Cross-Trait LD score regression

Usage

ldsc_rg(
  ld_score,
  ld_size,
  z1,
  z2,
  sample_size_1,
  sample_size_2,
  blocks = NULL,
  h2_1 = NULL,
  h2_2 = NULL,
  intercept = NULL,
  intercept_h2_1 = NULL,
  intercept_h2_2 = NULL,
  step1_chisq_max = 30,
  chi2_thr2 = Inf,
  ncores = 1
)

Arguments

ld_score: Vector of LD scores.
ld_size: Number of variants used to compute `ld_score`.
z1: Vector of z-scores for trait 1.
z2: Vector of z-scores for trait 2.
sample_size_1: Sample size of GWAS for trait 1. Possibly a vector, or just a single value.
sample_size_2: Sample size of GWAS for trait 2. Possibly a vector, or just a single value.
blocks: Either a single number specifying the number of blocks, or a vector of integers specifying the block number of each `chi2` value. Default is `200` for `snp_ldsc()`, dividing into 200 blocks of approximately equal size. `NULL` can also be used to skip estimating standard errors, which is the default for `snp_ldsc2()`.
intercept: You can constrain the intercept to some value (e.g. 0). Default is `NULL` (the intercept is estimated). Use a value of 0 if you are sure there is no overlap between GWAS samples.
intercept_h2_1: Intercept for heritability of trait 1 (default is NULL so the intercept is estimated).
intercept_h2_2: Intercept for heritability of trait 2 (default is NULL so the intercept is estimated).
step1_chisq_max: Threshold on `chi2` in step 1. Default is `30`.
chi2_thr2: Threshold on `chi2` in step 2. Default is `Inf` (none).

Value

Vector of 4 values (or only the first 2 if `blocks = NULL`): - `[["int"]]`: LDSC regression intercept, - `[["int_se"]]`: SE of this intercept, - `[["h2"]]`: LDSC regression estimate of (SNP) heritability - `[["h2_se"]]`: SE of this heritability estimate.