model.edgeR.common: Modeling NB2 Common Dispersion with the Adjusted Profile...
In gu-mi/NBGOF: Goodness-of-Fit Tests and Model Diagnostics for Negative Binomial Regression of RNA Sequencing Data

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

This function fits an NB regression model with a common dispersion using the adjusted profile likelihood estimator. See details below. The output of this function will be passed to the main GOF function nb.gof.m.

1	model.edgeR.common(counts, x, lib.sizes=colSums(counts), method=method)

`counts`	an m-by-n count matrix of non-negative integers. For a typical RNA-Seq experiment, this is the read counts with m genes and n samples.
`x`	an n-by-p design matrix.
`lib.sizes`	library sizes of an RNA-Seq experiment. Default is the column sums of the `counts` matrix.
`method`	method for estimating the common dispersion, including "CoxReid", "Pearson" and "deviance". If NULL, then use the "CoxReid" method. See `estimateGLMCommonDisp` for more details.

This function calls the estimateGLMCommonDisp function in edgeR, with the default estimation method using Cox-Reid adjusted profile likelihood (dispCoxReid). See the estimateGLMCommonDisp and glmFit functions in the edgeR package for more information.

A list of quantities to be used in the main nb.gof.m function.

Gu Mi <neo.migu@gmail.com>, Yanming Di, Daniel Schafer

See https://github.com/gu-mi/NBGOF/wiki/ for more details.

model.edgeR.tagcom and model.edgeR.genewise

gu-mi/NBGOF documentation built on Oct. 25, 2020, 3:30 a.m.