IRISFGM

DOI: 10.18129/B9.bioc.IRISFGM  

Comprehensive Analysis of Gene Interactivity Networks Based on Single-Cell RNA-Seq

Bioconductor version: Release (3.16)

Single-cell RNA-Seq data is useful in discovering cell heterogeneity and signature genes in specific cell populations in cancer and other complex diseases. Specifically, the investigation of functional gene modules (FGM) can help to understand gene interactive networks and complex biological processes. QUBIC2 is recognized as one of the most efficient and effective tools for FGM identification from scRNA-Seq data. However, its availability is limited to a C implementation, and its applicative power is affected by only a few downstream analyses functionalities. We developed an R package named IRIS-FGM (integrative scRNA-Seq interpretation system for functional gene module analysis) to support the investigation of FGMs and cell clustering using scRNA-Seq data. Empowered by QUBIC2, IRIS-FGM can identify co-expressed and co-regulated FGMs, predict types/clusters, identify differentially expressed genes, and perform functional enrichment analysis. It is noteworthy that IRIS-FGM also applies Seurat objects that can be easily used in the Seurat vignettes.

Author: Yuzhou Chang [aut, cre], Qin Ma [aut], Carter Allen [aut], Dongjun Chung [aut]

Maintainer: Yuzhou Chang <yuzhou.chang at osumc.edu>

Installation

To install this package, start R (version "4.2") and enter:

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

BiocManager::install("IRISFGM")

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("IRISFGM")

 

HTML	R Script	IRIS-FGM vignette
PDF		Reference Manual
Text		NEWS

Details

biocViews	Clustering, DataImport, DifferentialExpression, DimensionReduction, GeneExpression, Normalization, Preprocessing, SingleCell, Software, Visualization
Version	1.6.0
In Bioconductor since	BioC 3.13 (R-4.1) (2 years)
License	GPL-2
Depends	R (>= 4.1)
Imports	Rcpp (>= 1.0.0), MCL, anocva, Polychrome, RColorBrewer, colorspace, AnnotationDbi, ggplot2, org.Hs.eg.db, org.Mm.eg.db, pheatmap, AdaptGauss, DEsingle, DrImpute, Matrix, Seurat, SingleCellExperiment, clusterProfiler, ggpubr, ggraph, igraph, mixtools, scater, scran, stats, methods, grDevices, graphics, utils, knitr
LinkingTo	Rcpp
Suggests	rmarkdown
SystemRequirements
Enhances
URL
Depends On Me
Imports Me
Suggests Me
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Build Report

Package Archives

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

Source Package	IRISFGM_1.6.0.tar.gz
Windows Binary	IRISFGM_1.6.0.zip (64-bit only)
macOS Binary (x86_64)	IRISFGM_1.6.0.tgz
macOS Binary (arm64)	IRISFGM_1.6.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/IRISFGM
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/IRISFGM
Bioc Package Browser	https://code.bioconductor.org/browse/IRISFGM/
Package Short Url	https://bioconductor.org/packages/IRISFGM/
Package Downloads Report	Download Stats