[BioC] Human Gene array data analysis workflow

[cstrato]

Dear Javier,

In principle every workflow for Exon arrays can also be applied to Gene 
arrays.

One more note:
In principle you could use package "xps" for all these steps:

- rma(.., exonlevel="core") will only use the core genes but not AFFX or 
control genes

- PreFilter(mad=c(0.5,0.01)) etc will eliminate all transcripts with low 
variability

For more details see e.g. example script "xps/examples/script4exon.R" 
which shows you the workflow for HuExon and HuGene arrays.

Best regards
Christian
_._._._._._._._._._._._._._._._._._
C.h.r.i.s.t.i.a.n S.t.r.a.t.o.w.a
V.i.e.n.n.a A.u.s.t.r.i.a
e.m.a.i.l: cstrato at aon.at
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On 4/28/11 7:50 PM, Javier Pérez Florido wrote:
> Dear list,
> A possible data analysis workflow for EXON arrays could be as follows
> (extracted from "Exon Array data analysis using Affymetrix Power Tools
> and R statistical software", Briefings in Bioinformatics):
>
>      * Normalization and summarization (at exon or gene-level) of the
>        array set.
>      * Quality control of exon array data of summarization results (to
>        remove possible outliers)
>      * Specific filtering steps, for example:
>            o Restrict analysis to core probesets
>            o Filter for undetected probesets (i.e., undetected exons),
>              making use of DABG (Detected above background) analysis.
>            o Filter for cross-hybridizing probesets (exons)
>            o Filter for genes undetected genes in all groups
>
>    I'm running a gene-level data analysis on Human GENE ST 1.0 (not EXON)
> arrays, which are, in principle, designed for gene expression profiling,
> that is, a gene-level analysis. My question is related to the filtering
> step. I was wondering if, once the normalization and summarization is
> run at the transcript level (core), giving 33297 transcripts, the
> following filtering can be run before differential expression analysis:
>
>      * Remove control transcripts such as other_spike, AFFX, pos_control
>        (normgene->exon) and neg_control (normgene->intron). This step
>        removes around 4156 transcripts
>      * Remove transcripts with very low variability through varFilter
>        function (genefilter package)
>
> Since these were the steps recommended in "Bioconductor case studies"
> book for 3'IVT arrays (the controls were different in 3'IVT), I was
> wondering if these 2 filtering steps can also be used on Human Gene
> arrays for gene-level analysis or, on the contrary, I have to run the
> filtering steps described above for EXON arrays.
> Thanks,
> Javier
> P.S. If you know any data analysis workflow document for HuGene arrays,
> please, let me know
>
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>
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