cellity

This is the released version of cellity; for the devel version, see cellity.

All versions

3.24 (devel), 3.23 (release), 3.22, 3.21, 3.20, 3.19, 3.18, 3.17, 3.16, 3.15, 3.14, 3.13, 3.12, 3.11, 3.10, 3.9, 3.8, 3.7, 3.6, 3.5, 3.4, 3.3

Quality Control for Single-Cell RNA-seq Data

Bioconductor version: Release (3.23)

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")):

Tomislav Illicic, Davis McCarthy. cellity: Quality Control for Single-Cell RNA-seq Data. doi:10.18129/B9.bioc.cellity, R package version 1.40.0, https://bioconductor.org/packages/cellity.

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("cellity")

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("cellity")

Introduction to cellity: Classification of low quality cells in scRNA-seq data using R	HTML	R Script
Reference Manual	PDF
NEWS	Text

Need some help? Ask on the Bioconductor Support site!

Details

biocViews	DimensionReduction, GeneExpression, ImmunoOncology, Normalization, Preprocessing, QualityControl, RNASeq, Sequencing, Software, SupportVectorMachine, Transcriptomics, Visualization
Version	1.40.0
In Bioconductor since	BioC 3.3 (R-3.3) (10.5 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
System Requirements
URL

Suggests	BiocStyle, caret, knitr, testthat, rmarkdown
Linking To
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	cellity_1.40.0.tar.gz
Windows Binary (x86_64)	cellity_1.40.0.zip (64-bit only)
macOS Binary (big-sur-x86_64)	cellity_1.40.0.tgz
macOS Binary (sonoma-arm64)	cellity_1.40.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/cellity
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/cellity
Package Short Url	https://bioconductor.org/packages/cellity/
Package Downloads Report	Download Stats