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.

1 2 3 4 5 6 | ```
#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)
``` |

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