glmWeightedF {zinbwave} | R Documentation |
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.
glmWeightedF(glmfit, coef = ncol(glmfit$design), contrast = NULL, ZI = TRUE, independentFiltering = TRUE, filter = NULL)
glmfit |
a |
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
|
independentFiltering |
logical, specifying whether independent filtering should be performed. |
filter |
vector of values to perform filtering on. Default is the mean of the fitted values from glmfit. |
This function uses an adapted version of the glmLRT
function that was originally written by Gordon Smyth, Davis
McCarthy and Yunshun Chen as part of the edgeR package.
Koen Van den Berge wrote code to adjust residual degree
of freedoom and added the independent filtering step.
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.