[BioC] easyRNASeq for miRNA read counts

Nicolas Delhomme delhomme at embl.de
Mon Nov 18 13:49:52 CET 2013

Hej Vicky!

The very short answer is that  it depends on the content of your annotation. I can’t really tell you more without knowing more about the kind of data you want to provide as input to easyRNASeq, both for the read alignments and as annotation. In my view of things using “features” would be the more appropriate, but that’s just a name. If you define mono-exonic transcript and use “transcripts”, the results would be the same.

Now, with regards to miRNA, I assume that easyRNASeq could get you a count table, but the seldom time I’ve worked with miRNA, I directly got an occurrence count table as output, e.g. form the UEA workbench. If you would detail ab it more your data processing, I could tell you more accurately if there would be any caveats in using easyRNASeq for that.

Finally, I’ve never - so far - tried a differential analysis approach with miRNA data, and I would think that DESeq, DESeq2, edgeR, etc.. are valid tools for that but maybe others from the list can chime in? 



Nicolas Delhomme

Genome Biology Computational Support

European Molecular Biology Laboratory

Tel: +49 6221 387 8310
Email: nicolas.delhomme at embl.de
Meyerhofstrasse 1 - Postfach 10.2209
69102 Heidelberg, Germany

On 18 Nov 2013, at 05:12, Vicky Chu [guest] <guest at bioconductor.org> wrote:

> Hi, 
> I am looking to use DESeq to analyze my 18-29 nt small RNA libraries. Is it appropriate to prepare a  countDataSet that counts "transcripts" , or possibly "features" in this case? What do you recommend? 
> Thank you! 
> -- output of sessionInfo(): 
> sessionInfo() 
> R version 3.0.2 (2013-09-25)
> Platform: x86_64-apple-darwin10.8.0 (64-bit)
> locale:
> [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
> attached base packages:
> [1] parallel  stats     graphics  grDevices utils     datasets  methods   base     
> other attached packages:
> [1] easyRNASeq_1.8.1       ShortRead_1.20.0       Rsamtools_1.14.1       GenomicRanges_1.14.3  
> [5] DESeq_1.14.0           lattice_0.20-24        locfit_1.5-9.1         Biostrings_2.30.1     
> [9] XVector_0.2.0          IRanges_1.20.5         edgeR_3.4.0            limma_3.18.3          
> [13] biomaRt_2.18.0         Biobase_2.22.0         genomeIntervals_1.18.0 BiocGenerics_0.8.0    
> [17] intervals_0.14.0      
> loaded via a namespace (and not attached):
> [1] annotate_1.40.0      AnnotationDbi_1.24.0 bitops_1.0-6         DBI_0.2-7           
> [5] genefilter_1.44.0    geneplotter_1.40.0   grid_3.0.2           hwriter_1.3         
> [9] latticeExtra_0.6-26  LSD_2.5              RColorBrewer_1.0-5   RCurl_1.95-4.1      
> [13] RSQLite_0.11.4       splines_3.0.2        stats4_3.0.2         survival_2.37-4     
> [17] tools_3.0.2          XML_3.95-0.2         xtable_1.7-1         zlibbioc_1.8.0      
> --
> Sent via the guest posting facility at bioconductor.org.

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