gate.to.clust

This function takes an object of class iCellR and assigns cluster number to a vector of cell ids.

A toolkit that allows scientists to work with data from single cell sequencing technologies such as scRNA-seq, scVDJ-seq, scATAC-seq, CITE-Seq and Spatial Transcriptomics (ST). Single (i) Cell R package ('iCellR') provides unprecedented flexibility at every step of the analysis pipeline, including normalization, clustering, dimensionality reduction, imputation, visualization, and so on. Users can design both unsupervised and supervised models to best suit their research. In addition, the toolkit provides 2D and 3D interactive visualizations, differential expression analysis, filters based on cells, genes and clusters, data merging, normalizing for dropouts, data imputation methods, correcting for batch differences, pathway analysis, tools to find marker genes for clusters and conditions, predict cell types and pseudotime analysis. See Khodadadi-Jamayran, et al (2020) <doi:10.1101/2020.05.05.078550> and Khodadadi-Jamayran, et al (2020) <doi:10.1101/2020.03.31.019109> for more details.

Alireza Khodadadi-Jamayran

iCellR

Analyzing High-Throughput Single Cell Sequencing Data

Joseph Pucella

Hua Zhou

Nicole Doudican

John Carucci

Adriana Heguy

Boris Reizis

Aristotelis Tsirigos

gate.to.clust function

<dl><dt>x</dt>
<dd>An object of class iCellR.</dd>
<dt>my.gate</dt>
<dd>A vector of cell ids.</dd>
<dt>to.clust</dt>
<dd>A cluster id to be assigned to the provided cell ids.</dd></dl>

Arguments

Assign cluster number to cell ids — gate.to.clust

<dl>

<dt>x</dt>
<dd>An object of class iCellR.</dd>


<dt>my.gate</dt>
<dd>A vector of cell ids.</dd>


<dt>to.clust</dt>
<dd>A cluster id to be assigned to the provided cell ids.</dd>

</dl>

gate.to.clust: Assign cluster number to cell ids

Description

Usage

Value

Arguments