BetaFun: Estimate capture efficiency for cells

Description Usage Arguments Value Examples

View source: R/PRIOR_FUNCTIONS.R

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

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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

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

bayNorm documentation built on Nov. 8, 2020, 8:25 p.m.