Work

Accelerated somatic mutation calling for whole-genome and whole-exome sequencing data from heterogenous tumor samples

Year: 2024

Type: preprint

Abstract: Accurate detection of somatic mutations in DNA sequencing data is a fundamental prerequisite for cancer research. Previous analytical challenge was overcome by consensus mutation calling from four to five popular callers. This, however, increases the already nontrivial computing time from individual callers. Here, we launch MuSE2.0, powered by multi-step parallelization and efficient memory allocation, to resolve the computing time bottleneck. MuSE2.0 speeds up 50 times than MuSE1.0 and 8-80 times than other popular callers. Our benchmark study suggests combining MuSE2.0 and the recently expedited Strelka2 can achieve high efficiency and accuracy in analyzing large cancer genomic datasets.

Source: Genome Research

DOI: 10.1101/gr.278456.123

Authors: Shuangxi Ji, Tong Zhu, Ankit Sethia, Wenyi Wang

Institutions: The University of Texas MD Anderson Cancer Center, Nvidia (United States)

Language: English

Topic: Cancer Genomics and Diagnostics

Subfield: Cancer Research

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: bronze

Funders: National Institutes of Health, University of Texas MD Anderson Cancer Center, National Cancer Institute, DOD Prostate Cancer Research Program