maxNoisyGenes

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

Application of 'RaceID' allows inference of cell types and prediction of lineage trees by he StemID2 algorithm. Herman, J.S., Sagar, Grün D. (2018) <DOI:10.1038/nmeth.4662>.

Dominic Grc3<bc>n

RaceID

Identification of Cell Types and Inference of Lineage Trees from
Single-Cell RNA-Seq Data

maxNoisyGenes function

<dl><dt>noise</dt>
<dd>List object with the background noise model and a variability matrix, returned by the <code>compNoise</code> function.</dd>
<dt>cl</dt>
<dd>List object with Louvain clustering information, returned by the <code>graphCluster</code> function. Default is <code>NULL</code>.</dd>
<dt>set</dt>
<dd>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 <code>NULL</code> and noise levels are computed across all cells.</dd></dl>

Arguments

Function for extracting genes maximal variability — maxNoisyGenes

<dl>

<dt>noise</dt>
<dd>List object with the background noise model and a variability matrix, returned by the <code>compNoise</code> function.</dd>


<dt>cl</dt>
<dd>List object with Louvain clustering information, returned by the <code>graphCluster</code> function. Default is <code>NULL</code>.</dd>


<dt>set</dt>
<dd>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 <code>NULL</code> and noise levels are computed across all cells.</dd>

</dl>

maxNoisyGenes: Function for extracting genes maximal variability

Description

Usage

Value

Arguments

Examples