Seqtometry
This is the development version of Seqtometry; for the stable release version, see Seqtometry.
Signature scoring for single cell analysis
Bioconductor version: Development (3.24)
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")):
Huber W, Carey VJ, Gentleman R, Anders S, Carlson M, Carvalho BS, Bravo HC, Davis S, Gatto L, Girke T, Gottardo R, Hahne F, Hansen KD, Irizarry RA, Lawrence M, Love MI, MacDonald J, Obenchain V, Oleś AK, Pagès H, Reyes A, Shannon P, Smyth GK, Tenenbaum D, Waldron L, Morgan M (2015). "Orchestrating high-throughput genomic analysis with Bioconductor." Nature Methods, 12(2), 115–121. doi:10.1038/nmeth.3252.
Gentleman RC, Carey VJ, Bates DM, Bolstad B, Dettling M, Dudoit S, Ellis B, Gautier L, Ge Y, Gentry J, Hornik K, Hothorn T, Huber W, Iacus S, Irizarry R, Leisch F, Li C, Maechler M, Rossini AJ, Sawitzki G, Smith C, Smyth G, Tierney L, Yang JYH, Zhang J (2004). "Bioconductor: open software development for computational biology and bioinformatics." Genome Biology, 5(10), R80. doi:10.1186/gb-2004-5-10-r80.
Installation
To install this package, start R (version "4.6") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
## The following initializes the development version of Bioconductor
BiocManager::install(version = "devel")
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 | 1.1.1 |
| 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 |
Package Archives
Follow Installation instructions to use this package in your R session.
| Source Package | Seqtometry_1.1.1.tar.gz |
| Windows Binary (x86_64) | Seqtometry_1.1.1.zip |
| macOS Binary (big-sur-x86_64) | Seqtometry_1.1.1.tgz |
| macOS Binary (sonoma-arm64) | Seqtometry_1.1.1.tgz |
| Source Repository | git clone https://git.bioconductor.org/packages/Seqtometry |
| Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/Seqtometry |
| Bioc Package Browser | https://code.bioconductor.org/browse/Seqtometry/ |
| Package Short Url | https://bioconductor.org/packages/Seqtometry/ |
| Package Downloads Report | Download Stats |