compute_LDSC_enrichment_discrete: Compute LDSC enrichment

In alexandruioanvoda/gwascelltyper: Fast GWAS Enrichment Testing

Compute LDSC enrichment

Description

Compute GWAS enrichment in discrete lists of genes with LDSC.

Usage

compute_LDSC_enrichment_discrete(
  gene_sets,
  sumstats_file,
  output_dir = NULL,
  number_of_threads = 1,
  window_size = 1e+05,
  pop = "eur",
  ld_wind_cm = 1,
  deps = dep_path(pop, "ldsc")
)

Arguments

gene_sets	List of genesets. Each geneset must be a character vector, containing HGNC gene names.
sumstats_file	Address of properly formatted LDSC GWAS file.
output_dir	Folder where you want the output to be stored. Default = NULL, which makes this function create a directory where results will be temporarily stored. The directory will be deleted afterwards, if this parameter is null. The only output will be the return. Otherwise, both the files and the return are kept.
number_of_threads	Number of threads to parallelize calculation over. Default = 1.
window_size	Size of window surrounding gene, for SNP-to-gene mapping purposes. Default = 100000 (100kb).
pop	Word describing ancestry of the GWAS data. Relevant so that the proper LD panel will be used (default = eur; alternatives = afr, amr, eas, sas, subpop)
ld_wind_cm	Specify the window size to be used for estimating LD Scores in units of centiMorgans (cM). Default = 1.
deps	A named list, containing all of the dependencies for LDSC (e.g. Python script paths, SNP linkage disequilibrium data, etc.). Provided by default by another function, called gwascelltyper::dep_path().
gene_nomenclature	Type of gene IDs fed in from the expression data (default = hgnc; alternatives = entrez).

Value

Dataframe

alexandruioanvoda/gwascelltyper documentation built on April 16, 2023, 8:03 p.m.