Bioconductor 3.23 Release Schedule

Seqtometry

This is the development version of Seqtometry; to use it, please install the devel version of Bioconductor.

Signature scoring for single cell analysis


Bioconductor version: Development (3.23)

This package provides functions used in Seqtometry (Kousnetsov et al. 2024), a method for analyzing single cell (scRNA-seq or scATAC-seq) data via signature (gene set) enrichment scores. The Seqtometry scores may be useful for annotating or characterizing cells, either in a flow cytometry like workflow (where scores are standalone features used for progressive partitoning as described in the Seqtometry publication) or in a cluster-based workflow (as features of clusters). The exported impute function (a port of Python's MAGIC-impute, van Dijk et al. 2018), may also be useful for single cell analysis on its own.

Author: Robert Kousnetsov [aut, cre], Daniel Hawiger [cph, fnd]

Maintainer: Robert Kousnetsov <robert.kousnetsov at health.slu.edu>

Citation (from within R, enter citation("Seqtometry")):

Installation

To install this package, start R (version "4.6") and enter:


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("Seqtometry")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

Reference Manual PDF

Details

biocViews GeneExpression, GeneSetEnrichment, SingleCell, Software
Version 0.99.2
In Bioconductor since BioC 3.23 (R-4.6)
License MIT + file LICENSE
Depends R (>= 4.5.0)
Imports BiocSingular, checkmate, data.table, future.apply, Matrix, MatrixGenerics, purrr, Rcpp, RcppHNSW, RSpectra, zeallot
System Requirements
URL https://github.com/HawigerLab/Seqtometry
Bug Reports https://github.com/HawigerLab/Seqtometry/issues
See More
Suggests box, dplyr, future, ggplot2, harmony, knitr, MASS, patchwork, rmarkdown, scater, scuttle, SingleCellExperiment, sparseMatrixStats, stringr, TENxPBMCData, testthat (>= 3.0.0), tibble
Linking To Rcpp, RcppArmadillo
Enhances
Depends On Me
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Follow Installation instructions to use this package in your R session.

Source Package
Windows Binary (x86_64)
macOS Binary (big-sur-x86_64)
macOS Binary (big-sur-arm64)
macOS Binary (sonoma-arm64)
Source Repository git clone https://git.bioconductor.org/packages/Seqtometry
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/Seqtometry
Package Short Url https://bioconductor.org/packages/Seqtometry/
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