DOI: 10.18129/B9.bioc.scFeatureFilter    

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 data

Bioconductor version: Development (3.17)

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>

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biocViews GeneExpression, ImmunoOncology, Preprocessing, RNASeq, SingleCell, Software
Version 1.19.0
In Bioconductor since BioC 3.7 (R-3.5) (4.5 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
Suggests testthat, knitr, rmarkdown, BiocStyle, SingleCellExperiment, SummarizedExperiment, scRNAseq, cowplot
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