IOBRportal is an R package and Shiny-based web platform for bulk transcriptome and immuno-oncology studies. It integrates signature score calculation, TME deconvolution, clustering, visualization, mutation analysis, signature-gene correlation analysis and cohort-oriented workflows into a unified analysis environment. More information is available in the IOBRportal Book. Access the application here: https://iobr.github.io/IOBRportal/.
IOBRportal is designed to connect data preparation, feature generation, statistical analysis, and interactive visualization in one package-oriented framework. It supports both module-level analyses and workflow-level pipelines, allowing users to move from raw expression matrices or curated cohort tables to interpretable results in a reproducible manner.
This workflow is designed for user-uploaded data and supports:
- counts to TPM conversion
- outlier detection
- signature scoring or TME deconvolution
- clustering
- phenotype combination
- downstream visualization and statistical analysis
This workflow supports:
- mutation matrix construction from MAF files
- phenotype-associated mutation analysis
- oncoprint generation
- mutation-associated boxplot generation
This workflow supports:
- TPM preprocessing
- outlier removal
- signature calculation
- signature-gene correlation analysis
- correlation matrix construction
This workflow is designed for TCGA cohort analysis and supports:
- cohort selection
- signature or TME data preparation
- clustering
- visualization
- survival analysis
- correlation analysis
- group comparison
This workflow is designed for curated cancer cohort datasets and supports:
- data selection
- signature or TME preparation
- clustering
- visualization
- correlation analysis
- group comparison
This workflow is designed for immunotherapy-focused datasets and supports:
- filtering by cancer type, treatment, drug, and timepoint
- signature or TME extraction
- clustering
- visualization
- correlation analysis
- group comparison
This workflow is designed for CPTAC/TARGET-style datasets and supports:
- cohort selection
- signature or TME data preparation
- clustering
- visualization
- survival analysis
- correlation analysis
- group comparison
- PCA-based signature scoring
- ssGSEA-based signature scoring
- Z-score-based signature scoring
- multiple built-in signature collections
- CIBERSORT
- EPIC
- quanTIseq
- xCell
- ESTIMATE
- TIMER
- MCPcounter
- IPS
- integration mode for combined TME estimation
- batch correlation
- partial correlation
- batch survival screening
- Wilcoxon test
- Kruskal-Wallis test
- heatmap
- box plot
- percent bar plot
- cell bar plot
- forest plot
- correlation plot
- correlation matrix plot
- survival plot
- survival group plot
- time-dependent ROC plot
- signature ROC plot
- gsea plot
Typical outputs generated by IOBRportal include:
- processed expression matrices
- signature score matrices
- TME deconvolution tables
- cluster assignments
- combined phenotype-feature tables
- survival statistics
- correlation statistics
- group comparison results
- mutation result tables
- publication-ready figures
If you use IOBRportal in your work, please cite:
- the IOBRportal package paper or preprint, when available
- the original methods implemented in the package, such as CIBERSORT, EPIC, xCell, ESTIMATE, TIMER, MCPcounter, quanTIseq, IPS, and related statistical tools
E-mail questions or bug reports to:
- Qingcong Luo (qingcongl@163.com)
- Dr. Dongqiang Zeng (interlaken@smu.edu.cn)
IOBRportal is released under the GNU General Public License v3.0 (GPL-3).