I followed the following tutorial for RNA-Seq data analysis. https://ycl6.gitbooks.io/rna-seq-data-analysis/
After performing the Differential expression analysis using R (https://ycl6.gitbooks.io/rna-seq-data-analysis/perform_de_analysis.html) the final output files are DE_analysis.gene.txt and DE_analysis_transcript.txt. The output file has the following format:
chr left right gid score strand name source biotype logFC logCPM F PValue FDR
1 14403 29570 ENSG00000227232 . - WASH7P havana unprocessed_pseudogene 2.890084925 2.977441296 103.3708945 8.25E-09 3.27E-08
1 89294 133723 ENSG00000238009 . - RP11-34P13.7 ensembl_havana lincRNA 11.51392342 1.605598781 167.1675845 2.10E-10 1.21E-09
Could someone please explain the file format? Especially left, right, logFC, logCPM, and F. Which column represents the average gene expression value?
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mhasa006
1 answer
Pretty difficult to evaluate exactly without seeing the contents of RunEdgeR.R but my guess is
chr = chromosome
left = 5 ' start position on chromosome of feature
right = 3 ' end position on chromosome of feature
grid = feature code
score = ?
name = feature name
source = data source
biotype = feature type
logFC = fold(2) change difference in expression(no idea what the test is)
logCPM = log(2?) counts per million
F = ?
PValue = pvalue for logFC
FDR = false discovery rate for logFC
LogCPM seems to be the expression value you're looking for but I have no idea if it's averaged like you ask without the experimental design.
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