[BioC] Small RNA seq data analysis using DESeq

Simon Anders anders at embl.de
Thu Jun 20 19:11:06 CEST 2013

Hi Vedran

 > I have a question regarding the analysis of small RNAseq data using 
 > While counting the reads per loci I have weighted the reads by the
 > reciprocal of the places to which the read maps.
 > I was wondering whether it is still proper to use the negative binomial
 > test implemented in DESeq (after rounding the expression estimates) to
 > determine which loci are differentially expressed?

No, for two reason:

1. DESeq expects raw counts. Your weighting violates the assumptions 
behind the nehative-binomial model.

2. Imagine two of your loci are quite similar, such that most reads that 
map to locus A also map to locus B. Further, imagine that you compare 
treated samples to control ones, and locus A gets upregulated in 
response to the treatment while locus B is unaffected. With your method 
of summerizing the data, all the additional reads that the upregulated 
locus A produces in the treatment samples will also be counted for locus 
B, and hence, you will wrongly conclude that both loci react to the 

Note that the second issue is a problem not only to NB-based method, but 
rather shows that you approach is in general not suitable for 
differential expression analyses.


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