createSparseGRM: Construct a sparse GRM for a given data set

In weizhouUMICH/SAIGE: Efficiently controlling for case-control imbalance and sample relatedness in single-variant assoc tests (SAIGE) and controlling for sample relatedness in region-based assoc tests in large cohorts and biobanks (SAIGE-GENE)

Construct a sparse GRM for a given data set

Description

Construct a sparse GRM for a given data set

Usage

createSparseGRM(
  plinkFile = "",
  outputPrefix = "",
  numRandomMarkerforSparseKin = 1000,
  relatednessCutoff = 0.125,
  memoryChunk = 2,
  isDiagofKinSetAsOne = FALSE,
  nThreads = 1,
  minMAFforGRM = 0.01,
  isSetGeno = TRUE,
  isWritetoFiles = TRUE
)

Arguments

plinkFile	character. Path to plink file to be used for calculating the sparse GRM
outputPrefix	character. Path to the output files with prefix
numRandomMarkerforSparseKin	integer. number of randomly selected markers (MAF >= 0.01) to be used to identify related samples for sparse GRM. By default, 1000
relatednessCutoff	float. The threshold to treat two samples as unrelated if IsSparseKin is TRUE. By default, 0.125
memoryChunk	integer or float. The size (Gb) for each memory chunk. By default, 2
isDiagofKinSetAsOne	logical. Whether to set the diagnal elements in GRM to be 1. By default, FALSE
nThreads	integer. Number of threads to be used. By default, 1
minMAFforGRM	numeric. Minimum MAF for markers (in the Plink file) used for construcing the sparse GRM. By default, 0.01

Value

a file ended with sampleIDs.txt that contains sample IDs for the sparse GRM and a file ended with .sparseGRM.mtx that contains the sparse GRM

weizhouUMICH/SAIGE documentation built on May 6, 2022, 12:34 a.m.