This is the development version of scFeatureFilter; for the stable release version, see scFeatureFilter.
A correlation-based method for quality filtering of single-cell RNAseq dataBioconductor version: Development (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], Anagha Joshi [aut]
Maintainer: Guillaume Devailly <gdevailly at hotmail.com>
Citation (from within R, entercitation("scFeatureFilter")
): Installation
To install this package, start R (version "4.5") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
# The following initializes usage of Bioc devel
BiocManager::install(version='devel')
BiocManager::install("scFeatureFilter")
For older versions of R, please refer to the appropriate Bioconductor release.
DocumentationTo 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 1.29.0 In Bioconductor since BioC 3.7 (R-3.5) (7 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 Package Archives
Follow Installation instructions to use this package in your R session.
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