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. This package implements extensions of the work published by Ghannoum et. al. (2019) <doi:10.1101/700989>.
Version: | 1.1.0 |
Depends: | R (≥ 4.0), SingleCellExperiment |
Imports: | methods, TSCAN, boot, httr, mclust, statmod, igraph, RWeka, philentropy, NetIndices, png, grDevices, readr, RColorBrewer, ggplot2, rpart, fpc, cluster, rpart.plot, tsne, AnnotationDbi, org.Hs.eg.db, graphics, stats, utils, impute |
Suggests: | testthat, Seurat |
Published: | 2020-11-13 |
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 |
CRAN checks: | DIscBIO results |
Reference manual: | DIscBIO.pdf |
Package source: | DIscBIO_1.1.0.tar.gz |
Windows binaries: | r-devel: DIscBIO_1.1.0.zip, r-release: DIscBIO_1.1.0.zip, r-oldrel: not available |
macOS binaries: | r-release: not available, r-oldrel: not available |
Old sources: | DIscBIO archive |
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