Background: Accurate detection of copy number aberrations (CNA) can aid in understanding the genetic causes of diseases. Three methods (CopyNumber, Ginkgo, and HMMcopy) have been applied to single-cell DNA sequencing data for CNA detection.
Results:In this paper, we benchmarked these three methods on simulated as well as biological datasets. We found that HMMcopy has the best accuracy of the three methods in terms of breakpoint detection but that Ginkgo is better in terms of detecting the actual copy numbers. In terms of computational requirements, HMMcopy consumes the least memory, but is in between the two other methods in terms of running time.Conclusion: While single-cell DNA sequencing is very promising for elucidating and understanding CNAs, even the best existing method does not exceed 80% accuracy. New methods that significantly improve upon the accuracy of these three methods are needed. Furthermore, with the large datasets being generated, the methods must be computationally efficient.