plotUMINoise: Plotting noise dependence on total UMI count

In RaceID: Identification of Cell Types, Inference of Lineage Trees, and Prediction of Noise Dynamics from Single-Cell RNA-Seq Data

Plotting noise dependence on total UMI count

Description

This function plots the dependence of mean noise per cell on the total UMI count per cell. It serves as a basis for choosing the prior parameter gamma (see function compTBNoise). With a proper parameter choice, there should be no correlation between the two quantities. If a positive correlation is observed, gamma should be increased in order to weaken the prior. If the correlation is negative, gamma should be decreased in order to increase the strength of the prior.

Usage

plotUMINoise(object, noise, log.scale = TRUE)

Arguments

object	RaceID SCseq object.
noise	object returned by compTBNoise function.
log.scale	Logical. If TRUE total transcript counts and epsilon estimates are log2-transformed for plotting. Default is TRUE.

RaceID documentation built on Sept. 28, 2023, 5:06 p.m.