sample() takes a prob = argument which lets you supply weights, which
need not sum to one so, if I understand you, you could just pass TRUEs
and FALSEs for those rows you want. If I'm wrong about that last bit,
I'm still pretty confident sample(prob = ) is the way to go.
Best,
Michael
On Thu, Jun 14, 2012 at 6:02 AM, Guido Leoni <guido.leoni at gmail.com>
wrote:> Dear list I wish to extract from a population genotypized for 10 SNP a
> subsample of the same population of size n with similar allele frequencies.
> Essentially i have a matrix of 200 rows (df) like this
> Name,Condition,rs1385699_X,rs6625163_X,rs962458_X,Rs4658627_1,
> sample01,Case,1,1,1,-1
> sample02,Control,1,1,1,1
> sample06,Control,1,-1,1,0
> sample10,Case,1,1,1,0
> sample11,Control,1,1,1,1
> sample24,Control,-1,-1,1,0
> sample29,Control,1,-1,1,0
> sample42,Case,-1,-1,1,0
> sample64,Case,-1,1,1,0
> ....
> I'm interested to mantain in my subsample the same frequencies of those
> observed for the 1 value in each column
> I approached the problem with sample() function
>
> mysample<-df[sample(1:nrow(df),100,replace=F),]
> Then I tested that ?the frequencies of each allele in mysample are not
> statistically different respect to the initial dataset by mean of prop.test
> This seems to work but do you know if there is a package that can do the
> same thing ?allowing for example a more strict control?
> Thank you very much
> Guido
>
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