PoissonUMIFeatureSelectionDropouts {M3Drop} | R Documentation

## Dropout-based Feature Selection

### Description

Ranks genes by significance of increase in dropouts compared to expectation.

### Usage

    	PoissonUMIFeatureSelectionDropouts(fit)

### Arguments

`fit` | output from NBumiFitModel or NBumiFitBasicModel.

### Details

Calculates dropout probability for each observation using depth-adjusted negative binomial means and dispersions equal to the mean (Poisson). Total dropouts per gene are modelled using the normal approximation of the sum of bernoulli variables. And significance is evaluated using a Z-test.

### Value

Sorted vector of p-values

### Examples

    library(M3DExampleData)
    counts <- as.matrix(Mmus_example_list$data);
    counts <- counts[rowSums(counts) > 0,];
    fit <- NBumiFitModel(counts);
    Dropout_features <- names(PoissonUMIFeatureSelectionDropouts(fit)[1:2000]);

[Package M3Drop version 1.16.0 Index]