Seqtometry
This is the released version of Seqtometry; for the devel version, see Seqtometry.
Signature scoring for single cell analysis
Bioconductor version: Release (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("Seqtometry")):Robert Kousnetsov. Seqtometry: Signature scoring for single cell analysis. doi:10.18129/B9.bioc.Seqtometry, R package version 1.0.1, https://bioconductor.org/packages/Seqtometry.
Generated from the package metadata; it may differ from the package's own citation.
Installation
To install this package, start R (version "4.6") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("Seqtometry")For older versions of R, please refer to the appropriate Bioconductor release.
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("Seqtometry")| Seqtometry vignette | HTML | R Script |
| Reference Manual | ||
| NEWS | Text | |
| LICENSE | Text |
Details
| biocViews | GeneExpression, GeneSetEnrichment, SingleCell, Software |
| Version | 1.0.1 |
| In Bioconductor since | BioC 3.23 (R-4.6) (< 6 months) |
| License | MIT + file LICENSE |
| Depends | R (>= 4.5.0) |
| Imports | BiocSingular, checkmate, data.table, DelayedMatrixStats, future.apply, Matrix, MatrixGenerics, purrr, Rcpp, RcppHNSW, RSpectra, sparseMatrixStats, zeallot |
| System Requirements | |
| URL | https://github.com/HawigerLab/Seqtometry |
| Bug Reports | https://github.com/HawigerLab/Seqtometry/issues |
See More
| Suggests | BiocStyle, box, dplyr, future, ggplot2, harmony, knitr, MASS, patchwork, rmarkdown, scater, scuttle, SingleCellExperiment, stringr, TENxPBMCData, testthat (>= 3.0.0), tibble |
| Linking To | Rcpp, RcppArmadillo |
| Enhances | |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Links To Me | |
| Build Report | Build Report, r-universe |
Package Archives
Follow Installation instructions to use this package in your R session.
| Source Package | Seqtometry_1.0.1.tar.gz |
| Windows Binary (x86_64) | Seqtometry_1.0.1.zip |
| macOS Binary (big-sur-x86_64) | Seqtometry_1.0.1.tgz |
| macOS Binary (sonoma-arm64) | Seqtometry_1.0.1.tgz |
| 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/ |
| Package Downloads Report | Download Stats |
| Old Source Packages for BioC 3.23 | Source Archive |