Using Bioconductor To Analyse Beadarray Data: Difference between revisions
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*You may need to alter either the ProbeID or ControlID to fit the illuminaprobe column from the sampleprobe or controlprobe datasets. | *You may need to alter either the ProbeID or ControlID to fit the illuminaprobe column from the sampleprobe or controlprobe datasets. | ||
==Data Normalisation== | |||
*Microarray data is typically quantile normalised and log2 transformed: | |||
<pre>BSData.quantile = normaliseIllumina(BSData, method="quantile", transform="log2")</pre> | |||
*To examine the effects of normalisation on the dataset use boxplots: | |||
<pre> | |||
boxplot(as.data.frame(log2(exprs(BSData))),las=2,outline=FALSE, ylab="Intensity (Log2 Scale)") | |||
boxplot(as.data.frame(exprs(BSData.quantile)),las=2,outline=FALSE, ylab="Intensity (Log2 Scale)") | |||
</pre> | |||
*Save these boxplots as postscript files. | |||
*This fits the data into the BSData dataframe. Phenotype data can be accessed by pData(BSData) and expression data can be accessed by exprs(BSData). | *This fits the data into the BSData dataframe. Phenotype data can be accessed by pData(BSData) and expression data can be accessed by exprs(BSData). | ||