bioc-issue-bot
commented
3 years ago Hi @ilyessr
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The DESCRIPTION file for this package is:
Package: conclus
Title: ScRNA-seq Workflow CONCLUS - From CONsensus CLUSters To A Meaningful CONCLUSion
Version: 0.99.0
Authors@R: c(
person("Ilyess", "Rachedi", email = "ilyessr@hotmail.fr", role = "cre"),
person("Nicolas", "Descostes", email = "nicolas.descostes@embl.it", role = "aut"),
person("Polina", " Pavlovich", email = "pavlovich@ie-freiburg.mpg.de", role = "aut"),
person("Christophe", "Lancrin", email = "christophe.lancrin@embl.it", role = "aut"))
Description:
CONCLUS is a tool for robust clustering and positive marker features
selection of single-cell RNA-seq (sc-RNA-seq) datasets. It takes advantage
of a consensus clustering approach that greatly simplify sc-RNA-seq data
analysis for the user. Of note, CONCLUS does not cover the preprocessing
steps of sequencing files obtained following next-generation sequencing.
CONCLUS is organized into the following steps:
Generation of multiple t-SNE plots with a range of parameters including
different selection of genes extracted from PCA. Use the Density-based
spatial clustering of applications with noise (DBSCAN) algorithm for
idenfication of clusters in each generated t-SNE plot. All DBSCAN results
are combined into a cell similarity matrix. The cell similarity matrix is
used to define "CONSENSUS" clusters conserved accross the previously
defined clustering solutions. Identify marker genes for each concensus
cluster.
Depends: R (>= 4.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Suggests:
knitr,
rmarkdown,
BiocStyle,
S4Vectors,
matrixStats,
org.Hs.eg.db,
org.Mm.eg.db,
dynamicTreeCut,
testthat
VignetteBuilder: knitr
Imports:
dbscan,
fpc,
factoextra,
Biobase,
parallel,
doParallel,
foreach,
SummarizedExperiment,
biomaRt,
AnnotationDbi,
methods,
dplyr,
scran,
scater,
pheatmap,
ggplot2,
gridExtra,
SingleCellExperiment,
stats,
utils,
scales,
grDevices,
graphics,
Rtsne,
GEOquery,
clusterProfiler,
stringr
biocViews:
Software,
Technology,
SingleCell,
Sequencing,
Clustering,
ATACSeq,
Classification
Collate:
'AllClasses.R'
'AllGenerics.R'
'DataFormatting.R'
'checkFunctions.R'
'constructors.R'
'getters.R'
'globalVar.R'
'loadDataset.R'
'methods-clustering.R'
'methods-dbscan.R'
'methods-export.R'
'methods-markers.R'
'methods-normalization.R'
'sharedInternals.R'
'methods-plot.R'
'methods-tsne.R'
'runCONCLUS.R'
'setters.R'
lshep
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