IRISFGM

DOI: 10.18129/B9.bioc.IRISFGM    

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

Bioconductor version: Release (3.14)

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>

Citation (from within R, enter citation("IRISFGM")):

Installation

To install this package, start R (version "4.1") and enter:

if (!requireNamespace("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 1.2.0
In Bioconductor since BioC 3.13 (R-4.1) (0.5 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
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Build Report  

Package Archives

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

Source Package IRISFGM_1.2.0.tar.gz
Windows Binary IRISFGM_1.2.0.zip
macOS 10.13 (High Sierra) IRISFGM_1.2.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/IRISFGM
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/IRISFGM
Package Short Url https://bioconductor.org/packages/IRISFGM/
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Old Source Packages for BioC 3.14 Source Archive

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