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DESCRIPTION
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DESCRIPTION
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Package: scGate
Type: Package
Title: Marker-Based Cell Type Purification for Single-Cell Sequencing Data
Version: 1.6.2
Authors@R: c(
person('Massimo', 'Andreatta',
email = '[email protected]',
role = c('aut','cre'),
comment = c(ORCID = '0000-0002-8036-2647')),
person('Ariel','Berenstein',
email = '[email protected]',
role = c('aut'),
comment = c(ORCID = '0000-0001-8540-5389')),
person('Josep','Garnica',
email = '[email protected]',
role = c('aut')),
person('Santiago', 'Carmona',
email = '[email protected]',
role = c('aut'),
comment = c(ORCID = '0000-0002-2495-0671'))
)
Description: 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>.
biocViews:
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
VignetteBuilder: knitr
URL: https://github.com/carmonalab/scGate
BugReports: https://github.com/carmonalab/scGate/issues
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.2.3