Description Usage Arguments References See Also Examples

This function recycles an old version of the `glmLRT`

method that allows an F-test with adjusted denominator degrees of freedom to account for the downweighting in the zero-inflation model.

1 2 | ```
glmWeightedF(glmfit, coef = ncol(glmfit$design), contrast = NULL,
test = "F", ZI = TRUE, independentFiltering = TRUE, filter = NULL)
``` |

`coef` |
integer or character vector indicating which coefficients of the linear model are to be tested equal to zero. Values must be columns or column names of design. Defaults to the last coefficient. Ignored if |

`contrast` |
numeric vector or matrix specifying one or more contrasts of the linear model coefficients to be tested equal to zero. Number of rows must equal to the number of columns of |

`ZI` |
Logical, specifying whether the degrees of freedom in the statistical test should be adjusted according to the weights in the |

`fit` |
a |

McCarthy, DJ, Chen, Y, Smyth, GK (2012). Differential expression analysis of multifactor RNA-Seq experiments with respect to biological variation. Nucleic Acids Research 40, 4288-4297.

1 2 3 4 5 6 7 8 9 | ```
library(edgeR)
data(islamEset,package="zingeR")
islam=exprs(islamEset)[1:2000,]
design=model.matrix(~pData(islamEset)[,1])
d=DGEList(islam)
d=calcNormFactors(d)
d=estimateWeightedDispersions(d,design, maxit=200)
fit=glmFit(d,design)
lrt=glmWeightedF(fit,coef=2)
``` |

statOmics/zingeR documentation built on May 20, 2019, 6:48 p.m.

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