NBumiFeatureSelectionOther {M3Drop} | R Documentation

## Other Feature Selection Methods

### Description

Ineffective alternative feature selection methods based on the depth-adjusted negative binomial model. Functions tagged with "bg__" are not meant for direct usage and are not available in the Bioconductor release.

### Arguments

`fit` | output from NBumiFitModel or NBumiFitBasicModel.
`window_size` | window for calculating the moving median.

### Details

Calculates dropout probability for each observation using depth-adjusted negative binomial means and dispersions calculated from a fitted power-law relationship between mean and dispersion. Total dropouts per gene are modelled using the normal approximation of the sum of bernoulli variables. And significance is evaluated using a Z-test.

`obsolete__nbumiFeatureSelectionDropouts` Ranks genes by significance of increase in dropouts compared to expectation allowing for gene-specific dispersions. `obsolete__nbumiFeatureSelectionHighVarDist2Med` Ranks genes by the distance to median of log-transformed estimated dispersions.

### Value

Sorted vector of p-values/distances.

### Examples

    library(M3DExampleData)
    #counts <- as.matrix(Mmus_example_list$data);
    #counts <- counts[rowSums(counts) > 0,];
    #fit <- NBumiFitModel(counts);
    #Dropout_features <- names(obsolete__nbumiFeatureSelectionDropouts(fit)[1:2000]);
    #dist2med_features <- names(obsolete__nbumiFeatureSelectionHighVarDist2Med(fit)[1:2000]);

[Package M3Drop version 1.16.0 Index]