You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Ideally we want to have some basic SNP info available (e.g. position, allele), which is essential in combining LD with GWAS summary statistics in analyses.
I agree that returning some kind of info about SNPs would be useful. I don't think it's useful or necessary to enforce that though. One thing that would be quick and easy would be to add colnames and rownames to the LD matrix that match the colnames of the input SNP matrix, that way the user has the option of getting back SNP information, but doesn't need to make up fake SNP information if they don't have any (which comes up pretty often)
@CreRecombinase yes, colnames and rownames seem to be sufficient in most cases.
Totally agree the following:
that way the user has the option of getting back SNP information, but doesn't need to make up fake SNP information if they don't have any (which comes up pretty often)
LDshrink doesn't have to give a snp_info when users don't have any.
There is one use case that having snp_info seems necessary. Suppose one analyst needs to analyze GWAS summary data of two traits together with LD estimates. For many SNPs, the ALT and REF alleles are different between the two traits. To properly flip the sign of betahat and/or LD estimates, we need the ALT and REF info.
However, this won't be necessary if the analyst has already unified the ALT and REF of all GWAS summary data files before using LDshrink.
Finally, I think emeraLD can easily pull out snp_info because it uses vcf as input, and vcf already contains snp_info.
It seems the main function only returns an estimated LD matrix at this point?
https://github.com/stephenslab/LDshrink/blob/32b4ad3942f7cb429f23c529b86ab72cfbb1b257/R/LDshrink.R#L6
Ideally we want to have some basic SNP info available (e.g. position, allele), which is essential in combining LD with GWAS summary statistics in analyses.
I think the
emeraLD
package gives us a good example: https://github.com/statgen/emeraLDThe text was updated successfully, but these errors were encountered: