R/check_ldsc_format.R
check_ldsc_format.RdFormat summary statistics for direct input to
Linkage Disequilibrium SCore (LDSC) regression without the need
to use their munge_sumstats.py script first.
check_ldsc_format(
sumstats_dt,
save_format,
convert_n_int,
allele_flip_check,
compute_z,
compute_n
)data table obj of the summary statistics file for the GWAS.
Output format of sumstats. Options are NULL - standardised output format from MungeSumstats, LDSC - output format compatible with LDSC and openGWAS - output compatible with openGWAS VCFs. Default is NULL.
Binary, if N (the number of samples) is not an integer, should this be rounded? Default is TRUE.
Binary Should the allele columns be checked against reference genome to infer if flipping is necessary. Default is TRUE.
Whether to compute Z-score column. Default is FALSE. This can be computed from Beta and SE with (Beta/SE) or P (Z:=sign(BETA)*sqrt(stats::qchisq(P,1,lower=FALSE))). Note that imputing the Z-score from P for every SNP will not be perfectly correct and may result in a loss of power. This should only be done as a last resort. Use 'BETA' to impute by BETA/SE and 'P' to impute by SNP p-value.
Whether to impute N. Default of 0 won't impute, any other integer will be imputed as the N (sample size) for every SNP in the dataset. Note that imputing the sample size for every SNP is not correct and should only be done as a last resort. N can also be inputted with "ldsc", "sum", "giant" or "metal" by passing one of these for this field or a vector of multiple. Sum and an integer value creates an N column in the output whereas giant, metal or ldsc create an Neff or effective sample size. If multiples are passed, the formula used to derive it will be indicated.
Formatted summary statistics