fit_SKAT_NULL: Fit the null logistic mixed model and estimate the variance...

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)

Fit the null logistic mixed model and estimate the variance ratio by a set of randomly selected variants

Description

Fit the null logistic mixed model and estimate the variance ratio by a set of randomly selected variants

Usage

fit_SKAT_NULL(
  kins = NULL,
  phenoFile = "",
  phenoCol = "",
  traitType = "quantitative",
  invNormalize = FALSE,
  covarColList = NULL,
  qCovarCol = NULL,
  sampleIDColinphenoFile = "",
  outputPrefix = "",
  isCovariateTransform = FALSE,
  sampleFileForDosages = "",
  methodforRelatedSample = "EMMAX",
  isDiagofKinSetAsOne = FALSE
)

Arguments

phenoFile	character. Path to the phenotype file
phenoCol	character. Column name for the trait e.g. "CAD"
traitType	character. e.g. "binary" or "quantitative". By default, "binary"
invNormalize	logical. Whether to perform the inverse normalization of the trait or not. E.g. TRUE or FALSE. By default, FALSE
covarColList	vector of characters. Covariates to be used in the glm model e.g c("Sex", "Age")
qCovarCol	vector of characters. Categorical covariates to be used in the glm model (NOT work yet)
sampleIDColinphenoFile	character. Column name for the sample IDs in the phenotype file e.g. "IID".
outputPrefix	character. Path to the output files with prefix.
methodforRelatedSample	character. The method to fit model for related samples. GMMAT or EMMAX
plinkFile	character. Path to plink file to be used for calculating elements of the genetic relationship matrix (GRM)
nThreads	integer. Number of threads to be used. By default, 1
numMarkers	integer (>0). Number of markers to be used for estimating the variance ratio. By default, 30
skipModelFitting	logical. Whether to skip fitting the null model and only calculating the variance ratio, By default, FALSE. If TURE, the model file ".rda" is needed
tauInit	vector of numbers. e.g. c(1,1), Unitial values for tau. For binary traits, the first element will be always be set to 1. If the tauInit is not specified, the second element will be 0.5 for binary traits.
memoryChunk	integer or float. The size (Gb) for each memory chunk. By default, 4
LOCO	logical. Whether to apply the leave-one-chromosome-out (LOCO) option.
traceCVcutoff	float. The threshold for coefficient of variantion (CV) for the trace estimator to increase nrun
isCateVarianceRatio	logical. Whether to estimate variance ratio based on different MAC categories. If yes, six categories will be used MAC = 1, 2, 3, 4, 5, >5. Currently, if isCateVarianceRatio=TRUE, then LOCO=FALSE
IsSparseKin	logical. Whether to exploit the sparsity of GRM to estimate the variance ratio. By default, TRUE
numRandomMarkerforSparseKin	integer (>0). Number of markers to be used for first estimating the relatedness between each sample pair if IsSparseKin is TRUE
relatednessCutoff	float. The threshold to treat two samples as unrelated if IsSparseKin is TRUE

Value

a file ended with .rda that contains the glmm model information, a file ended with .varianceRatio.txt that contains the variance ratio value, and a file ended with #markers.SPAOut.txt that contains the SPAGMMAT tests results for the markers used for estimating the variance ratio.

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