Usually, many studies did differential expression analysis in their microRNA or tasi-RNA transcriptomic studies using the method described in this paper (http://www.ncbi.nlm.nih.gov/pubmed/9331369).
But, a majority of them have no biological replicate or sequencing duplication. That is, differential expression analysis was performed between two single samples ......
So my question is what if biological replicates or sequencing duplications did exist? Is there some improved or optimization of the algorithms in the literature mentioned above? Even tools like DESeq or BaySeq are more suitable?
Thanks for any attention or suggestion!
Hi Leavy,
I consistently have used DESeq for a couple of small RNA differential expression studies. It accepts biological replicates and does not make any assumption about the type of data, except for that they are counts.
On the other hand, there is a compendium of tools called sRNAtoolbox (pubmed link attached) that uses a combination of three programs - DESeq, edgeR and NOISeq - to determine a consensus of differentially expressed small RNAs.
Hope this helps.
http://www.ncbi.nlm.nih.gov/pubmed/26019179
Thank you, SRNAtoolbox sounds really excellent. I'll try sRNAde of that. By the way, are you focusing on plant or animal small RNA？
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