Hi all I am using DEXSeq to analyse genome wide exon usage in RNA-Seq sample from maize. I have two factors data. One is condition (weedy/weed-free) and thiamethoxam treatment (treated/untreated). Each has 3 replicates. I wanted to see the differential exon usage for weedy versus weed-free, treated versus untreated and for interaction between condition and treatment. Here is my sample table : condition treatment replicate WC_RepI weedy untreated 1 WC_RepII weedy untreated 2 WC_RepIII weedy untreated 3 WCT_RepI weedy treated 1 WCT_RepII weedy treated 2 WCT_RepIII weedy treated 3 WFC_RepI weed-free untreated 1 WFC_RepII weed-free untreated 2 WFC_RepIII weed-free untreated 3 WFT_RepI weed-free treated 1 WFT_RepII weed-free treated 2 WFT_RepIII weed-free treated 3
The DEXSeq dataset is dxd1= DEXSeqDataSetFromHTSeq( countFiles, sampleData=SampleTable, design=~sample+exon+treatment:exon+condition:exon, flattenedfile=annotfile) The formula that I used for all 3 analysis; For weedy vs weed-free, formulaFullModel=~sample+exon+treatment:exon+condition:exon formulaReducedModel=~sample+exon+treatment:exon dxd_e1=estimateDispersions(dxd1,formula=formulaFullModel) dxd_t1=testForDEU(dxd_e1,reducedModel=formulaReducedModel,fullModel=formulaFullModel) dxd_fc1=estimateExonFoldChanges(dxd_t1,fitExpToVar = "condition") dxr3=DEXSeqResults(dxd_fc1) For treated vs untreated, formulaFullModel_t=~sample+exon+condition:exon+treatment:exon formulaReducedModel_t=~sample+exon+condition:exon dxd_e2=estimateDispersions(dxd1,formula=formulaFullModel_t) dxd_t2=testForDEU(dxd_e2,reducedModel=formulaReducedModel_t,fullModel=formulaFullModel_t) dxd_fc2=estimateExonFoldChanges(dxd_t2,fitExpToVar = "treatment") dxr2=DEXSeqResults(dxd_fc2) For interaction, colData(dxd1)$mix<-paste0(colData(dxd1)$condition,colData(dxd1)$treatment) formulaFullModel_i=~sample+exon+condition:exon+treatment:exon+condition:treatment:exon formulaReducedModel_i=~sample+exon+condition:exon+treatment:exon dxd_e3=estimateDispersions(dxd1,formula=formulaFullModel_i) dxd_t3=testForDEU(dxd_e3,reducedModel=formulaReducedModel_i,fullModel=formulaFullModel_i) dxd_fc3=estimateExonFoldChanges(dxd_t3,fitExpToVar = "mix") dxr3=DEXSeqResults(dxd_fc3) For first two analysis I got same result with no significant hits for padj<0.1 While, for interaction I got 1 significant hit at padj<0.1. I am just wondering if such results can be expected. Did I do wrong somewhere in the steps? I will really appreciate your suggestions. My session info : R version 3.3.1 (2016-06-21) Platform: x86_64-w64-mingw32/x64 (64-bit) Running under: Windows >= 8 x64 (build 9200) locale: [1] LC_COLLATE=English_Canada.1252 LC_CTYPE=English_Canada.1252 [3] LC_MONETARY=English_Canada.1252 LC_NUMERIC=C [5] LC_TIME=English_Canada.1252 attached base packages: [1] stats4 parallel stats graphics grDevices utils datasets [8] methods base other attached packages: [1] genefilter_1.54.2 DEXSeq_1.18.4 [3] RColorBrewer_1.1-2 AnnotationDbi_1.34.4 [5] DESeq2_1.12.3 SummarizedExperiment_1.2.3 [7] GenomicRanges_1.24.2 BiocInstaller_1.22.3 [9] GenomeInfoDb_1.8.3 IRanges_2.6.1 [11] S4Vectors_0.10.2 Biobase_2.32.0 [13] BiocGenerics_0.18.0 BiocParallel_1.6.3 Thanks! [[alternative HTML version deleted]] _______________________________________________ Bioc-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/bioc-devel