getSlopes: Estimate gene specific count-depth relationships

In SCnorm: Normalization of single cell RNA-seq data

Description

This is the gene-specific fitting function, where a median (Tau = .5) quantile regression is fit for each gene. Only genes having at least 10 non-zero expression values are considered.

Usage

getSlopes(
  Data,
  SeqDepth = 0,
  Tau = 0.5,
  FilterCellNum = 10,
  ditherCounts = FALSE
)

Arguments

Data	matrix of un-normalized expression counts. Rows are genes and columns are samples.
SeqDepth	vector of sequencing depths estimated as columns sums of un-normalized expression matrix.
Tau	value of quantile for the quantile regression used to estimate gene-specific slopes (default is median, Tau = .5 ).
FilterCellNum	the number of non-zero expression estimate required to include the genes into the SCnorm fitting (default = 10). The initial
ditherCounts	whether to dither/jitter the counts, may be used for data with many ties, default is FALSE.

Value

vector of estimated slopes.

Author(s)

Rhonda Bacher

Examples

 data(ExampleSimSCData)
 myslopes <- getSlopes(ExampleSimSCData)

SCnorm documentation built on Nov. 8, 2020, 5:07 p.m.