glmLRTqtQDA: Fit 'glmLRT' from 'edgeR'

In goknurginer/qtQDA: Classify Samples From RNA-Seq Datasets

Description

Given training set and training labels, generates the table of features obtained from glmLRT in R package edgeR and sorted by likelihood ratio statistics (LR).

Usage

glmLRTqtQDA(training, training.labels)

Arguments

training	a DGEList object or a matrix containing counts for training samples.
training.labels	a character vector of class labels for each sample. The labels show which category each sample comes from.

Details

This function estimates the top tags from training data using the statistical methodologies glmFit and glmLRT that implement generalized linear model (glm) methods developed by McCarthy et al (2012) in R package edgeR.

Value

a data frame where the rows are same as for training but sorted in descending order by likelihood ratio statistics (LR).

References

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. https://doi.org/10.1093/nar/gks042

See Also

See qtQDA and qtQDA.resampling.

goknurginer/qtQDA documentation built on March 4, 2020, 6:02 p.m.