question about how to understand exon usage coefficient value
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Ou, Jianhong ★ 1.3k
@ou-jianhong-4539
Last seen 19 hours ago
United States
Hi Alejandro, I am using DEXSeq to analysis alternative splicing events of my knockdown samples. DEXSeq is very easy to use. However, I have some trouble in understanding the results. The question is why some of the log2fold change of the KD vs WT is opposite with the raw counts. For example the E012 in the following sample (attached please find the figures of expression and normalized counts): groupID featureID exonBaseMean dispersion stat pvalue padj KD NS log2fold_KD_NS ENSG00000171603:E012 ENSG00000171603 E012 255.50 0.0009438170 2.347679e+02 5.439942e-53 7.353639e-50 36.9088539 20.20013887 0.869601727 genomicData.seqnames genomicData.start genomicData.end genomicData.width genomicData.strand countData.NSrep1 countData.NSrep2 ENSG00000171603:E012 chr1 9797556 9797612 57 - 377 372 countData.KDrep1 countData.KDrep2 transcripts ENSG00000171603:E012 147 126 ENST0000.... Thank you for your help. The codes I used is , > countFiles [1] "NS-1.nodenovo.counts" "NS-2.nodenovo.counts" "KD-1.nodenovo.counts" "KD-2.nodenovo.counts" > sampleTable <- data.frame(row.names=c("NSrep1", "NSrep2", "KDrep1", "KDrep2"), condition=c("NS", "NS", "KD", "KD")) > sampleTable condition NSrep1 NS NSrep2 NS KDrep1 KD KDrep2 KD > dxd <- DEXSeqDataSetFromHTSeq(countFiles, sampleData=sampleTable, design=~sample+exon+condition:exon, flattenedfile=gffFile) > dxr <- DEXSeq(dxd) The sessionInfo is, R version 3.1.0 (2014-04-10) Platform: x86_64-apple-darwin12.5.0 (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] grid parallel stats graphics grDevices utils datasets methods base other attached packages: [1] biomaRt_2.20.0 Vennerable_3.0 xtable_1.7-3 gtools_3.4.0 reshape_0.8.5 RColorBrewer_1.0-5 [7] lattice_0.20-29 RBGL_1.40.0 graph_1.42.0 DEXSeq_1.10.3 BiocParallel_0.6.0 DESeq2_1.4.5 [13] RcppArmadillo_0.4.300.0 Rcpp_0.11.1 GenomicRanges_1.16.3 GenomeInfoDb_1.0.2 IRanges_1.22.6 Biobase_2.24.0 [19] BiocGenerics_0.10.0 loaded via a namespace (and not attached): [1] annotate_1.42.0 AnnotationDbi_1.26.0 BatchJobs_1.2 BBmisc_1.6 Biostrings_2.32.0 bitops_1.0-6 brew_1.0-6 [8] codetools_0.2-8 DBI_0.2-7 digest_0.6.4 fail_1.2 foreach_1.4.2 genefilter_1.46.1 geneplotter_1.42.0 [15] hwriter_1.3 iterators_1.0.7 locfit_1.5-9.1 plyr_1.8.1 RCurl_1.95-4.1 Rsamtools_1.16.0 RSQLite_0.11.4 [22] sendmailR_1.1-2 splines_3.1.0 statmod_1.4.19 stats4_3.1.0 stringr_0.6.2 survival_2.37-7 tools_3.1.0 [29] XML_3.98-1.1 XVector_0.4.0 zlibbioc_1.10.0 Yours Sincerely, Jianhong Ou LRB 670A Program in Gene Function and Expression 364 Plantation Street Worcester, MA 01605 -------------- next part -------------- A non-text attachment was scrubbed... Name: exp.CLSTN1.pdf Type: application/pdf Size: 8795 bytes Desc: exp.CLSTN1.pdf URL: <https: stat.ethz.ch="" pipermail="" bioconductor="" attachments="" 20140529="" c7067163="" attachment.pdf=""> -------------- next part -------------- A non-text attachment was scrubbed... Name: norCounts.CLSTN1.pdf Type: application/pdf Size: 9558 bytes Desc: norCounts.CLSTN1.pdf URL: <https: stat.ethz.ch="" pipermail="" bioconductor="" attachments="" 20140529="" c7067163="" attachment-0001.pdf="">
DEXSeq DEXSeq • 1.1k views
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