DeSeq2 independant filtering barely removes any genes
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mnaymik • 0
@mnaymik-13524
Last seen 23 months ago

I have a data set where I am comparing a few exposures to a basleine group. When I run Deseq on all of the groups it filters out about 20,000 of the 36,000 genes which is what I expect and has always been the case when running Deseq. However, for 1 of the contrasts only 200 genes get filtered out. Looking at the results table it looks like almost 15,000 genes that make it through have counts < 1. Does anyone know why the low counts filter would not be filtering here? 

 

 

out of 35599 with nonzero total read count

adjusted p-value < 0.1

LFC > 0 (up)     : 0, 0%

LFC < 0 (down)   : 0, 0%

outliers [1]     : 0, 0%

low counts [2]   : 205, 0.58%

(mean count < 0)

[1] see 'cooksCutoff' argument of ?results

[2] see 'independentFiltering' argument of ?results

 

[1] "Genes < 0.05:"

[1] 0

 

 

ensembl gene_name baseMean log2FoldChange lfcSE stat pvalue padj
ENSG00000090402 SI 0.025828054 0.264452178 4.618680726 0.057257081 0.954340408 0.99559156
ENSG00000161270 NPHS1 0.025828054 0.264452178 4.618680726 0.057257081 0.954340408 0.99559156
ENSG00000164113 ADAD1 0.025828054 0.264452178 4.618680726 0.057257081 0.954340408 0.99559156
ENSG00000165970 SLC6A5 0.025828054 0.264452178 4.618680726 0.057257081 0.954340408 0.99559156
ENSG00000166007 TRIM51HP 0.025828054 0.264452178 4.618680726 0.057257081 0.954340408 0.99559156
ENSG00000179452 RP11-380B22.1 0.025828054 0.264452178 4.618680726 0.057257081 0.954340408 0.99559156

 

 

deseq2 differential gene expression filtering • 266 views
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Entering edit mode
@mikelove
Last seen 1 day ago
United States

The filtering is an optimization based on how much power is gained by filtering at a certain threshold. If users have many pairs to compare it may be more consistent to pick a common threshold and set independentFiltering=FALSE. You can filter at the beginning based on mean of normalized counts.

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