plotPP: Plotting function for posterior checks

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

Plotting function for posterior checks

Description

This function plots various statistics for the posterior check

Usage

plotPP(pp, y = NULL, umi.eps = FALSE, i = 1, log.scale = TRUE)

Arguments

pp	List object returned by testPrior function.
y	One of "mean", "median", "var", "cor", or NULL. If NULL then the ratios between the predicted and the actual variances across all sampled genes and neighbourhoods are shown as boxplots for all tested values of the prior parameter gamma. If y equals "mean", "median", or "var", the mean, median, or variance is plotted for all gamma values. If y equal "cor", then the correlation between the total transcript count of a cell and the local noise estimate epsilon is plotted for all values of gamma. Default is NULL.
umi.eps	Logical. If TRUE then a scatter plot of the local noise estimate epsilon and the total transcript count is produced for a given element i of the pp$noise corresponding to a value of the prior parameter gamma. Default is FALSE.
i	Positive integer number. Index of pp$noise, corresponding to a value of the prior parameter gamma to be used for plotting is umi.eps=TRUE. Default is 1.
log.scale	Logical. If TRUE then the ratio between the predicted and the actual variance is transformed to a log2-scale prior to computations and plotting. If umi.eps=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.