RemoveSparseFeatures {CountClust} | R Documentation

## Removes features with a lot of 0 counts

### Description

This function deals with zero counts in the counts dataset. If for a feature, the proportion of zeros across the samples is greater than filter_prop, then we remove the feature.

### Usage

    RemoveSparseFeatures(data, filter_prop = 0.9)

### Arguments

`data` | count data in a sample by feature matrix.
`filter_prop` | threshold proportion. If the proportion of zeros for the feature exceeds this threshold then we remove the feature altogether. Default is 0.9.

### Value

Returns a list with

`data` | filtered data with sparse features removed
`sparse_features` | the feature names of the features found sparse and removed

### Examples

    mat <- rbind(c(2,0,3,0,4),c(4,5,5,0,0),c(30,34,63,25,0),c(0,0,0,0,0));
    RemoveSparseFeatures(mat, filter_prop = 0.5)
    RemoveSparseFeatures(mat)

[Package CountClust version 1.16.0 Index]