IOBR: Immune Oncology Biological Research

Provides six modules for tumor microenvironment (TME) analysis based on multi-omics data. These modules cover data preprocessing, TME estimation, TME infiltrating patterns, cellular interactions, genome and TME interaction, and visualization for TME relevant features, as well as modelling based on key features. It integrates multiple microenvironmental analysis algorithms and signature estimation methods, simplifying the analysis and downstream visualization of the TME. In addition to providing a quick and easy way to construct gene signatures from single-cell RNA-seq data, it also provides a way to construct a reference matrix for TME deconvolution from single-cell RNA-seq data. The analysis pipeline and feature visualization are user-friendly and provide a comprehensive description of the complex TME, offering insights into tumour-immune interactions (Zeng D, et al. (2024) <doi:10.1016/j.crmeth.2024.100910>. Fang Y, et al. (2025) <doi:10.1002/mdr2.70001>).

Version:	2.2.0
Depends:	R (≥ 3.6.0)
Imports:	cli, dplyr, ggplot2, glmnet, GSVA, methods, purrr, rlang, stringr, survival, survminer, tibble, tidyr
Suggests:	BiocParallel, biomaRt, circlize, clusterProfiler, ComplexHeatmap, corrplot, DESeq2, doParallel, DOSE, e1071, easier, enrichplot, factoextra, FactoMineR, foreach, ggdensity, ggpp, ggpubr, ggsci, gridExtra, Hmisc, knitr, limma, limSolve, maftools, MASS, Matrix, msigdbr, NbClust, org.Hs.eg.db, org.Mm.eg.db, patchwork, PMCMRplus, pracma, preprocessCore, prettydoc, pROC, psych, RColorBrewer, reshape2, rmarkdown, ROCR, sampling, scales, Seurat, SeuratObject, sva, testthat (≥ 3.0.0), tidyHeatmap, timeROC, webr, WGCNA
Published:	2026-04-22
DOI:	10.32614/CRAN.package.IOBR
Author:	Dongqiang Zeng [aut], Yiran Fang [aut], Shixiang Wang [aut, cre], Qingcong Luo [aut], Hongqian Qian [aut]
Maintainer:	Shixiang Wang <w_shixiang at 163.com>
BugReports:	https://github.com/IOBR/IOBR/issues
License:	GPL-3
URL:	https://doi.org/10.3389/fimmu.2021.687975 (paper), https://iobr.github.io/book/ (docs), https://iobr.github.io/IOBR/
NeedsCompilation:	no
Citation:	IOBR citation info
Materials:	README, NEWS
CRAN checks:	IOBR results

Documentation:

Reference manual:	IOBR.html , IOBR.pdf
Vignettes:	IOBR User Manual (source, R code)

Downloads:

Package source:	IOBR_2.2.0.tar.gz
Windows binaries:	r-release: IOBR_2.2.0.zip, r-oldrel: IOBR_2.2.0.zip
macOS binaries:	r-release (arm64): IOBR_2.2.0.tgz, r-oldrel (arm64): not available, r-release (x86_64): IOBR_2.2.0.tgz, r-oldrel (x86_64): IOBR_2.2.0.tgz

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