Compute estimated coefficients, standard errors and LogVarRatios for a given set of contrasts.

1 | ```
contrasts.varFit(fit, contrasts=NULL)
``` |

`fit` |
list containing a linear model fit produced by |

`contrasts` |
numeric matrix with rows corresponding to coefficients in |

This function calls the `contrasts.fit`

function in `limma`

to compute coefficients and standard errors for the specified contrasts corresponding to a linear model fit obtained from the `varFit`

function. LogVarRatios are also computed in terms of the contrasts. A contrasts matrix can be computed using the `makeContrasts`

function.

A list object of the same class as `fit`

.

Belinda Phipson

`varFit`

, `contrasts.fit`

, `makeContrasts`

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | ```
# Randomly generate data for a 3 group problem with 100 CpG sites and 4 arrays in each group.
library(limma)
y<-matrix(rnorm(1200),ncol=12)
group<-factor(rep(c(1,2,3),each=4))
design<-model.matrix(~0+group)
colnames(design)<-c("grp1","grp2","grp3")
# Fit linear model for differential variability
vfit<-varFit(y,design)
# Specify contrasts
contr<-makeContrasts(grp2-grp1,grp3-grp1,grp3-grp2,levels=colnames(design))
# Compute contrasts from fit object
vfit.contr<-contrasts.varFit(vfit,contrasts=contr)
summary(decideTests(vfit.contr))
# Look at top table of results for first contrast
topVar(vfit.contr,coef=1)
``` |

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