scFeatureFilter

A correlation-based method for quality filtering of single-cell RNAseq data


Bioconductor version: Release (3.19)

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], Anagha Joshi [aut]

Maintainer: Guillaume Devailly <gdevailly at hotmail.com>

Citation (from within R, enter citation("scFeatureFilter")):

Installation

To install this package, start R (version "4.4") 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")
Introduction to scFeatureFilter HTML R Script
Reference Manual PDF
NEWS Text
LICENSE Text

Details

biocViews GeneExpression, ImmunoOncology, Preprocessing, RNASeq, SingleCell, Software
Version 1.24.0
In Bioconductor since BioC 3.7 (R-3.5) (6.5 years)
License MIT + file LICENSE
Depends R (>= 3.6)
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
See More
Suggests testthat, knitr, rmarkdown, BiocStyle, SingleCellExperiment, SummarizedExperiment, scRNAseq, cowplot
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Package Archives

Follow Installation instructions to use this package in your R session.

Source Package scFeatureFilter_1.24.0.tar.gz
Windows Binary (x86_64) scFeatureFilter_1.24.0.zip
macOS Binary (x86_64) scFeatureFilter_1.24.0.tgz
macOS Binary (arm64) scFeatureFilter_1.24.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/scFeatureFilter
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/scFeatureFilter
Bioc Package Browser https://code.bioconductor.org/browse/scFeatureFilter/
Package Short Url https://bioconductor.org/packages/scFeatureFilter/
Package Downloads Report Download Stats