check_zscore: Check for Z-score column

In neurogenomics/MungeSumstats: Standardise summary statistics from GWAS

Check for Z-score column

Description

The following ensures that a Z-score column is present. The Z-score formula we used here is a R implementation of the formula used in LDSC's munge_sumstats.py:

Usage

check_zscore(
  sumstats_dt,
  imputation_ind,
  compute_z = "BETA",
  force_new_z = FALSE,
  standardise_headers = FALSE,
  mapping_file
)

Arguments

sumstats_dt	data table obj of the summary statistics file for the GWAS.
imputation_ind	Binary Should a column be added for each imputation step to show what SNPs have imputed values for differing fields. This includes a field denoting SNP allele flipping (flipped). Note these columns will be in the formatted summary statistics returned. Default is FALSE.
compute_z	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.
force_new_z	When a "Z" column already exists, it will be used by default. To override and compute a new Z-score column from P set force_new_z=TRUE.
standardise_headers	Run standardise_sumstats_column_headers_crossplatform first.
mapping_file	MungeSumstats has a pre-defined column-name mapping file which should cover the most common column headers and their interpretations. However, if a column header that is in youf file is missing of the mapping we give is incorrect you can supply your own mapping file. Must be a 2 column dataframe with column names "Uncorrected" and "Corrected". See data(sumstatsColHeaders) for default mapping and necessary format.

Details

np.sqrt(chi2.isf(P, 1))

The R implementation is adapted from the GenomicSEM::munge function, after optimizing for speed using data.table:

sumstats_dt[,Z:=sign(BETA)*sqrt(stats::qchisq(P,1,lower=FALSE))]

NOTE: compute_z is set to TRUE by default to ensure standardisation of the "Z" column (which can be computed differently in different datasets).

Value

list("sumstats_dt"=sumstats_dt)

neurogenomics/MungeSumstats documentation built on May 2, 2024, 9:04 a.m.