CNpare: matching DNA copy number profiles

Abstract

Abstract Selecting the optimal cancer cell line for an experiment can be challenging given the diversity of lines available. Cell lines are often chosen based on their tissue of origin, however, the results of large-scale pan-cancer studies suggest that matching lines based on molecular features may be more appropriate. Existing approaches are available for matching lines based on gene expression, DNA methylation or low resolution DNA copy number features. However, a specific tool for computing similarity based on high resolution genome-wide copy number profiles is lacking. Here, we present CNpare, which identifies similar cell line models based on genome-wide DNA copy number. CNpare compares copy number profiles using four different similarity metrics, quantifies the extent of genome differences between pairs, and facilitates comparison based on copy number signatures. CNpare incorporates a precomputed database of 1,170 human cancer cell line profiles for comparison. In an analysis of separate cultures of 304 cell line pairs, CNpare identified the matched lines in all cases. CNpare provides a powerful solution to the problem of selecting the best cell line models for cancer research, especially in the context of studying chromosomal instability.