scFeatureFilter

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

Bioconductor version: 3.23 · Package version: 1.32.0

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	RELEASE_3_23
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_1.32.0.tar.gz
Windows binary (x86_64)	scFeatureFilter_1.32.0.zip
macOS binary (arm64)	scFeatureFilter_1.32.0.tgz
macOS binary (x86_64)	scFeatureFilter_1.32.0.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