Resolving clonal substructure from single cell genomic data using CopyKit

Abstract

High-throughput methods for single cell copy number sequencing have enabled the profiling of thousands of cells in parallel, yet there remains a significant bottleneck for data analysis. Here we present CopyKit, a comprehensive set of computational methods for the pre-processing and analysis of single cell copy number data to resolve clonal substructure and reconstruct genetic lineages in tumors. We performed single cell DNA sequencing of 2977 cells from multiple spatial regions in two liver metastasis and 7365 cells from three primary tumors with matched metastatic tissues. In the liver metastases, CopyKit resolved clonal substructure in different spatial regions, which revealed both clonal intermixing and spatial segregation in the tumor mass. In the matched metastatic colorectal and breast cancers, CopyKit resolved metastatic lineages and identified subclones and genomic events that were associated with metastases. These applications show that CopyKit is comprehensive tool for resolving copy number substructure in tumors.