CRAN/E | scGate

scGate

Marker-Based Cell Type Purification for Single-Cell Sequencing Data

Installation

About

A common bioinformatics task in single-cell data analysis is to purify a cell type or cell population of interest from heterogeneous datasets. 'scGate' automatizes marker-based purification of specific cell populations, without requiring training data or reference gene expression profiles. Briefly, 'scGate' takes as input: i) a gene expression matrix stored in a 'Seurat' object and ii) a “gating model” (GM), consisting of a set of marker genes that define the cell population of interest. The GM can be as simple as a single marker gene, or a combination of positive and negative markers. More complex GMs can be constructed in a hierarchical fashion, akin to gating strategies employed in flow cytometry. 'scGate' evaluates the strength of signature marker expression in each cell using the rank-based method 'UCell', and then performs k-nearest neighbor (kNN) smoothing by calculating the mean 'UCell' score across neighboring cells. kNN-smoothing aims at compensating for the large degree of sparsity in scRNA-seq data. Finally, a universal threshold over kNN-smoothed signature scores is applied in binary decision trees generated from the user-provided gating model, to annotate cells as either “pure” or “impure”, with respect to the cell population of interest. See the related publication Andreatta et al. (2022) doi:10.1093/bioinformatics/btac141.

Citation scGate citation info
github.com/carmonalab/scGate
Bug report File report

Key Metrics

Version 1.6.2
R ≥ 4.3.0
Published 2024-04-23 167 days ago
Needs compilation? no
License GPL-3
CRAN checks scGate results

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Maintainer

Maintainer

Massimo Andreatta

Authors

Massimo Andreatta

aut / cre

Ariel Berenstein

aut

Josep Garnica

aut

Santiago Carmona

aut

Material

NEWS
Reference manual
Package source

Vignettes

Index of scGate vignettes

macOS

r-prerel

arm64

r-release

arm64

r-oldrel

arm64

r-prerel

x86_64

r-release

x86_64

Windows

r-prerel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

scGate archive

Depends

R ≥ 4.3.0

Imports

Seurat ≥ 4.0.0
UCell ≥ 2.6.0
dplyr
stats
utils
methods
patchwork
ggridges
reshape2
ggplot2
BiocParallel

Suggests

ggparty
partykit
knitr
rmarkdown