can small rnaseq data be analyzed like rnaseq data?

[PFS]

Sorry if this is a dumb question.

I was wondering whether small rna-seq data can be analyzed with the standard software for rna-seq data such as TopHat, Cufflinks, DESeq, etc...

Are there differences in the pre-processing steps? We are interested in differential expression only.

Thanks!

[volks]

not really. depending on the read length also the 3' adapter is sequenced. you could use cutadapt for trimming.

since you dont expect splice junctions, you dont need TopHat for mapping. you could use BWA or bowtie instead.

the most tricky part is the post-processing of genomic alignments (identical sequences mapping to multiple miRNA genes, mapping to anti-sense strand in perfectly complementary mature and star sequence, to name a few). or you generate a reference database only consisting of miRNA precursors. but there are also published tools around.

i used DESeq and edgeR for differential expression analysis of miRNAs before.

[NicoBxl]

I'm using bowtie for alignment, IGV for visualisation and DESeq for DE analysis.

[Kennels]

Can anyone comment on the presence of PCR duplicates in sRNA datasets and how these are handled (if necessary at all) in these sorts of analyses?

I'm wondering if PCR duplication would be amplified by the fact that there are so many identical reads.

[volks]

there is no way to tell, as you have thousands of identical sequences starting from the same position.

if you are concerned about PCR bias you should do technical replicates.

[illuminaGA]

Sorry if this is a dumb question.

How should I choose the GFT file for small RNA seq analysis? Can I use the same gene annotation GFT for regular RNA-seq pipeline? Thank you in advance.