[BioC] edgeR and FDR values always equals 1

Gordon K Smyth smyth at wehi.EDU.AU
Thu Nov 11 23:34:41 CET 2010


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

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