[BioC] sample size for microarray experiments having 2 factors with one random effect

[shirley zhang]

Dear Dr. Altman,

Thanks for your quick response. Is the method you suggested similar to
what Dr. KEVIN DOBBIN and RICHARD SIMON proposed in Biostatistics
2005? (http://biostatistics.oxfordjournals.org/cgi/reprint/6/1/27)

Sorry that I did not make my experiment design clear.

There are 2 fixed effects (tissue and status). We got two different
tissues from the same patient. Patients are grouped into two category
based on their status. Here we are interested in finding genes
commonly changed by status across different tissue types.  We are
suggested to use lme function in nlme package by treating tissue and
status as fixed effects, and patient as random effect.  Is my
experiment still a randomized complete block design?

Thanks again for your help,
Shirley

On Thu, Apr 23, 2009 at 10:40 PM, Naomi Altman <naomi at stat.psu.edu> wrote:
> This appears to be a randomized complete block design.  The way I would
> compute the sample size is:
>
> Use a routine that computes sample size for a randomized complete block
> design.
> If you are planning to use log2 expression, then enter "1" as the size of
> the difference you want to detect.  That
> corresponds to 2-fold.
> Using someone else's data for the same experiment, compute the sd for each
> gene (e.g. using Limma).  Use the 70th or
> 80th percentile of SD as the SD for computing sample size.  (This will be
> somewhat anti-conservative, but software for RCB
> sample size will not include EBayes computations which boost the power for
> any sample size, which is like decreasing the SD.)
>
> Then just enter the p-value and power that you want.  Again, you might want
> to consider using a smaller p-value to adjust for multiple comparisons.
> If so, you could look at the q-value versus p-value plot for the data you
> used to compute SD, and pick the p-value corresponding to your desired
> q-value.
>
> The number of replicates in any experiment should be at least 3.  (Those of
> you working in the medical field will think this is ridiculously small, but
> in underfunded
> areas of biology we are happy if we have funds for more than 3 reps.)
>
> There is also software from uab.edu called PowerAtlas.  I haven't looked
> recently, but I think it is primarily for completely randomized designs.
>
> --Naomi
>
>
> At 10:09 PM 4/23/2009, shirley zhang wrote:
>>
>> Dear list,
>>
>> I have the following  affymetrix microarray experiment:
>>
>> 2 fixed effects, each factor has two levels
>> 1 random effect (patient)
>>
>> Can anybody tell me how to calculate the sample size for it?
>>
>> Thanks,
>> Shirley
>>
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>
> Naomi S. Altman                                814-865-3791 (voice)
> Associate Professor
> Dept. of Statistics                              814-863-7114 (fax)
> Penn State University                         814-865-1348 (Statistics)
> University Park, PA 16802-2111
>
>



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Xiaoling