susieI_rss: Iteratively run susie and estimate parameters - RSS version

In simingz/ctwas: Adjusting for genetic confounders in transcriptome-wide association studies improves discovery of risk genes of complex traits

Iteratively run susie and estimate parameters - RSS version

Description

Iteratively run susie and estimate parameters - RSS version

Usage

susieI_rss(
  zdf,
  regionlist,
  ld_exprvarfs,
  ld_exprfs = NULL,
  ld_pgenfs = NULL,
  ld_Rfs = NULL,
  niter = 20,
  L = 1,
  z_ld_weight = 0,
  group_prior = NULL,
  group_prior_var = NULL,
  estimate_group_prior = T,
  estimate_group_prior_var = T,
  use_null_weight = T,
  coverage = 0.95,
  ncore = 1,
  outputdir = getwd(),
  outname = NULL,
  report_parameters = T
)

Arguments

zdf	A data frame with three columns: "id", "z", "type". This data frame gives the the z scores for SNPs and genes, denoted in "type". The "type" column can also be use to specify multiple sets of weights
regionlist	a list object indexing regions, variants and genes. The output of index_regions
ld_exprvarfs	A character vector of '.exprvar' files. One file for one chromosome, in the order of 1 to 22. Therefore, the length of this vector needs to be 22. '.exprvar' files are tab delimited text files, with columns: chrom chromosome number, numeric p0 gene boundary position, the smaller value p1 gene boundary position, the larger value id gene id Its rows should be in the same order as the columns for corresponding '.expr' files.
ld_pgenfs	A character vector of .pgen or .bed files. One file for one chromosome, in the order of 1 to 22. Therefore, the length of this vector needs to be 22. If .pgen files are given, then .pvar and .psam are assumed to present in the same directory. If .bed files are given, then .bim and .fam files are assumed to present in the same directory.
ld_Rfs	a vector of paths to the LD matrices
niter	the number of iterations of the E-M algorithm to perform
L	the number of effects for susie
z_ld_weight	the z_ld_weight parameter for susie_rss
group_prior	a vector of two prior inclusion probabilities for SNPs and genes. This is ignored if estimate_group_prior = T
group_prior_var	a vector of two prior variances for SNPs and gene effects. This is ignored if estimate_group_prior_var = T
estimate_group_prior	TRUE/FALSE. If TRUE, the prior inclusion probabilities for SNPs and genes are estimated using the data. If FALSE, group_prior must be specified
estimate_group_prior_var	TRUE/FALSE. If TRUE, the prior variances for SNPs and genes are estimated using the data. If FALSE, group_prior_var must be specified
use_null_weight	TRUE/FALSE. If TRUE, allow for a probability of no effect in susie
coverage	A number between 0 and 1 specifying the “coverage” of the estimated confidence sets
ncore	The number of cores used to parallelize susie over regions
outputdir	a string, the directory to store output
outname	a string, the output name
report_parameters	TRUE/FALSE. If TRUE, estimated parameters are reported at the end of iteration

simingz/ctwas documentation built on Sept. 17, 2024, 10:55 p.m.