estEffsCPP: Estimates for covariates

View source: R/RcppExports.R

estEffsCPPR Documentation

Estimates for covariates

Description

Compute the estimates and standard errors for the covariates in the input matrix W.

Usage

estEffsCPP(
  y0,
  w0,
  x0,
  vg,
  ve,
  k,
  returnSe = TRUE,
  estCom = FALSE,
  nCores = NULL
)

Arguments

y0

An n x p matrix of observed phenotypes, on p traits or environments for n genotypes. No missing values are allowed.

w0

An n x c covariate matrix, c being the number of covariates and n being the number of genotypes. c has to be at least one (typically an intercept). No missing values are allowed.

x0

An n x ns matrix of marker scores. Neither missing values nor non-segregating markers are allowed.

vg

A p x p matrix of genetic covariances.

ve

A p x p matrix of environmental covariances.

k

An n x n genetic relatedness matrix.

returnSe

Should standard errors and p-values be returned?

estCom

Should the common SNP-effect model be fitted?

nCores

An integer indicating the number of cores used for parallel computation.

Value

A list containing the estimates, optionally the standard errors of the estimates and corresponding p-values. If estCom = TRUE also common SNP-effects, their standard errors and corresponding p-values and the p-values for QtlxE are output.

References

Zhou, X. and Stephens, M. (2014). Efficient multivariate linear mixed model algorithms for genome-wide association studies. Nature Methods, February 2014, Vol. 11, p. 407–409


statgenQTLxT documentation built on May 29, 2024, 2:08 a.m.