IRISFGM
This is the development version of IRISFGM; for the stable release version, see IRISFGM.
Comprehensive Analysis of Gene Interactivity Networks Based on Single-Cell RNA-Seq
Bioconductor version: Development (3.18)
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("IRISFGM")):
Installation
To install this package, start R (version "4.3") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
# The following initializes usage of Bioc devel
BiocManager::install(version='devel')
BiocManager::install("IRISFGM")For older versions of R, please refer to the appropriate Bioconductor release.
Documentation
| Reference Manual |
Details
| biocViews | Clustering, DataImport, DifferentialExpression, DimensionReduction, GeneExpression, Normalization, Preprocessing, SingleCell, Software, Visualization |
| Version | 1.9.0 |
| 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 |
| Linking To | Rcpp |
| Suggests | rmarkdown |
| System Requirements | |
| Enhances | |
| URL |
See More
| 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 | |
| Windows Binary | IRISFGM_1.9.0.zip (64-bit only) |
| macOS Binary (x86_64) | IRISFGM_1.9.0.tgz |
| 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 |
| Bioc Package Browser | https://code.bioconductor.org/browse/IRISFGM/ |
| Package Short Url | https://bioconductor.org/packages/IRISFGM/ |
| Package Downloads Report | Download Stats |