[BioC] (no subject)
James W. MacDonald
jmacdon at med.umich.edu
Tue Jul 12 15:53:05 CEST 2005
I don't think this idea makes much sense scientifically for at least two
reasons, and probably more.
1.) How exactly will you distinguish genes that are expressed from those
that are not expressed? Note that in canonical microarray analyses
nobody is claiming that a certain gene is expressed or not, only that it
is expressed at a different level in one sample vs another.
2.) If you could somehow accurately determine which genes are being
expressed, of what use is that information? When you are comparing two
samples, you know phenotypically what the differences are, so you can
attribute (rightly or wrongly) the differences in expression to that
phenotypic difference. If you are just looking at e.g., normal liver and
you find 5000 genes that are expressed, how do you attribute those genes
to any phenotype or process (other than to note the trivial result that
the liver appears to express these 5000 genes)?
Marta Agudo wrote:
> Hi there
> I´ve been thinking about gene expression in just one condition without
> comparing to anything else.
> I explain better: I have data from an affy array experiment using naive
> tissue RNA, and I want to know which genes, out of the 30000 present in the
> chip, are being expressed in this tissue.
> I would like to know is this analysis is possible, i mean not just
> statistically but also if scientifically has any sense,
> And if it is I would need some help
> a) is it possible to use bioconductor and GCRMA analysis ? then, anyone
> knows a script or could guide me?
> b) how many replicas do we need?
> c) which is the cut off point?
> Basically which are the pros and the cons of this kind of analysis?
> thank you very much!
> Marta Agudo PhD
> Departamento de Oftalmología
> Facultad de Medicina
> Campus Espinardo
> 30100 Murcia- Spain
> Phone:+34 968363996
> [[alternative HTML version deleted]]
> Bioconductor mailing list
> Bioconductor at stat.math.ethz.ch
James W. MacDonald
Affymetrix and cDNA Microarray Core
University of Michigan Cancer Center
1500 E. Medical Center Drive
Ann Arbor MI 48109
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