SGCP
SGCP: A semi-supervised pipeline for gene clustering using self-training approach in gene co-expression networks
Bioconductor version: 3.23 · Package version: 1.12.0
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.
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("SGCP") Details
| Maintainer | Niloofar AghaieAbiane <niloofar.abiane@gmail.com> |
| Author | Niloofar AghaieAbiane [aut, cre] (ORCID: <https://orcid.org/0000-0003-1096-7592>), Ioannis Koutis [aut] |
| License | GPL-3 |
| URL | https://github.com/na396/SGCP |
| Status | Deprecated |
| Downloads rank | 202 |
| Source branch | RELEASE_3_23 |
| biocViews | Classification, Clustering, DimensionReduction, GeneExpression, GeneSetEnrichment, GraphAndNetwork, Network, NetworkEnrichment, NeuralNetwork, RNASeq, Software, SystemsBiology, Visualization, mRNAMicroarray |
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Dependencies
Depends: R (>= 4.2.0)
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, RSpectra, graph
Suggests: knitr, rmarkdown, BiocManager, devtools, BiocStyle