This is the released version of scFeatureFilter; for the devel version, see scFeatureFilter.
A correlation-based method for quality filtering of single-cell RNAseq data
Bioconductor version: Release (3.22)
An R implementation of the correlation-based method developed in the Joshi laboratory to analyse and filter processed single-cell RNAseq data. It returns a filtered version of the data containing only genes expression values unaffected by systematic noise.
Author: Angeles Arzalluz-Luque [aut], Guillaume Devailly [aut, cre]
ORCID: 0000-0001-8878-9357
, Anagha Joshi [aut]
Maintainer: Guillaume Devailly <gdevailly at hotmail.com>
citation("scFeatureFilter")):
Installation
To install this package, start R (version "4.5") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("scFeatureFilter")
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("scFeatureFilter")
Details
| biocViews | GeneExpression, ImmunoOncology, Preprocessing, RNASeq, SingleCell, Software |
| Version | 1.30.1 |
| In Bioconductor since | BioC 3.7 (R-3.5) (8 years) |
| License | MIT + file LICENSE |
| Depends | R (>= 4.5.0) |
| Imports | dplyr (>= 0.7.3), ggplot2 (>= 2.1.0), magrittr (>= 1.5), rlang (>= 0.1.2), tibble (>= 1.3.4), stats, methods |
| System Requirements | |
| URL | https://bioconductor.org/packages/scFeatureFilter/ |
| Bug Reports | https://github.com/gdevailly/scFeatureFilter/issues |
See More
Package Archives
Follow Installation instructions to use this package in your R session.