getContrast {variancePartition} | R Documentation

## Extract contrast matrix for linear mixed model

### Description

Extract contrast matrix, L, testing a single variable. Contrasts involving more than one variable can be constructed by modifying L directly

### Usage

    getContrast(exprObj, formula, data, coefficient)

### Arguments

`exprObj` | matrix of expression data (g genes x n samples), or ExpressionSet, or EList returned by voom() from the limma package
`formula` | specifies variables for the linear (mixed) model. Must only specify covariates, since the rows of exprObj are automatically used a a response. e.g.: ~ a + b + (1|c) Formulas with only fixed effects also work
`data` | data.frame with columns corresponding to formula
`coefficient` | the coefficient to use in the hypothesis test

### Value

Contrast matrix testing one variable

### Examples

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

    # get contrast matrix testing if the coefficient for Batch2 is zero
    # The variable of interest must be a fixed effect
    form <- ~ Batch + (1|Individual) + (1|Tissue)
    L = getContrast( geneExpr, form, info, "Batch3")

    # get contrast matrix testing if Batch3 - Batch2 = 0
    form <- ~ Batch + (1|Individual) + (1|Tissue)
    L = getContrast( geneExpr, form, info, c("Batch3", "Batch2"))

    # To test against Batch1 use the formula:
    # 	~ 0 + Batch + (1|Individual) + (1|Tissue)
    # to estimate Batch1 directly instead of using it as the baseline

[Package variancePartition version 1.12.3 Index]