scFeatureFilter

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

Bioconductor version: 3.24 · Package version: 1.33.0

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.

Installation

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("scFeatureFilter")

Details

Maintainer	Guillaume Devailly <gdevailly@hotmail.com>
Author	Angeles Arzalluz-Luque [aut], Guillaume Devailly [aut, cre] (ORCID: <https://orcid.org/0000-0001-8878-9357>), Anagha Joshi [aut]
License	MIT + file LICENSE
URL	https://bioconductor.org/packages/scFeatureFilter/
Bug Reports	https://github.com/gdevailly/scFeatureFilter/issues
Downloads rank	464
Source branch	devel
biocViews	GeneExpression, ImmunoOncology, Preprocessing, RNASeq, SingleCell, Software

Documentation

Introduction to the scFeatureFilter package

Download

Follow the installation instructions to use this package in your R session.

Source package	scFeatureFilter_1.33.0.tar.gz
Windows binary (x86_64)	scFeatureFilter_1.33.0.zip
macOS binary (arm64)	scFeatureFilter_1.33.0.tgz
macOS binary (x86_64)	scFeatureFilter_1.33.0.tgz

Dependencies

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

Suggests: testthat, knitr, rmarkdown, BiocStyle, MASS, SingleCellExperiment, SummarizedExperiment, scRNAseq, cowplot