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MSA: reproducible mutational signature attribution with confidence based on simulations.

Sergey Senkin
Published in: BMC bioinformatics (2021)
MSA is a tool for optimised mutational signature attribution based on simulations, providing confidence intervals using parametric bootstrap. It comprises a set of Python scripts unified in a single Nextflow pipeline with containerisation for cross-platform reproducibility and scalability in high-performance computing environments. The tool is publicly available from https://gitlab.com/s.senkin/MSA .
Keyphrases
  • molecular dynamics
  • monte carlo
  • high throughput