kersplatEstMean: Estimate Kersplat means
In Oshlack/splatter: Simple Simulation of Single-cell RNA Sequencing Data

kersplatEstMean

R Documentation

Estimate Kersplat means

Description

Estimate mean parameters for the Kersplat simulation

Usage

kersplatEstMean(norm.counts, params, verbose)

Arguments

`norm.counts`	library size normalised counts matrix.
`params`	KersplatParams object to store estimated values in.
`verbose`	logical. Whether to print progress messages

Details

Parameters for the gamma distribution are estimated by fitting the mean normalised counts using fitdist. All the fitting methods are tried and the fit with the best Cramer-von Mises statistic is selected. The density of the means is also estimated using density.

Expression outlier genes are detected using the Median Absolute Deviation (MAD) from median method. If the log2 mean expression of a gene is greater than two MADs above the median log2 mean expression it is designated as an outlier. The proportion of outlier genes is used to estimate the outlier probability. Factors for each outlier gene are calculated by dividing mean expression by the median mean expression. A log-normal distribution is then fitted to these factors in order to estimate the outlier factor location and scale parameters using the fitdist MLE method.