User: Sam
Sam • 2.4k
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Posts by Sam
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... Given your tag and your sample size, are you trying to perform PRS analysis on UK biobank data? You can definitely run an analysis on this sample size using the common PRS software such as [PRSice][1], [lassosum][2] and [LDpred][3].
[1]: http://www.prsice.info/
[2]: https://github.com/tshmak/ ...
written 3 days ago by
Sam • 2.4k
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Comment:
C: WGCNA Different Module Results
... I'm not sure. But from the glance of it, those two codes are using two different method (tree vs hybrid). So I am not surprise that they generate a different result ...
written 15 days ago by
Sam • 2.4k
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... One of the step of WGCNA involves hierachical clustering, which is partially random. Unless you've set the random seed before each run, you'd expect to see slight difference in the number of modules, module size and module membership, especially when your sample size is relatively small ...
written 16 days ago by
Sam • 2.4k
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Answer:
C: polygenic risk score
... It might be best if you open a separate question for this. But in short, if you are looking for a pure R package for PRS, then you can use [lassosum][1]. Alternatively, you can always use PRSice and LDpred, which are the other PRS software, though they are not written in R (PRSice is technically a C ...
written 17 days ago by
Sam • 2.4k
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... I am not sure what you meant by "adjust for phenotype". Maybe you want to elaborate a bit more? We almost always use logistic regression for binary traits and we can adjust for covariates using the logistic regression model. ...
written 17 days ago by
Sam • 2.4k
1
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... The covariate should only affects the parameter optimization part of PRS calculation, but not for the actual PRS calculation. If you look at your equation carefully, you will note that the PRS is only determined by the beta obtained from the summary statistics and the genotype of the individual with ...
written 20 days ago by
Sam • 2.4k
0
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1
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190
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... Yes, there's a typo. Have now updated the code ...
written 22 days ago by
Sam • 2.4k
0
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1
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190
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... Opps, I thought the message didn't sent (accidentally click back), didn't realize it was sent out.
Sorry about that. Will now try to complete it. ...
written 22 days ago by
Sam • 2.4k
0
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1
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... In R, assume your data is stored in a data.frame call dat
dat$Group <- 1
counter<-0
prev.chr <- NA
prev.loc <- 0
sub.count <- 0.1
for(i in 1:nrow(dat)){
if ( is.na(prev.chr) | prev.chr != dat$Chromosome[i]){
counter <- 0
prev ...
written 22 days ago by
Sam • 2.4k
0
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1
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... The P-value is in fact a function of the effect size and the standard error. You can calculate the z-score by dividing the beta by the standard error, then transform the z-score into p-value directly.
One problem with the standard error is that it is correlated with the minor allele frequency of t ...
written 7 weeks ago by
Sam • 2.4k
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