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>).
Package details |
|
|---|---|
| Author | Dongqiang Zeng [aut], Yiran Fang [aut], Shixiang Wang [aut, cre] (ORCID: <https://orcid.org/0000-0001-9855-7357>), Qingcong Luo [aut], Hongqian Qian [aut] |
| Bioconductor views | Clustering DifferentialExpression GeneExpression ImmunoOncology Survival Transcriptomics Visualization |
| Maintainer | Shixiang Wang <w_shixiang@163.com> |
| License | GPL-3 |
| Version | 2.2.3 |
| URL | https://doi.org/10.3389/fimmu.2021.687975 (paper) https://iobr.github.io/book/ (docs) https://iobr.github.io/IOBR/ |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
|
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.