PyClone-VI: Scalable inference of clonal population structures using whole genome data

We describe PyClone-VI, a computationally efficient Bayesian statistical method for inferring the clonal population structure of cancers. Our proposed method is 10-100x times faster than existing methods, while providing results which are as accurate. We demonstrate the utility of the method by analyzing data from 1717 patients from PCAWG study and 100 patients from the TRACERx study. Software implementing our method is freely available https://github.com/Roth-Lab/pyclone-vi.