ldsc_h2: Estimate heritability - refer to ldscr R package (https://github.com/mglev1n/ldscr)

Description

`ldsc_h2()` uses ldscore regression to estimate the heritability of a trait from GWAS summary statistics and reference LD information.

Usage

ldsc_h2(
  munged_sumstats,
  sample_prev = NA,
  population_prev = NA,
  ld,
  wld,
  n_blocks = 200,
  chisq_max = NA,
  chr_filter = seq(1, 22, 1)
)

Value

A [tibble][tibble::tibble-package] containing heritability information. If `sample_prev` and `population_prev` were provided, the heritability estimate will also be returned on the liability scale.

Arguments

munged_sumstats: Either a dataframe, or a path to a file containing munged summary statistics. Must contain at least columns named `SNP` (rsid), `A1` (effect allele), `A2` (non-effect allele), `N` (total sample size) and `Z` (Z-score)
sample_prev: (numeric) For binary traits, this should be the prevalence of cases in the current sample, used for conversion from observed heritability to liability-scale heritability. The default is `NA`, which is appropriate for quantitative traits or estimating heritability on the observed scale.
population_prev: (numeric) For binary traits, this should be the population prevalence of the trait, used for conversion from observed heritability to liability-scale heritability. The default is `NA`, which is appropriate for quantitative traits or estimating heritability on the observed scale.
ld: (character) Path to directory containing ld score files, ending in `*.l2.ldscore.gz`.
wld: (character) Path to directory containing weight files.
n_blocks: (numeric) Number of blocks used to produce block jackknife standard errors. Default is `200`
chisq_max: (numeric) Maximum value of Z^2 for SNPs to be included in LD-score regression. Default is to set `chisq_max` to the maximum of 80 and N*0.001.
chr_filter: (numeric vector) Chromosomes to include in analysis. Separating even/odd chromosomes may be useful for exploratory/confirmatory factor analysis.