Hello everybody,
I am a beginner in R&Bioinformatics and I am following a tutorial based on the book of Dan Maclean, R Bioinformatics Cookbook.
I have a question with regard to the interpretation of the results on some differential expression.
In essence, I am performing differential expression on a subset of Drosophila Melanogaster and I would like an explanation in natural terms on the results obtained.
Practically I select a subset of of larvae and I perform Differential Expression and I get those results:
grouping <- droplevels(phenoData(modencodefly.eset)[['stage']][columns_of_interest])
print(columns_of_interest) print(grouping)
counts_of_interest <- exprs(modencodefly.eset)[, columns_of_interest]
eset_dge <- edgeR::DGEList( counts = counts_of_interest, group = grouping )
design <- model.matrix(~ grouping)
eset_dge <-edgeR::estimateDisp(eset_dge, design)
fit <- edgeR::glmQLFit(eset_dge, design)
result <- edgeR::glmQLFTest(fit, coef=2)
topTags(result)
The table below is the result obtained after D.E.
logFC logCPM F PValue FDR
FBgn0027527 6.318665 11.148756 42854.72 1.132951e-41 1.684584e-37
FBgn0037424 6.417770 9.715826 33791.15 2.152507e-40 1.518091e-36
FBgn0037430 6.557774 9.109132 32483.00 3.510727e-40 1.518091e-36
FBgn0037414 6.337846 10.704514 32088.92 4.083908e-40 1.518091e-36
FBgn0029807 6.334590 9.008720 27648.19 2.585312e-39 7.688200e-36
FBgn0037224 7.055635 9.195077 24593.62 1.102456e-38 2.732070e-35
Can someone explain to me the first 3 columns?
Thank you
See this thread