Re: st: Genome-wide associations in Stata

[David Airey <david.airey@Vanderbilt.Edu>]

.

I believe our Center for Human Genetics Research at the Vanderbilt  
School of Medicine piloted their GWAS (genome wide association study)  
efforts in Stata, but then ported to C++ and now that pipeline uses  
our parallel computing system (ACCRE). Statistical analyses in GWAS  
are very simple models, but the problem of housing and securing data  
for GWAS is not a desktop PC solution. Statistical analysis in GWAS  
lag the technology to gather the data, is one message.

There is no reason Stata cannot be used to analyze microarray data.  
I've done this and used Roger's smileplot in the process. I am at the  
moment starting a meta-analysis of microarray results, and Stata will  
work just fine for this. However, you will find no large cache of  
programs for microarray data analysis for Stata, like there is at  
Bioconductor.org for R. For this reason alone, you should consider  
knowing enough of R to make use of the packages on that site.

-Dave

On May 9, 2008, at 9:24 AM, tiago.pereira@incor.usp.br wrote:


> Dear statalister,
>
> Does anyone have experience in running genome-wide association  
> analyses in
> Stata?
>
> Toby Andrew has provied useful tips for genome-wide linkage  
> analysis, but
> I would like to know in more detail your current experience in running
> these sort of computer intensive stuff. I got frustrated with Stata
> regarding its complete lack of programs to analyze microarray data.  
> To put
> it bluntly, Should I forget using Stata in these high-throughput
> experiments from now on and rely on R only?
--
David C. Airey, Ph.D.
Pharmacology Research Assistant Professor
Center for Human Genetics Research Member
Vanderbilt University School of Medicine

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