[BioC] microarray analysis of a dose response * strain experiment

[Kimpel, Mark William]

Thanks Ana, I will take a look :)  Mark

Mark W. Kimpel MD 

 

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-----Original Message-----
From: Ana Conesa [mailto:aconesa at ivia.es] 
Sent: Saturday, November 04, 2006 4:04 PM
To: Kimpel, Mark William; sdavis2 at mail.nih.gov;
bioconductor at stat.math.ethz.ch
Cc: McBride, William J.
Subject: Re: [BioC] microarray analysis of a dose response * strain
experiment

Hi Mark

I recommend you to have a look to the maSigPro package and the
corresponding 
publication (Bioinformatics 2006 22(9):1096-1102). The methodology has
been 
designed for decting genes that change between experimental conditions
on a 
data series, normally this would be different treatments along the time 
component, but could also be different strains along a increasing dose 
value. You can model different type of responses (linear, quadratic or
more 
sophisticated) although the method finnaly finds the model most suited
for 
each gene. The method does not focus on pair-wise comparisons, but
rather 
detects differences in expression patterns between conditons (thus,
strain-
dose interactions) or genes that significantly change "somewhere".

I hope this package suits your analysis needs

Best regards

Ana

On Sat, 4 Nov 2006 14:45:37 -0500, Kimpel, Mark William wrote
> Sean,
> 
> Perhaps it will have to be, I can think of two ways to do that and
> neither seems entirely satisfactory. Firstly, one could assume that
the
> response (for responding genes) would be linearly related to the 
> dose or the log of the dose, but this might not be the case. So 
> regressing by dose in a linear model might not be correct for all or 
> even most of the affected genes. Secondly, one could simply assume 
> that the dose is a factor with 4 non-ordered levels and look at 
> contrasts and interactions for each level. This would be the 
> approach I am most familiar with using Limma. This would, however, 
> seem to be throwing information away regarding the relationship of 
> the doses to one another.
> 
> Mark
> 
> Mark W. Kimpel MD
> 
> (317) 490-5129 Work, & Mobile
> 
> (317) 663-0513 Home (no voice mail please)
> 
> 1-(317)-536-2730 FAX
> 
> -----Original Message-----
> From: Sean Davis [mailto:sdavis2 at mail.nih.gov] 
> Sent: Saturday, November 04, 2006 1:39 PM
> To: bioconductor at stat.math.ethz.ch
> Cc: Kimpel, Mark William; McBride, William J.
> Subject: Re: [BioC] microarray analysis of a dose response * strain
> experiment
> 
> On Saturday 04 November 2006 13:20, Kimpel, Mark William wrote:
> > My group is writing a grant with a proposed dose response experiment
> on two
> > different rat strains that I have been tasked to provide an analysis
> method
> > for. Briefly, we have two rat strains that have different
preferences
> for
> > alcohol (one drinks, the other doesn't). We are going to give each
> line
> > injections for alcohol to see if gene expression in the brain is
> > differentially affected between the 3 strains. We don't, however,
know
> > which of several possible doses of alcohol will provide the greatest
> effect
> > on each of the thousands of genes on our Affy chipset. So, we are
> proposing
> > to give each line one of 4 doses (zero, 0.5, 1.0, and 2.0 mg/kg).
For
> any
> > gene, we have no way of knowing a priori what shape the dose
response
> curve
> > will take. We are, for screening purposes, not really interested in
> the
> > shape of the curve, only that it is not a line with a slope of zero
> (i.e.
> > no response). We are also, for screening purposed, only interested
to
> know,
> > for each gene, if the response of strain A is different from strain
B.
> In
> > other words, what we want to know is the interaction between strain
> and
> > dose response.
> >
> > I have searched the literature and the Bioconductor mailing list and
> cannot
> > find a reference to an experiment of this sort. Can anyone provide
> some
> > advice?
> 
> This can't be handled with a linear model?
> 
> Sean
> 
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