Hi Meena,
I think in this instance you probably need to do some reshaping of your data.
My guess is that you have some outcome (event, which is presumably
binary) which you would like to regress the SNPs onto accounting for
environmental/phenotypic co-variates.
You'll probably want a command along the lines of....
xi: logistic event i.snp1 i.snp2 x1 x2
where event is the binary outcome, and the SNPs have been encoded to 0
(00), 1 (01), 2 (11). As with all regression models you can look at
interactions between terms in this model.
Your data would look like...
id event snp1 snp2 x1 x2
1 0 0 1 a a
2 1 1 1 b b
The logistic cluster option would be appropriate if your cases and
controls have been matched on an additional trait such as age or sex
(in which case you would add -, cluster(age)- to the above command).
More on this is given in the book Clayton & Hills (1993) "Statistical
Models in Epidemiology" OUP (I don't have it to hand, but I think its
chapter 29).
You may find some of the information on my website (URL below) of some
use. Its a little disorganised (I'm going to try and work on that in
due course, and perhaps write something up as a paper).
HTH's
Neil
--
"Every great advance in natural knowledge has involved the absolute
rejection of authority." - Thomas H. Huxley
Email - [email protected] / [email protected]
Website - http://slack.ser.man.ac.uk/
Photos - http://www.flickr.com/photos/slackline/
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