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DESCRIPTION
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DESCRIPTION
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Package: DIscBIO
Date: 2020-02-06
Title: A User-Friendly Pipeline for Biomarker Discovery in Single-Cell Transcriptomics
Version: 0.99.1
Authors@R:
c(
person(given = "Salim",
family = "Ghannoum",
role = c("aut", "cph"),
email = "salim.ghannoum@medisin.uio.no"),
person(given = "Alvaro",
family = "Köhn-Luque",
role = c("aut", "ths"),
email = "alvaro.kohn-luque@medisin.uio.no"),
person(given = "Waldir",
family = "Leoncio",
role = c("cre", "aut"),
email = "w.l.netto@medisin.uio.no"),
person(given = "Damiano",
family = "Fantini",
role = c("ctb"))
)
Description: 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.
<doi:10.1101/700989>.
biocViews: SingleCell, Transcriptomics, Clustering, DecisionTree
License: MIT + file LICENSE
Encoding: UTF-8
Imports: methods, TSCAN, boot, httr, mclust, statmod, biomaRt, samr, igraph,
RWeka, partykit, grid, philentropy, NetIndices, png, matrixStats, grDevices,
readr, RColorBrewer, ggplot2, rpart, fpc, cluster, rpart.plot, amap, dplyr,
tsne, AnnotationDbi, org.Hs.eg.db, calibrate, graphics, stats, utils
Depends:
R (>= 3.6),
Suggests:
knitr,
rmarkdown,
testthat,
enrichR,
Seurat,
SingleCellExperiment
VignetteBuilder: knitr
LazyData: true
RoxygenNote: 7.1.0
BugReports: https://github.com/ocbe-uio/DIscBIO/issues
Collate:
'DIscBIO-classes.R'
'DIscBIO-generic-ClassVectoringDT.R'
'DIscBIO-generic-Clustexp.R'
'DIscBIO-generic-DEGanalysis.R'
'DIscBIO-generic-DEGanalysis2clust.R'
'DIscBIO-generic-Exprmclust.R'
'DIscBIO-generic-FinalPreprocessing.R'
'DIscBIO-generic-FindOutliersKM.R'
'DIscBIO-generic-FindOutliersMB.R'
'DIscBIO-generic-KMClustDiffGenes.R'
'DIscBIO-generic-KMclustheatmap.R'
'DIscBIO-generic-KmeanOrder.R'
'DIscBIO-generic-MBClustDiffGenes.R'
'DIscBIO-generic-MBclustheatmap.R'
'DIscBIO-generic-NoiseFiltering.R'
'DIscBIO-generic-Normalizedata.R'
'DIscBIO-generic-PCAplotSymbols.R'
'DIscBIO-generic-PlotmclustMB.R'
'DIscBIO-generic-comptSNE.R'
'DIscBIO-generic-comptsneMB.R'
'DIscBIO-generic-plotExptSNE.R'
'DIscBIO-generic-plotGap.R'
'DIscBIO-generic-plotKmeansLabelstSNE.R'
'DIscBIO-generic-plotMBLabelstSNE.R'
'DIscBIO-generic-plotOrderKMtsne.R'
'DIscBIO-generic-plotOrderMBtsne.R'
'DIscBIO-generic-plotSilhouette.R'
'DIscBIO-generic-plotSymbolstSNE.R'
'DIscBIO-generic-plotexptsneMB.R'
'DIscBIO-generic-plotsilhouetteMB.R'
'DIscBIO-generic-plottSNE.R'
'DIscBIO-generic-plottsneMB.R'
'J48DT.R'
'J48DTeval.R'
'Jaccard.R'
'MB_Order.R'
'NetAnalysis.R'
'Networking.R'
'PPI.R'
'PlotMBexpPCA.R'
'PlotMBorderPCA.R'
'RpartDT.R'
'RpartEVAL.R'
'VolcanoPlot.R'
'customConverters.R'
'datasets.R'
'retrieveBiomart.R'