# CCRR: a user-friendly platform for analyzing complex chromosomal rearrangements in tumors

**Authors:** Jinjiang Liu, Kun Wang, Yawen Yuan, Guangchao Bao, Hang Ci, Mingqin Liu, Yunpan Lyu, Jingxin Tang, Jian Yang, Haoyang Cai

PMC · DOI: 10.1093/bioinformatics/btaf386 · 2025-07-03

## TL;DR

CCRR is a user-friendly platform that simplifies the analysis of complex chromosomal rearrangements in tumors using integrated tools and automated workflows.

## Contribution

CCRR introduces a comprehensive and reproducible platform for analyzing complex chromosomal rearrangements in tumors with minimal bioinformatics expertise.

## Key findings

- CCRR integrates multiple SV and CNV detection tools in a Docker container environment for simplified deployment.
- The platform provides high-confidence consensus SV and CNV calls through automated execution and result merging.
- CCRR includes a web server for one-click analysis and customized visualization of chromosomal rearrangements.

## Abstract

Complex chromosomal rearrangements in tumors involve intricate genomic alterations that significantly affect gene function and contribute to cancer development. Identifying these events is crucial for cancer research but is often challenging due to the complexity and limitations of existing tools. We developed the Complex Chromosomal Rearrangements Resolver (CCRR), a comprehensive, reproducible, and user-friendly platform for analyzing complex rearrangements in tumors. CCRR integrates multiple SV and CNV detection tools within a Docker container environment, simplifying installation and configuration. It can be easily deployed, automating the execution and merging of results, providing high-confidence consensus SV and CNV calls, allowing researchers to efficiently analyze complex chromosomal rearrangements in tumors without extensive bioinformatics expertise. CCRR also includes a web server for one-click analysis and customized visualization.

The CCRR platform is freely available at https://www.ccrr.life. Source code and executables can be accessed at https://github.com/laslk/CCRR. An archived version is available at Zenodo: https://doi.org/10.5281/zenodo.15386513.

## Full-text entities

- **Diseases:** cancer (MESH:D009369)

## Figures

1 figure with captions in the complete paper: https://tomesphere.com/paper/PMC12258142/full.md

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Source: https://tomesphere.com/paper/PMC12258142