Delineating the copy-number substructure of metastatic tumors with CopyKit

Tumors are composed of a myriad of subclones that bulk DNA sequencing (DNA-seq) methods cannot accurately resolve. Single-cell DNA-seq methods were developed to address this issue, yet their data analysis remains challenging. Here, we present CopyKit, a comprehensive tool for single-cell DNA copy-number analysis to resolve clonal substructure and reconstruct genetic lineages. Additionally, we introduce "scquantum" to estimate the integer copy-number states of single cells. We performed single-cell DNA-seq of 11,845 cells from one primary breast tumor, two liver metastases, and three primary tumors with matched metastatic tissues. These data identified the subclones from the primary tumors that seeded the metastatic lesions and their associated copy-number events. The data also provided evidence of both subclonal intermixing and spatial segregation in different regions of the liver metastasis. These applications show that CopyKit is a powerful approach for the analysis of high-throughput single-cell copy-number data.