SCSilicon: a tool for synthetic single-cell DNA sequencing data generation

SCSilicon: a tool for synthetic single-cell DNA sequencing data generation

Blog Article

Abstract Background Single-cell DNA sequencing is getting indispensable in silicone-toys the study of cell-specific cancer genomics.The performance of computational tools that tackle single-cell genome aberrations may be nevertheless undervalued or overvalued, owing to the insufficient size of benchmarking data.In silicon simulation is a cost-effective approach to generate as many single-cell genomes as possible in a controlled manner to make reliable and valid benchmarking.

Results This study proposes a new tool, SCSilicon, which efficiently generates single-cell in silicon DNA reads with minimum manual intervention.SCSilicon automatically creates a set of genomic aberrations, including SNP, SNV, Indel, and CNV.Besides, SCSilicon yields the ground truth of CNV segmentation breakpoints and subclone cell labels.

We little Girls onepiece suit have manually inspected a series of synthetic variations.We conducted a sanity check of the start-of-the-art single-cell CNV callers and found SCYN was the most robust one.Conclusions SCSilicon is a user-friendly software package for users to develop and benchmark single-cell CNV callers.

Source code of SCSilicon is available at https://github.com/xikanfeng2/SCSilicon.