[BioC] DEXSeq for 1 gene

Wolfgang Huber whuber at embl.de
Sun May 26 14:12:16 CEST 2013


Dear Eamonn

from your initial post -i.e. the output of head(counts(ecs))- it looks like your counts are very low? This would make estimateSizeFactors produce lots of NA values, but even if it did not, it would mean that you'd have essentially no statistical power to detect anything useful from such low counts.

You mentioned "20 bumblebee samples" but the table whose head you show only has 9?

Can you post the full output of 'counts(ecs)' and make sure its content is plausible based on your understanding of the data?

	Best wishes
	Wolfgang

 
On May 23, 2013, at 2:03 pm, Eamonn Mallon <ebm3 at leicester.ac.uk> wrote:

> Hi Alejandro,
> Thanks very much for getting back to me.
> 
> I think I got the second parameter idea from DESeq. I see I am wrong. so I ran
> 
> > ecs<-estimateSizeFactors(ecs)
> > sizeFactors(ecs)
> K61 K62 K63 K83 Q61 Q62 Q63 Q81 Q82
> NA  NA  NA  NA  NA  NA  NA  NA  NA
> 
> Is there any way to get DEXSeq to estimate size factors with my small dataset?
> 
> If you are only interested in a single gene maybe you could visualize
> directly the counts per exon using the function plotDEXSeq.
> 
> I'm not sure how to do this I tried
> 
> >plotDEXSeq(ecs,"XLOC_000001", fitExpToVar="condition", norCounts=FALSE, expression=FALSE, splicing=FALSE, displayTranscripts=FALSE, legend=TRUE)
> 
> Error in plotDEXSeq(ecs, "XLOC_000001", fitExpToVar = "condition", norCounts = FALSE,  :
>  Please estimate sizeFactors first
> 
> I guess this is because modelFrameForGene requires sizefactors.
> 
> Any ideas?
> 
> Eamonn
> 
> 
> On 22/05/13 18:07, Alejandro Reyes wrote:
>> Dear Eamonn,
>> 
>> Thanks for your interest in DEXSeq.
>> 
>> In your size factor estimation, where did you get your second parameter
>> from? (check ?estimateSizeFactors) There is no need to specify anything
>> else than the ExonCountSet object and that is the reason you are getting
>> the error message.
>> 
>> If you are only interested in a single gene maybe you could visualize
>> directly the counts per exon using the function plotDEXSeq.
>> 
>> Best regards,
>> Alejandro Reyes
>> 
>> 
>>> Dear All,
>>> I have RNA-seq data for 20 bumblebee samples divided into treatment and control. I am interested in differential exon usage. Unfortunately the bumblebee genome is not at the stage where I can do a complete DEXSeq analysis genome wide. I decided to look at a single gene where I have a decent gene model. Using TopHat2 and the python scripts included in DEXSeq I was able to produce an ExonCountSet object.
>>> 
>>>> head(counts(ecs))
>>>                   K61 K62 K63 K83 Q61 Q62 Q63 Q81 Q82
>>> XLOC_000001:E001   1   0   1   0   1   0   0   0   0
>>> XLOC_000001:E002   1   0   0   0   2   1   0   1   1
>>> XLOC_000001:E003   0   0   0   0   3   0   0   0   0
>>> XLOC_000001:E004   1   0   1   0   1   0   0   1   0
>>> XLOC_000001:E005   1   3   3   2   3   0   0   0   0
>>> XLOC_000001:E006   0   0   0   0   0   0   0   0   0
>>> 
>>> As I expected, its all come crashing down round my ears at the analysis stage
>>> 
>>>> sizeFactors(ecs)
>>> K61 K62 K63 K83 Q61 Q62 Q63 Q81 Q82
>>>   NA  NA  NA  NA  NA  NA  NA  NA  NA
>>> 
>>> I tried using the shorth value
>>> 
>>>> ecs<-estimateSizeFactors(ecs,(locfunc=genefilter::shorth((counts(ecs)),tie.action="min")))
>>> Error in .local(object, ...) : unused argument (0.2)
>>> 
>>> I understand that my main problem is that the DEXSeq analysis should be genome wide (my data has too few counts).
>>> 
>>> Is there a way to use DEXSeq to ONLY look at a single gene? If not can anyone think of a statistical way to analyse my data (cross tabs? How should I normalise?)
>>> 
>>> Thanks for your time
>>> 
>>> Eamonn
>>> 
>>> 
>>>> sessionInfo()
>>> R version 3.0.0 (2013-04-03)
>>> Platform: x86_64-apple-darwin10.8.0 (64-bit)
>>> 
>>> locale:
>>> [1] en_GB.UTF-8/en_GB.UTF-8/en_GB.UTF-8/C/en_GB.UTF-8/en_GB.UTF-8
>>> 
>>> attached base packages:
>>> [1] parallel  stats     graphics  grDevices utils     datasets  methods   base
>>> 
>>> other attached packages:
>>> [1] genefilter_1.42.0  DEXSeq_1.6.0       Biobase_2.20.0     BiocGenerics_0.6.0
>>> 
>>> loaded via a namespace (and not attached):
>>>   [1] annotate_1.38.0      AnnotationDbi_1.22.5 biomaRt_2.16.0       Biostrings_2.28.0    bitops_1.0-5         DBI_0.2-7
>>>   [7] GenomicRanges_1.12.3 hwriter_1.3          IRanges_1.18.1       RCurl_1.95-4.1       Rsamtools_1.12.3     RSQLite_0.11.3
>>> [13] splines_3.0.0        statmod_1.4.17       stats4_3.0.0         stringr_0.6.2        survival_2.37-4      tools_3.0.0
>>> [19] XML_3.95-0.2         xtable_1.7-1         zlibbioc_1.6.0
>>> Dr Eamonn Mallon
>>> Lecturer in Evolutionary Biology
>>> Adrian 220
>>> Biology Department
>>> University of Leicester
>>> 
>>> http://www2.le.ac.uk/departments/biology/people/mallon
>>> 
>>> 
>>> 	[[alternative HTML version deleted]]
>>> 
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