contrastAsCoef: Reform a Design Matrix to that Contrasts Become Coefficients
In hdeberg/limma: Linear Models for Microarray Data

Description Usage Arguments Details Value Author(s) See Also Examples

Reform a design matrix so that one or more coefficients from the new matrix correspond to specified contrasts of coefficients from the old matrix.

1	contrastAsCoef(design, contrast=NULL, first=TRUE)

`design`	numeric design matrix.
`contrast`	numeric matrix with rows corresponding to columns of the design matrix (coefficients) and columns containing contrasts. May be a vector if there is only one contrast.
`first`	logical, should coefficients corresponding to contrasts be the first columns (`TRUE`) or last columns (`FALSE`) of the output design matrix.

If the contrasts contained in the columns of contrast are not linearly dependent, then superfluous columns are dropped until the remaining matrix has full column rank. The number of retained contrasts is stored in qr$rank and the retained columns are given by qr$pivot.

A list with components

`design`	reformed design matrix
`coef`	columns of design matrix which hold the meaningful coefficients
`qr`	QR-decomposition of contrast matrix

Gordon Smyth

model.matrix in the stats package.

An overview of linear model functions in limma is given by 06.LinearModels.

design <- cbind(1,c(0,0,1,1,0,0),c(0,0,0,0,1,1))
cont <- c(0,-1,1)
design2 <- contrastAsCoef(design, cont)$design

#  Original coef[3]-coef[2] becomes coef[1]
y <- rnorm(6)
fit1 <- lm(y~0+design)
fit2 <- lm(y~0+design2)
coef(fit1)
coef(fit1) 
coef(fit2)