NBumi_TradDE: Perform Traditional Differential Expression
In tallulandrews/M3D: Michaelis-Menten Modelling of Dropouts in single-cell RNASeq

Description Arguments Details Value Examples

Performs traditional (i.e. compare defined groups) differential expression using a negative binomial model with MM zero-inflation. Functions tagged with "bg__" are not meant for direct usage and are not available in the Bioconductor release.

`counts`	a numeric matrix of raw UMI counts, columns = samples, rows = genes.
`fit`	fit NB UMI model from NBumiFitModel
`groups`	a vector of biological group IDs for each cell(columns).

THIS FUNCTION SHOULD NOT BE USED.

unfinished__nbumiGroupDE Uses a log-likelihood ratio test to perform model selection between a model of constant mean expression vs a model of different mean expression across the biological groups. Probabilities of observing the data given the model are calculated using a negative binomial distribution with means adjusted for the total molecules detected per cell and dispersion fit to observed variance and adjusted to the mean of each group based on a globally fit power-law relationship. Significance is evaluated using the chi-square distribution.

A table of fold mean expression differences for each biological group relative to the global mean expression level with raw p-values and FDR corrected p-values for each gene.

#library(M3DExampleData)
#counts <- as.matrix(Mmus_example_list$data);
#counts <- counts[rowSums(counts) > 0,];
#counts <- counts[1:1000,]
#fit <- NBumiFitModel(counts);
#DE_output <- bg__nbumiGroupDE(counts, fit, Mmus_example_list$labels)