Journal
BMC GENOMICS
Volume 19, Issue -, Pages -Publisher
BMC
DOI: 10.1186/s12864-018-5264-y
Keywords
Mutational signatures; Cancer genomics; Python; Single nucleotide variants
Funding
- U.S. National Institutes of Health [R01GM118928]
Ask authors/readers for more resources
Background: The spectrum of somatic single-nucleotide variants in cancer genomes often reflects the signatures of multiple distinct mutational processes, which can provide clinically actionable insights into cancer etiology. Existing software tools for identifying and evaluating these mutational signatures do not scale to analyze large datasets containing thousands of individuals or millions of variants. Results: We introduce Helmsman, a program designed to perform mutation signature analysis on arbitrarily large sequencing datasets. Helmsman is up to 300 times faster than existing software. Helmsman's memory usage is independent of the number of variants, resulting in a small enough memory footprint to analyze datasets that would otherwise exceed the memory limitations of other programs. Conclusions: Helmsman is a computationally efficient tool that enables users to evaluate mutational signatures in massive sequencing datasets that are otherwise intractable with existing software.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available