Publikation:

Uncovering novel mutational signatures by de novo extraction with SigProfilerExtractor

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Islam_2-1dbw5dkpf7ikh0.pdf
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2022

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Islam, S.M. Ashiqul
Díaz-Gay, Marcos
Wu, Yang
Barnes, Mark
Vangara, Raviteja
Bergstrom, Erik N.
He, Yudou
Vella, Mike
Alexandrov, Ludmil B.
et al.

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Published

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Cell Genomics. Elsevier. 2022, 2(11), 100179. eISSN 2666-979X. Available under: doi: 10.1016/j.xgen.2022.100179

Zusammenfassung

Mutational signature analysis is commonly performed in cancer genomic studies. Here, we present SigProfilerExtractor, an automated tool for de novo extraction of mutational signatures, and benchmark it against another 13 bioinformatics tools by using 34 scenarios encompassing 2,500 simulated signatures found in 60,000 synthetic genomes and 20,000 synthetic exomes. For simulations with 5% noise, reflecting high-quality datasets, SigProfilerExtractor outperforms other approaches by elucidating between 20% and 50% more true-positive signatures while yielding 5-fold less false-positive signatures. Applying SigProfilerExtractor to 4,643 whole-genome- and 19,184 whole-exome-sequenced cancers reveals four novel signatures. Two of the signatures are confirmed in independent cohorts, and one of these signatures is associated with tobacco smoking. In summary, this report provides a reference tool for analysis of mutational signatures, a comprehensive benchmarking of bioinformatics tools for extracting signatures, and several novel mutational signatures, including one putatively attributed to direct tobacco smoking mutagenesis in bladder tissues.

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570 Biowissenschaften, Biologie

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mutagenesis, mutational signatures, cancer genomics, genomics

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ISO 690ISLAM, S.M. Ashiqul, Marcos DÍAZ-GAY, Yang WU, Mark BARNES, Raviteja VANGARA, Erik N. BERGSTROM, Yudou HE, Mike VELLA, Andreas J. GRUBER, Ludmil B. ALEXANDROV, 2022. Uncovering novel mutational signatures by de novo extraction with SigProfilerExtractor. In: Cell Genomics. Elsevier. 2022, 2(11), 100179. eISSN 2666-979X. Available under: doi: 10.1016/j.xgen.2022.100179
BibTex
@article{Islam2022Uncov-66400,
  year={2022},
  doi={10.1016/j.xgen.2022.100179},
  title={Uncovering novel mutational signatures by de novo extraction with SigProfilerExtractor},
  number={11},
  volume={2},
  journal={Cell Genomics},
  author={Islam, S.M. Ashiqul and Díaz-Gay, Marcos and Wu, Yang and Barnes, Mark and Vangara, Raviteja and Bergstrom, Erik N. and He, Yudou and Vella, Mike and Gruber, Andreas J. and Alexandrov, Ludmil B.},
  note={Article Number: 100179}
}
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