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

ABSTRACT:

Background

Single-cell DNA sequencing is getting indispensable in 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 sub

SUBMITTER: Feng X 

PROVIDER: S-EPMC9092674 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature