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delhomme@embl.de
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@delhommeemblde-3232
Last seen 10.2 years ago
Hi Meritxell,
I've Cced the Bioc Mailing list in case this is of interest to others.
On Oct 11, 2012, at 6:15 PM, Meritxell Oliva wrote:
> Hi Nicolas,
>
> I am an easyRNASeq "newbie" user.
>
> First of all, congratulations for the development of the pipeline:
so far it's one of the best R libraries I have found to deal with
RNASeq data, as it tries to tackle problematic issues such as unique
read-exon count assignment and also wraps the normalization packages
(DESeq, edgeR), so you get all you need in one go. Thanks!
>
Thanks, that's nice to hear. Let me know as well whenever your
encounter problems of think of new features!
> I do have a question: I would like to create a non-redundant,
synthetic exon dataset, using the Ensembl68 gene models. From what I
understand from the manual, when using easyRNASeq() if you summarize
your counts by counts=gene,summarization=geneModels, this synthetic
exon dataset is generated in order to create unique read-exon
correspondances. This is what I do, and I store the object as RNASeq
object, to preserve the genomic annotation. However, the annotation
that I get if I apply the function genomicAnnotation() to this object,
is the original one from Ensembl, with redundant exons shared between
transcripts. I would like to get the synthetic exon dataset, to select
unique coding regions for each gene transcript.
>
> How can I get this dataset? My ultimate goal is to perform gene
expression differential analysis at gene, transcript and exon level.
First one is solved, and I want to find the best way to do perform the
latter ones.
>
At the moment it's still a dual step process, but I plan on making
that easier. You first need to run
easyRNASeq(counts=gene,summarization=geneModels,etc...) and asking to
get an "RNAseq" outputFormat: rnaSeq <- easyRNASeq(counts=gene,summari
zation=geneModels,outputFormat="RNAseq",etc...). This will give you an
object of the class RNAseq that contains the geneModel annotation
accessible through geneModel(rnaSeq). That's a RangedData object
containing the synthetic exon, although it is still redundant for
genes located on opposite strands. So if you're not using stranded
RNAseq data, you need to do some more filtering.
> Can you help me?
>
Hope this did, let me know if not,
Nico
> Thanks
>
>
> Meritxell Oliva
> PhD student
> IBB (Biotechnology and Biomedicine Institute)
> Comparative and Functional Genomics group
> Campus Universitari - 08193 Bellaterra Cerdanyola del Vall?s -
Barcelona
>
>
>
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