maxNoisyGenes: Function for extracting genes maximal variability

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

Function for extracting genes maximal variability

Description

This function extracts genes with maximal variability in a cluster or in the entire data set.

Usage

maxNoisyGenes(noise, cl = NULL, set = NULL)

Arguments

noise	List object with the background noise model and a variability matrix, returned by the compNoise function.
cl	List object with clustering information, returned by the graphCluster function. Default is NULL.
set	Postive integer number or vector of integers corresponding to valid cluster numbers. Noise levels are computed across all cells in this subset of clusters. Default is NULL and noise levels are computed across all cells.

Value

Vector with average gene expression variability in decreasing order, computed across all cells or only cells in a set of clusters (if cl and set are given.

Examples

res <- pruneKnn(intestinalDataSmall,knn=10,alpha=1,no_cores=1,FSelect=FALSE)
noise <- compNoise(intestinalDataSmall,res,pvalue=0.01,genes = NULL,no_cores=1)
mgenes <- maxNoisyGenes(noise)

RaceID documentation built on April 4, 2025, 4:34 a.m.