[BioC] multiple comparisons followed by multiple tests

[Richard Friedman]

Dear Matt and other Bioconductor Users:
On Jul 21, 2004, at 9:56 AM, Matthew Hannah wrote:

> I would look at the Limma help pages as this allows Lm fitting and the
> specification of multiple comparisons and also P value correction by 
> fdr
> (although I think this is only after ebayes mod of t-stats?).
>
> As for the replication if you have less than 3 reps per treatment then
> you are obviously wasting your time. Also if they are just technical 
> reps
> rather than true biological reps then any statistical analysis will be
> misleading due to the underestimate of biological variability. You also
> don't mention what type of data (affy or cDNA) or the general design
> which may allow people to offer more detailed advice.
> You also don't mention the starting point data - for example if it's 
> affy
> data are the signal values from MAS5 or have you looked into using RMA 
> or
> GCRMA as a low-level normalisation?

Thank you for your help. I phrased my questions generally, but will now
be more specific, if that affects the answers.
The data is Affy data. I normalized it with RMA.
I agree with you that between 1-3 technical replicates is not optimal.
I didn't design the experiments. I was just given them to analyze
  after they were performed. The experimentalist with whom I am working 
is
prepared to perform a limited number of PCR confirmatory experiments.
I will encourage him to do more experiments, but he wants to see what 
can be
learned from the present dataset first.
The experiment is to detect the effect of a knockout on the ability of
cells to respond to different mutagens. So I am planning on comparing:


1. wild-type exposed to mutagen (1 technical replicate)  vs. wildtype 
no treatment (3 technical replicates).
2. knockout no treatment (2 technical replicates) vs. wildtype 
no-treatmen (3 technical replicates).
3. knockout exposed to mutagen (1 technical replicate) - wildtype 
exposed to mutagen (1 technical replicate).
4. (knockout exposed to mutagen  (1 technical replicate) - wildtype 
exposed to mutagen)(1 technical replicate). -
      (knockout no treatment  (2 technical replicates) - wildtype no 
treatment (3 technical replicates)).

  My question is; Given the small number of replicates, should I ignore 
statistical analysis altogether and merely
proceed with fold changes.

Thanks and best wishes,
Rich

>
> HTH,
> Matt
>
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------------------------------------------------------------
Richard A. Friedman, PhD
Associate Research Scientist
Herbert Irving Comprehensive Cancer Center
Oncoinformatics Core
Lecturer
Department of Biomedical Informatics
Box 95, Room 130BB or P&S 1-420C
Columbia University Medical Center
630 W. 168th St.
New York, NY 10032
(212)305-6901 (5-6901) (voice)
friedman at cancercenter.columbia.edu
http://cancercenter.columbia.edu/~friedman/


"What is the breakfast all those people ate on Bloomsday?"
-Rose Friedman, age 8

In Memoriam, Tim O'Connor