SGCP

DOI: 10.18129/B9.bioc.SGCP  

This package is for version 3.17 of Bioconductor; for the stable, up-to-date release version, see SGCP.

SGCP: A semi-supervised pipeline for gene clustering using self-training approach in gene co-expression networks

Bioconductor version: 3.17

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.

Author: Niloofar AghaieAbiane [aut, cre] , Ioannis Koutis [aut]

Maintainer: Niloofar AghaieAbiane <niloofar.abiane at gmail.com>

Installation

To install this package, start R (version "4.3") and enter:

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("SGCP")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("SGCP")

 

HTML	R Script	SGCP package manual
PDF		Reference Manual
Text		NEWS

Details

biocViews	Classification, Clustering, DimensionReduction, GeneExpression, GeneSetEnrichment, GraphAndNetwork, Network, NetworkEnrichment, NeuralNetwork, RNASeq, Software, SystemsBiology, Visualization, mRNAMicroarray
Version	1.0.0
In Bioconductor since	BioC 3.17 (R-4.3) (< 6 months)
License	GPL-3
Depends	R (>= 4.3.0)
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
LinkingTo
Suggests	knitr, BiocManager
SystemRequirements
Enhances
URL	https://github.com/na396/SGCP
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package	SGCP_1.0.0.tar.gz
Windows Binary	SGCP_1.0.0.zip
macOS Binary (x86_64)	SGCP_1.0.0.tgz
macOS Binary (arm64)	SGCP_1.0.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/SGCP
Source Repository (Developer Access)	git clone [email protected]:packages/SGCP
Bioc Package Browser	https://code.bioconductor.org/browse/SGCP/
Package Short Url	https://bioconductor.org/packages/SGCP/
Package Downloads Report	Download Stats