Bioconductor version: Release (3.16)
A support vector machine approach to identifying and filtering low quality cells from single-cell RNA-seq datasets.
Author: Tomislav Illicic, Davis McCarthy
Maintainer: Tomislav Ilicic <ti243 at cam.ac.uk>
Citation (from within R,
enter citation("cellity")
):
To install this package, start R (version "4.2") and enter:
if (!require("BiocManager", quietly = TRUE)) install.packages("BiocManager") BiocManager::install("cellity")
For older versions of R, please refer to the appropriate Bioconductor release.
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("cellity")
HTML | R Script | An introduction to the cellity package |
Reference Manual | ||
Text | NEWS |
biocViews | DimensionReduction, GeneExpression, ImmunoOncology, Normalization, Preprocessing, QualityControl, RNASeq, Sequencing, Software, SupportVectorMachine, Transcriptomics, Visualization |
Version | 1.26.0 |
In Bioconductor since | BioC 3.3 (R-3.3) (7 years) |
License | GPL (>= 2) |
Depends | R (>= 3.3) |
Imports | AnnotationDbi, e1071, ggplot2, graphics, grDevices, grid, mvoutlier, org.Hs.eg.db, org.Mm.eg.db, robustbase, stats, topGO, utils |
LinkingTo | |
Suggests | BiocStyle, caret, knitr, testthat, rmarkdown |
SystemRequirements | |
Enhances | |
URL | |
Depends On Me | |
Imports Me | |
Suggests Me | |
Links To Me | |
Build Report |
Follow Installation instructions to use this package in your R session.
Source Package | cellity_1.26.0.tar.gz |
Windows Binary | cellity_1.26.0.zip |
macOS Binary (x86_64) | cellity_1.26.0.tgz |
macOS Binary (arm64) | cellity_1.26.0.tgz |
Source Repository | git clone https://git.bioconductor.org/packages/cellity |
Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/cellity |
Bioc Package Browser | https://code.bioconductor.org/browse/cellity/ |
Package Short Url | https://bioconductor.org/packages/cellity/ |
Package Downloads Report | Download Stats |
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