Wang Lab at HKUST

• Software Development: Jiguang Wang, Biaobin Jiang, Dong Song and Quanhua Mu
• Logo Design: Shengshuo Huang

Active Development

Cancer EvoLution for LOngitudinal data (CELLO) is a MATLAB toolbox for comprehensive analysis of longitudinal genomic sequencing data in cancer. It was originally developed by Jiguang Wang [1,2,3], and the implementation has both MATLAB and R versions:

• MATLAB
• R

To ensure reproducibility and improve usability, we have developed a docker version of CELLO, based on the R implementation. To use the docker image, the first step is to install docker in your computer. Please follow the instructions from their website to install it.

The docker image of CELLO can be retrieved by:

docker pull qmu123/cellor

Then you can run CELLO docker to analyze your own longitudinal data. The working directory in the docker image is /home/CELLOR. In order to access your own data at your own folder: /your/local/path inside the docker, you can bind your own folder to a directory within the docker at, for example, /home/data using the following command:

docker run -it --rm -v /your/local/path/:/home/data qmu123/cellor

This runs the docker in an interactive mode, so you can follow the CELLOR tutorial to analyze your data step by step. By default the resulting figures are placed at the /home/CELLOR folder, and you can move them to your local folder after completing the analysis.

Finally, if one wants to make changes to the docker image, the docker file is also available at this repository. Please download the Dockerfile and CELLO.R into a directory, then you can make your changes and build your new image using:

docker build -t cellor .

• The input SAVI report consists of a list of genetic variants from 90 glioblastoma patients before and after treatment [2].
• The additional glioblastoma data (either treated or untreated) for hypermutation detection are available from 43 samples of whole-exome sequencing, 63 samples of targeted-DNA sequencing, and 51 samples of RNA sequencing [3].
• Note that the germline mutations have been removed from all the above shared data for protection of individual privacy.

If you use CELLO in your research, please cite:

Biaobin Jiang*, Dong Song*, Quanhua Mu, and Jiguang Wang#. (2020). CELLO: a longitudinal data analysis toolbox untangling cancer evolution. Quantitative Biology, Link.

[1] Jiguang Wang, Hossein Khiabanian, Davide Rossi, Giulia Fabbri, Valter Gattei, Francesco Forconi, Luca Laurenti, Roberto Marasca, Giovanni Del Poeta, Robin Foà, Laura Pasqualucci, Gianluca Gaidano, Raul Rabadan. (2014). Tumor evolutionary directed graphs and the history of chronic lymphocytic leukemia. Elife, 3, e02869.

[2] Jiguang Wang, Emanuela Cazzato, Erik Ladewig, Veronique Frattini, Daniel I S Rosenbloom, Sakellarios Zairis, Francesco Abate, Zhaoqi Liu, Oliver Elliott, Yong-Jae Shin, Jin-Ku Lee, In-Hee Lee, Woong-Yang Park, Marica Eoli, Andrew J Blumberg, Anna Lasorella, Do-Hyun Nam, Gaetano Finocchiaro, Antonio Iavarone, Raul Rabadan. (2016). Clonal evolution of glioblastoma under therapy. Nature Genetics, 48(7), 768-776.

[3] Huimin Hu*, Quanhua Mu*, Zhaoshi Bao*, Yiyun Chen*, Yanwei Liu*, Jing Chen, Kuanyu Wang, Zheng Wang, Yoonhee Nam, Biaobin Jiang, Jason K. Sa, Hee-Jin Cho, Nam-Gu Her, Chuanbao Zhang, Zheng Zhao, Ying Zhang, Fan Zeng, Fan Wu, Xun Kang, Yuqing Liu, Zenghui Qian, Zhiliang Wang, Ruoyu Huang, Qiangwei Wang, Wei Zhang, Xiaoguang Qiu, Wenbin Li, Do-Hyun Nam, Xiaolong Fan#, Jiguang Wang#, Tao Jiang#. (2018). Mutational landscape of secondary glioblastoma guides MET-targeted trial in brain tumor. Cell, 175(6), 1665-1678.

For any questions, please contact Professor Jiguang Wang via email: jgwang AT ust DOT hk