DIscBIO: A User-Friendly Pipeline for Biomarker Discovery in Single-Cell Transcriptomics

An open, multi-algorithmic pipeline for easy, fast and efficient analysis of cellular sub-populations and the molecular signatures that characterize them. The pipeline consists of four successive steps: data pre-processing, cellular clustering with pseudo-temporal ordering, defining differential expressed genes and biomarker identification. More details on Ghannoum et. al. (2021) <doi:10.3390/ijms22031399>. This package implements extensions of the work published by Ghannoum et. al. (2019) <doi:10.1101/700989>.

Version: 1.2.2
Depends: R (≥ 4.0), SingleCellExperiment
Imports: methods, TSCAN, httr, mclust, statmod, igraph, RWeka, vegan, NetIndices, png, grDevices, RColorBrewer, ggplot2, rpart, fpc, cluster, rpart.plot, tsne, AnnotationDbi, org.Hs.eg.db, graphics, stats, utils, impute, withr
Suggests: testthat, Seurat
Published: 2023-11-06
Author: Salim Ghannoum [aut, cph], Alvaro Köhn-Luque [aut, ths], Waldir Leoncio [cre, aut], Damiano Fantini [ctb]
Maintainer: Waldir Leoncio <w.l.netto at medisin.uio.no>
BugReports: https://github.com/ocbe-uio/DIscBIO/issues
License: MIT + file LICENSE
URL: https://github.com/ocbe-uio/DIscBIO
NeedsCompilation: no
Materials: NEWS
In views: Omics
CRAN checks: DIscBIO results

Documentation:

Reference manual: DIscBIO.pdf

Downloads:

Package source: DIscBIO_1.2.2.tar.gz
Windows binaries: r-devel: DIscBIO_1.2.2.zip, r-release: DIscBIO_1.2.2.zip, r-oldrel: DIscBIO_1.2.2.zip
macOS binaries: r-release (arm64): DIscBIO_1.2.2.tgz, r-oldrel (arm64): DIscBIO_1.2.2.tgz, r-release (x86_64): DIscBIO_1.2.2.tgz
Old sources: DIscBIO archive

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