bioc-issue-bot
commented
2 years ago Hi @na396
Thanks for submitting your package. We are taking a quick look at it and you will hear back from us soon.
The DESCRIPTION file for this package is:
Package: SGCP
Type: Package
Title: SGCP: A semi-supervised pipeline for gene clustering using self-training approach in gene co-expression networks
Version: 0.99.0
Authors@R: c(person("Niloofar", "AghaieAbiane", email = "niloofar.abiane@gmail.com" ,role = c("aut", "cre")),
person("Ioannis", "Koutis", email = " ikoutis@njit.edu",role = c("aut")))
Description: SGC is a semi-supervised pipeline for gene clustering in gene co-expression networks.
SGC consists of multiple novel steps that enable the computation of highly enriched modules
in an unsupervised manner. But unlike all existing frameworks, it further incorporates a
novel step that leverages Gene Ontology information in a semi-supervised clustering method
that further improves the quality of the computed modules.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: ggplot2, expm, caret, plyr, dplyr, GO.db, annotate, SummarizedExperiment,
genefilter, GOstats, RColorBrewer, xtable, Rgraphviz, reshape2, openxlsx,
ggridges, DescTools, org.Hs.eg.db, methods, grDevices, stats
Suggests: knitr
Depends: R (>= 4.2.0)
biocViews: GeneExpression, GeneSetEnrichment, NetworkEnrichment, SystemsBiology,
Classification, Clustering, DimensionReduction, GraphAndNetwork,
NeuralNetwork, Network, mRNAMicroarray, RNASeq, Visualization
VignetteBuilder: knitr
NeedsCompilation: no
URL: https://github.com/na396/SGC
Date/Publication: 2022-10-06
RoxygenNote: 7.2.1
na396
lshep
vjcitn
jianhong
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