vcovSqrt-method: Sqrt of co-variance matrix for 'dream()' fit

In GabrielHoffman/variancePartition: Quantify and interpret drivers of variation in multilevel gene expression experiments

Sqrt of co-variance matrix for dream() fit

Description

Define generic vcovSqrt() for result of lmFit() and dream()

Usage

vcovSqrt(object, vobj, coef, approx = TRUE)

## S4 method for signature 'MArrayLM'
vcovSqrt(object, vobj, coef, approx = TRUE)

## S4 method for signature 'MArrayLM2'
vcovSqrt(object, vobj, coef, approx = TRUE)

Arguments

object	MArrayLM object return by lmFit() or dream()
vobj	EList object returned by voom()
coef	name of coefficient to be extracted
approx	use fast approximation

Value

Computes factor of covariance matrix so that vcov(object) is the same as crossprod(vcovSqrt(object))

Examples

# load simulated data:
# geneExpr: matrix of *normalized* gene expression values
# info: information/metadata about each sample
data(varPartData)

form <- ~Batch

fit <- dream(geneExpr[1:2, ], form, info)
fit <- eBayes(fit)

# Compute covariance directly
Sigma <- vcov(fit, geneExpr[1:2, ])

# Compute factor of covariance
S <- crossprod(vcovSqrt(fit, geneExpr[1:2, ]))

GabrielHoffman/variancePartition documentation built on Nov. 8, 2024, 11:17 a.m.