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Clonal Structure Identification through Pairwise Penalization
Tumor subclonal architecture shapes cancer evolution, yet subclonal reconstruction from bulk sequencing remains difficult to scale due to computational cost and model complexity. We developed Clonal Structure Identification through Pairwise Penalization (CliPP) , a penalized-likelihood framework that jointly estimates cellular prevalence with pairwise fusion penalties, automatically identifying subclones without requiring extensive priors, which enables fast and accurate subclonal reconstruction.
Using CliPP on Web, users may upload their own samples for fast subclonal reconstruction using our easy to navigate user interface. We also present the subclonal reconstruction results for 2,675 TCGA samples and 1,312 PCAWG samples.
Jiang, Y., Montierth, M.D., Ding, Y., Yu, K., Tran, Q., Wu, A., Li, R., Ji, S., Liu, X., Shin, S.J., Cao, S., Tang, Y., Lesluyes, T., Kimmel, M., Wang, J.R., Tarabichi, M., Zhu, H., Van Loo, P., & Wang, W. Scalable subclonal reconstruction of cancer cells in DNA sequencing data using a penalized likelihood model. bioRxiv (2021).
https://www.biorxiv.org/content/10.1101/2021.03.31.437383v2@article{jiang2021clipp,
title = {Scalable subclonal reconstruction of cancer cells in DNA sequencing data using a penalized likelihood model},
author = {Jiang, Yujie and Montierth, Matthew D and Ding, Y and Yu, Kaixian and Tran, Quang and Wu, Aaron and Li, Ruonan and Ji, Shuangxi and Liu, Xiaoqian and Shin, Seung Jun and Cao, Shaolong and Tang, Yuxin and Lesluyes, Tom and Kimmel, Marek and Wang, Jennifer R and Tarabichi, Maxime and Zhu, Hongtu and Van Loo, Peter and Wang, Wenyi},
journal = {bioRxiv},
year = {2021},
doi = {10.1101/2021.03.31.437383}
}
If you use this data in your research, please cite:
All data is provided for research purposes. Please follow the data usage policies of the respective consortiums.
Explore subclonal reconstruction results from 2,675 TCGA samples and 1,312 PCAWG samples. For each sample, we provide a visualization of subclonal reconstruction results and subclonal mutation fraction (sMF) calculation. Samples included in our data exploration all passed our filtering criteria, having more than 20 and less than 20,000 SNVs, and number of reads per chromosomal copy (nrpcc) value greater than 10. Additional sample filtering was performed based on quality control of copy number calls. For more details please see our pre-print . To download the full datasets, visit the Downloads page .
Explore driver mutation annotation for mutations in 289 genes across 2,172 TCGA samples from 28 cancer types. Driver mutation lists were obtained from IntOGen (Martínez-Jiménez et al., Nature Reviews Cancer , 2020).
| DATASET | DESCRIPTION | TYPE | SIZE | ACTION |
|---|---|---|---|---|
| CliPPSim4k Input Data | Per-sample SNV, CNA, and purity input files for 4,050 simulated samples | ZIP | 4.2 GB | Download ZIP |
| CliPPSim4k Results | CliPP subclonal reconstruction output for 4,050 simulated samples | ZIP | 45 MB | Download ZIP |
| DATASET | DESCRIPTION | TYPE | SIZE | ACTION |
|---|---|---|---|---|
| Per-sample CliPP results | Individual clonal structure outputs - zip archive | ZIP | 372 MB | Download ZIP |
| DATASET | DESCRIPTION | TYPE | SIZE | ACTION |
|---|---|---|---|---|
| Per-sample CliPP outputs | Cluster assignments and CCF estimates for every PCAWG tumor | ZIP | 2.8 GB | Download ZIP |
| DATASET | DESCRIPTION | TYPE | SIZE | ACTION |
|---|---|---|---|---|
| Driver mutation data | Driver mutations with VAF, CP, clonality, and clinical annotations for all TCGA samples | CSV | ~12 MB | Download |
If you encounter problems with downloads, contact pandachessaaron@gmail.com or MDMontierth@mdanderson.org .