edgeR and FDR values always equals 1
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@gordon-smyth
Last seen 54 minutes ago
WEHI, Melbourne, Australia
Hi Anton, This is the way the software is designed to behave when there is no differential expression between your groups. The software is telling you that there is no statistically significant differential expression. The reason for this result seems to be the enormously high values for the dispersions. The values you have (3.5 up to 7) are an order of magnitude higher than my lab has ever seen for RNA-seq or SAGE-seq data. This represents enormous inconsistency between your replicate samples, and suggests something might wrong with your data setup. Another curious fact is that all the putative differential expression is one direction, down in the INF group. To examine your data setup, you might try an MDS plot (plotMDS). This would show you if you have one or more outlier libraries, or if one or more libraries are mis-classified into groups. You might also explore your data using smear plots plotSmear() to get a better idea of what is happening. You must have some very unusual samples. To combat the fact that much of the differential expression is in one direction, you might try normalizing, calcNormFactors(). Best wishes Gordon > Message: 25 > Date: Thu, 11 Nov 2010 10:44:07 +0000 > From: A Gossner <a.gossner at="" ed.ac.uk=""> > To: bioconductor at stat.math.ethz.ch > Subject: [BioC] edgeR and FDR values always equals 1 > > Hi, > > While using edgeR to analysis my Tag-seq data, no matter which way I > analyse the data common or tagwise dispersion the FDR value is always 1. > Typical output is shown below; > >> d$prior.n > [1] 10 >> head(d$tagwise.dispersion) > [1] 4.360269 5.192625 5.006097 5.006097 3.960243 5.192625 >> summary(d$tagwise.dispersion) > Min. 1st Qu. Median Mean 3rd Qu. Max. > 3.511 4.665 5.006 4.926 5.193 7.240 >> d$common.dispersion > [1] 4.884378 >> prior.n <- estimateSmoothing(d) prior.n > [1] 3.575805e-05 >> >> de.tagwise <- exactTest(d, common.disp = FALSE) > Comparison of groups: INF - CON >> topTags(de.tagwise) > Comparison of groups: INF - CON > logConc logFC PValue FDR > CATGGGAACAATAAACTCCAC -17.88755 -10.968487 0.0004244306 1 > CATGTCTGCCCAAGCACCTAC -32.20325 -35.625605 0.0009657247 1 > CATGTTCCTGGTAGCACAAAT -18.89883 -9.075728 0.0011952265 1 > ATTGATGTTCTACACCACATG -32.92827 -34.175568 0.0014322637 1 > AAAAGGATGACTTCACTCATG -32.99637 -34.039364 0.0016256396 1 > CATGATGTGACTTTTAAGTCC -32.81141 -34.409298 0.0018494476 1 > AAACCCAGGGAAAGAAGCATG -32.98827 -34.055559 0.0018645461 1 > CTTTTTAGATCAAAAAGCATG -33.17368 -33.684744 0.0022498203 1 > CGGTCTTATTTAGGAGACATG -32.83447 -34.363162 0.0026414159 1 > CATGCTCTTTATCACACCCCC -33.05201 -33.928086 0.0027765733 1 >> sessionInfo() > R version 2.11.1 (2010-05-31) > x86_64-pc-mingw32 > > locale: > [1] LC_COLLATE=English_United Kingdom.1252 > [2] LC_CTYPE=English_United Kingdom.1252 > [3] LC_MONETARY=English_United Kingdom.1252 > [4] LC_NUMERIC=C > [5] LC_TIME=English_United Kingdom.1252 > > attached base packages: > [1] stats graphics grDevices utils datasets methods base > > other attached packages: > [1] edgeR_1.6.15 > > loaded via a namespace (and not attached): > [1] limma_3.4.5 > > Would be grateful for any suggestions? > > Regards > > Anton ______________________________________________________________________ The information in this email is confidential and intend...{{dropped:4}}
edgeR edgeR • 1.9k views
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