BetaFun {bayNorm} | R Documentation

## Estimate capture efficiency for cells

### Description

This function estimates cell specific capture efficiencies (`BETA_vec`) using mean raw counts of a subset of genes that is an input for bayNorm. A specific method is used to exclude genes with high expression or high drop-out are excluded.

### Usage

    BetaFun(Data, MeanBETA)

### Arguments

`Data` | A matrix of single-cell expression where rows are genes and columns are samples (cells). `Data` can be of class `SummarizedExperiment` (the assays slot contains the expression matrix, is named "Counts"), just `matrix` or sparse matrix.
`MeanBETA` | Mean capture efficiency of the scRNAseq data. This can be estimated via spike-ins or other methods.

### Value

List containing: `BETA`: a vector of capture efficiencies, which is of length number of cells; `Selected_genes`: a subset of genes that are used for estimating BETA.

### Examples

    data('EXAMPLE_DATA_list')
    BETA_out<-BetaFun(Data=EXAMPLE_DATA_list$inputdata,
    MeanBETA=0.06)

[Package bayNorm version 1.6.0 Index]