Hi, Thanh,
If your primary goal is inference about differential 'gene' expression
taking biological variability into account with biological replicates for
each of two conditions, you might want (eg see Dillies et al.,
http://bib.oxfordjournals.org/content/early/2012/09/15/bib.bbs046.long and
http://wiki.galaxyproject.org/Events/GCC2013/Abstracts#Events.2FGCC2013.2FAbstracts.2FPosters.P4:_Comparing_R-based_methods_and_Cuffdiff2_for_analysis_of_RNA-seq_data_in_Galaxy)
to try (and compare!) edgeR (and optionally DESeq and VOOM/limma). A set of
*very much beta* tools is available for admin installation and user testing
from the test toolshed in the statistics section owned by fubar.

The edgeR tool can optionally run 2 way GLM. It requires raw count matrices
as inputs which can be generated from a GTF/'gene' model of your choice and
any number of mapped SAM/BAM inputs using the htseq based companion tool in
the same tool shed section. Please don't install to a production machine
yet but we're getting good results from it - feedback and code improvements
are welcomed from willing beta testers.

The R 3.0.x tool shed dependency package in particular is still under
development and is likely to change substantially in the next week or two
as we sort out a sane and generalised Atlas dependency installation.


On Fri, Jul 19, 2013 at 2:55 AM, Hoang, Thanh <hoan...@miamioh.edu> wrote:

> Hi all,
> I have been analyzing my RNA-seq data on mouse tissues. My RNA-data is
> single-ended and 51 bp in length. I ran TopHat/Cufflink/Cuffdiff to test to
> differential gene expression
> In the Cuffdiff's output, I got very high RPKM value for some of miRNA and
> some other short genes ( less than 100bp). These genes are in the top genes
> with the highest RPKM. I think the RPKM values of these genes are probably
>  too high to be true.
>   *test_id* *gene_id* *gene* *locus* *sample_1* *sample_2* *status* *
> value_1* *value_2* *log2(fold_change)* *test_stat* *p_value* *q_value* *
> significant*  *ENSMUSG00000093077* *ENSMUSG00000093077* *Mir5105* *
> 5:146231229-146302874* *Epithelium* *Fiber* *OK* *1.53E+06* *  445558* *
> -1.78097* *-355.367* *0.00715* *0.016986* *yes*  *ENSMUSG00000093098* *
> ENSMUSG00000093098* *Gm22641* *7:130162450-133124354* *Epithelium* *Fiber*
> *OK* *87894.1* * 36474.7* *-1.26887* *-0.59863* *0.4913* *0.587174* *no*
> *ENSMUSG00000089855* *ENSMUSG00000089855* *Gm15662* *
> 10:105187662-105583874* *Epithelium* *Fiber* *OK* *42868.9* * 21566.5* *
> -0.99114* *-20.7066* *0.0186* *0.039568* *yes*  *ENSMUSG00000092984* *
> ENSMUSG00000092984* *Mir5115* *2:73012853-73012927* *Epithelium* *Fiber* *
> OK* *21104.8* * 8317.49* *-1.34335* *-447.314* *0.0001* *0.000354* *yes*
> *ENSMUSG00000086324* *ENSMUSG00000086324* *Gm15564* *16:35926510-36037131*
> *Epithelium* *Fiber* *OK* *6443.35* * 3664.15* *-0.81433* *-1.52095* *
> 0.2129* *0.301429* *no*  *ENSMUSG00000092981* *ENSMUSG00000092981* *
> Mir5125* *17:23803186-23824739* *Epithelium* *Fiber* *OK* *5974.14* *
> 2390.75* *-1.32127* *-0.34111* *0.5746* *0.661937* *no*
>
>  I checked some forums and they said that this is the drawback of
> TopHat/Cufflink/Cuffdiff when dealing with short genes. But I am still not
> so clear about this. Anyone got the same problem? What can I do with this
> situation?
> Anyone suggests any other good tools to test for (1) differential gene
> expression OR (2) both differential gene expression and gene discovery?
>
> Thank you
> Thanh
>
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