hto.anno

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

hto.anno function

<dl><dt>hto.data</dt>
<dd>HTO raw data</dd>
<dt>cov.thr</dt>
<dd>A number which average coverage is divided by to set a threshold for low coverage. For example 10 means it is 10 time less than the average. default = 10.</dd>
<dt>assignment.thr</dt>
<dd>A percent above which you decide to set as a good sample assignment/HTO, default = 80.</dd></dl>

Arguments

Demultiplexing HTOs — hto.anno

<dl>

<dt>hto.data</dt>
<dd>HTO raw data</dd>


<dt>cov.thr</dt>
<dd>A number which average coverage is divided by to set a threshold for low coverage. For example 10 means it is 10 time less than the average. default = 10.</dd>


<dt>assignment.thr</dt>
<dd>A percent above which you decide to set as a good sample assignment/HTO, default = 80.</dd>

</dl>

Demultiplexing HTOs

hto.anno: Demultiplexing HTOs

Description

Usage

Value

Arguments