[BioC] Which log2FC to report?

[Rafael Moreira [guest]]

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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