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) . This package implements extensions of the work published by Ghannoum et. al. (2019) .


Reference manual

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1.2.0 by Waldir Leoncio, 6 months ago


Report a bug at https://github.com/ocbe-uio/DIscBIO/issues

Browse source code at https://github.com/cran/DIscBIO

Authors: Salim Ghannoum [aut, cph] , Alvaro Köhn-Luque [aut, ths] , Waldir Leoncio [cre, aut] , Damiano Fantini [ctb]

Documentation:   PDF Manual  

MIT + file LICENSE license

Imports methods, TSCAN, boot, httr, mclust, statmod, igraph, RWeka, philentropy, NetIndices, png, grDevices, RColorBrewer, ggplot2, rpart, fpc, cluster, rpart.plot, tsne, AnnotationDbi, org.Hs.eg.db, graphics, stats, utils, impute

Depends on SingleCellExperiment

Suggests testthat, Seurat

See at CRAN