IRISFGM

This package is deprecated. It will probably be removed from Bioconductor. Please refer to the package end-of-life guidelines for more information.

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


Bioconductor version: Release (3.19)

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 "4.4") 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

Reference Manual PDF

Details

biocViews Clustering, DataImport, DifferentialExpression, DimensionReduction, GeneExpression, Normalization, Preprocessing, SingleCell, Software, Visualization
Version 1.12.0
In Bioconductor since BioC 3.13 (R-4.1) (3.5 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
System Requirements
URL
See More
Suggests rmarkdown
Linking To Rcpp
Enhances
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report Build Report

Package Archives

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

Source Package
Windows Binary
macOS Binary (x86_64)
macOS Binary (arm64)
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/
Package Downloads Report Download Stats