[BioC] Which log2FC to report?
Rafael Moreira [guest]
guest at bioconductor.org
Tue Apr 15 15:50:34 CEST 2014
Hello community, I'm using DESeq and edgeR to conduct RNA-Seq data analysis.
I want to get log2FC adjusted for (possible) lane effects. For example, in edgeR I use:
design = model.matrix(~ lane + condition, data=tmp)
de = DGEList(counts, group=tmp$condition)
de = calcNormFactors(de)
de = estimateGLMCommonDisp(de, design)
de = estimateGLMTrendedDisp(de, design)
de = estimateGLMTagwiseDisp(de, design)
fit = glmFit(de, design)
lrt = glmLRT(fit, coef='conditiontreated')
while in DESeq2, I have:
rawData <- DESeqDataSetFromMatrix(counts, pd, ~ lane + condition)
dds <- DESeq(rawData, test='LRT', reduced= ~ lane)
>From the documentation, this seems the right way of getting the DE genes when I want to account for the lane effect. Is this correct? Or would be something like
DESeq(rawData)
sufficient? (and of course getting the results for the proper coefficient) Does the same apply for edgeR?
-- output of sessionInfo():
R version 3.0.3 Patched (2014-03-06 r65200)
Platform: x86_64-apple-darwin10.8.0 (64-bit)
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
attached base packages:
[1] parallel splines stats graphics grDevices utils datasets
[8] methods base
other attached packages:
[1] DESeq2_1.2.10 RcppArmadillo_0.4.200.0 Rcpp_0.11.1
[4] GenomicRanges_1.14.4 XVector_0.2.0 IRanges_1.20.7
[7] BiocGenerics_0.8.0 edgeR_3.4.2 limma_3.18.13
loaded via a namespace (and not attached):
[1] annotate_1.40.1 AnnotationDbi_1.24.0 Biobase_2.22.0
[4] DBI_0.2-7 genefilter_1.44.0 grid_3.0.3
[7] lattice_0.20-29 locfit_1.5-9.1 RColorBrewer_1.0-5
[10] RSQLite_0.11.4 stats4_3.0.3 survival_2.37-7
[13] XML_3.95-0.2 xtable_1.7-3
--
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