[BioC] Theoretical Question

[Naomi Altman]

I am not sure who is responsible for the bioconductor web page, but I would 
find it useful to have these supporting papers listed on the web page along 
with the Release Packages.

Thanks,
Naomi

At 10:32 AM 6/1/2004 -0400, James MacDonald wrote:
>Naomi,
>
>The limma package fits an ANOVA with an adjusted denominator, based on an 
>empirical Bayes procedure. Literature describing the procedure can be 
>found here: http://www.statsci.org/smyth/pubs/ebayes.pdf
>
>Best,
>
>Jim
>
>
>
>James W. MacDonald
>Affymetrix and cDNA Microarray Core
>University of Michigan Cancer Center
>1500 E. Medical Center Drive
>7410 CCGC
>Ann Arbor MI 48109
>734-647-5623
>
> >>> Naomi Altman <naomi at stat.psu.edu> 05/30/04 12:25AM >>>
>I would use ANOVA  (lm or lme) followed by a contrast.  It would likely be
>better to adjust the denominator (like SAM) but I don't think there is any
>software for this (or literature on exactly how to do it).  So, probably
>the best thing for now is to treat this as a 1-way ANOVA with say a
>Bonferroni correction (for each gene). Once you have the
>Bonferroni-corrected p-values, you use FDR to determine an appropriate
>p-value to select genes.
>
>--Naomi
>
>At 02:10 PM 5/19/2004 -0400, Luckey, John wrote:
> >I posted a similar question last week and received some help with this
> >problem, but I am still a bit unclear on the best way to proceed- any
> >insights would be greatly appreciated.
> >
> >I want to identify a set of genes that are co-regulated with a given
> >phenotype that is observed across various tissue types -to ID the
> >'signature' that corresponds to the phenotype regardless of tissue-
> >
> >
> >
> >Here is the simplest set up: (all data is affymetrix and has been
> >pre-processed/normalized by rma)
> >
> >
> >
> >Tissue type A has 3 conditions: 1A, 2A, 3A
> >
> >Type B has 4 conditions: 1B, 2B, 3B, 4B
> >
> >
> >
> >My phenotype of interest is observed only in 1A and 1B.
> >
> >
> >
> >I am interested in knowing what is common (both up and down regulated)
> >between 1A (relative only to 2A and 3A) and 1B (relative to 2B, 3B, and
> >4B).  I have varying numbers of replicates per condition (2-5).
> >
> >
> >
> >I have done unsupervised clustering using all genes, and 1A and 1B don't
> >cluster together (not really surprising since they are quite different in
> >many respects , I am interested only in their overlapping phenotypes). I
> >am not entirely sure how best to proceed.
> >
> >
> >
> >I have used straight fold change to ID unique genes in 1A vs 2A and 1A vs
> >3A. I then select those genes up (or down) in 1A in both comparisons. I
> >then look at how the *€~1A specific*€™ genes are expressed in 1B vs all
> >other B's- and there is a general positive skewing- but the concern is
> >where to draw cutoffs- how to estimate FDR, etc in such a comparison.
> >Basically, how does one go about saying that the skewing in a different
> >comparison of a subset of genes is significant?
> >
> >
> >
> >Any insights you might have would be appreciated.
> >
> >
> >
> >Thx
> >
> >
> >
> >
> >
> >John Luckey, MD PhD
> >
> >Clinical Pathology Resident - Brigham and Womens Hospital
> >
> >Post Doctoral Fellow  -          Mathis - Benoist Lab
> >
> >Joslin Diabetes Center
> >
> >One Joslin Place, Rm. 474
> >
> >Boston, MA  02215
> >
> >_______________________________________________
> >Bioconductor mailing list
> >Bioconductor at stat.math.ethz.ch
> >https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor
>
>Naomi S. Altman                                814-865-3791 (voice)
>Associate Professor
>Bioinformatics Consulting Center
>Dept. of Statistics                              814-863-7114 (fax)
>Penn State University                         814-865-1348 (Statistics)
>University Park, PA 16802-2111
>
>_______________________________________________
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Naomi S. Altman                                814-865-3791 (voice)
Associate Professor
Bioinformatics Consulting Center
Dept. of Statistics                              814-863-7114 (fax)
Penn State University                         814-865-1348 (Statistics)
University Park, PA 16802-2111