfCore/Common/DATA/CufflinksData_hg19/hg19.gtf /ccmb/CoreBA/BioinfCore/Common/DATA/CufflinksData_hg19/hg19.gtf )>
 $ cuffcompare -o ./cuffcompare_out /ccmb/CoreBA/BioinfCore/Common/DATA/CufflinksData_hg19/hg19_genes.gtf /ccmb/CoreBA/BioinfCore/Common/DATA/CufflinksData_hg19/hg19_genes.gtf
+</pre>
+==Use Cuffdiff to Identify Differentially Expressed Transcripts==
-.	Run cuffdiff to identify differentially abundant transcripts.
+Run cuffdiff to identify differentially abundant transcripts.
+<pre>
 $ cuffdiff  [-p #processors -o ./output_directory –L label1,label2,etc. –T (for time series data) –N (use upper quantile normalization –compatible_hits_norm (use reference hits in normalization) –b (use reference transcripts to reduce bias, include path to file e.g. /ccmb/CoreBA/BioinfCore/Common/DATA/BowtieData/H_Sapiens/hg19.fa) –u (improve multi-read weighting) ] <transcripts.gtf (produced by cuffcompare) sample_A_accepted_hits1.bam, sample_A_accepted_hits2.bam,etc (all produced by tophat) sample_B_accepted_hits1.bam,sample_B_accepted_hits2.bam, etc>
 $ cuffdiff -o ./HG19/Cuffdiff_out_options_b_u_N_compatible/ -p 14 -L Control,PUF_kd --no-update-check -b /ccmb/CoreBA/BioinfCore/Common/DATA/BowtieData/H_Sapiens/hg19.fa -u -N --compatible-hits-norm /ccmb/CoreBA/BioinfCore/Projects/Goldstrohm_McEachin/HG19/cuffcompare_out.combined.gtf /ccmb/CoreBA/BioinfCore/Projects/Goldstrohm_McEachin/HG19/tophat_out_hg19_001_trimmed/accepted_hits.bam /ccmb/CoreBA/BioinfCore/Projects/Goldstrohm_McEachin/HG19/tophat_out_hg19_002_trimmed/accepted_hits.bam
+</pre>
+[[Category: Bioinformatics]]
+[[Category: Transcription]]
+[[Category: RNA-seq]]
+[[Category: Next Generation Sequencing]]