Literature DB >> 29790943

Mutalisk: a web-based somatic MUTation AnaLyIS toolKit for genomic, transcriptional and epigenomic signatures.

Jongkeun Lee1, Andy Jinseok Lee1, June-Koo Lee2, Jongkeun Park1, Youngoh Kwon1, Seongyeol Park2, Hyonho Chun3, Young Seok Ju2, Dongwan Hong1.   

Abstract

Somatic genome mutations occur due to combinations of various intrinsic/extrinsic mutational processes and DNA repair mechanisms. Different molecular processes frequently generate different signatures of somatic mutations in their own favored contexts. As a result, the regional somatic mutation rate is dependent on the local DNA sequence, the DNA replication/RNA transcription dynamics and epigenomic chromatin organization landscape in the genome. Here, we propose an online computational framework, termed Mutalisk, which correlates somatic mutations with various genomic, transcriptional and epigenomic features in order to understand mutational processes that contribute to the generation of the mutations. This user-friendly tool explores the presence of localized hypermutations (kataegis), dissects the spectrum of mutations into the maximum likelihood combination of known mutational signatures and associates the mutation density with numerous regulatory elements in the genome. As a result, global patterns of somatic mutations in any query sample can be efficiently screened, thus enabling a deeper understanding of various mutagenic factors. This tool will facilitate more effective downstream analyses of cancer genome sequences to elucidate the diversity of mutational processes underlying the development and clonal evolution of cancer cells. Mutalisk is freely available at http://mutalisk.org.

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Year:  2018        PMID: 29790943      PMCID: PMC6030918          DOI: 10.1093/nar/gky406

Source DB:  PubMed          Journal:  Nucleic Acids Res        ISSN: 0305-1048            Impact factor:   16.971


  26 in total

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2.  Chromatin organization is a major influence on regional mutation rates in human cancer cells.

Authors:  Benjamin Schuster-Böckler; Ben Lehner
Journal:  Nature       Date:  2012-08-23       Impact factor: 49.962

3.  A comprehensive catalogue of somatic mutations from a human cancer genome.

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Journal:  Nature       Date:  2002-06-09       Impact factor: 49.962

7.  DeconstructSigs: delineating mutational processes in single tumors distinguishes DNA repair deficiencies and patterns of carcinoma evolution.

Authors:  Rachel Rosenthal; Nicholas McGranahan; Javier Herrero; Barry S Taylor; Charles Swanton
Journal:  Genome Biol       Date:  2016-02-22       Impact factor: 13.583

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Journal:  Nature       Date:  2012-09-06       Impact factor: 49.962

10.  Deciphering signatures of mutational processes operative in human cancer.

Authors:  Ludmil B Alexandrov; Serena Nik-Zainal; David C Wedge; Peter J Campbell; Michael R Stratton
Journal:  Cell Rep       Date:  2013-01-10       Impact factor: 9.423

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Review 2.  Computational tools to detect signatures of mutational processes in DNA from tumours: A review and empirical comparison of performance.

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Journal:  PLoS One       Date:  2019-09-12       Impact factor: 3.240

3.  MetaMutationalSigs: Comparison of mutational signature refitting results made easy.

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4.  Rates and Patterns of Clonal Oncogenic Mutations in the Normal Human Brain.

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5.  Patient-derived organoids as a preclinical platform for precision medicine in colorectal cancer.

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6.  Brain somatic mutations observed in Alzheimer's disease associated with aging and dysregulation of tau phosphorylation.

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7.  Whole-genome sequencing of glioblastoma reveals enrichment of non-coding constraint mutations in known and novel genes.

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Journal:  Genome Biol       Date:  2020-06-09       Impact factor: 13.583

8.  Prexasertib (LY2606368) reduces clonogenic survival by inducing apoptosis in primary patient-derived osteosarcoma cells and synergizes with cisplatin and talazoparib.

Authors:  Christopher L Heidler; Eva K Roth; Markus Thiemann; Claudia Blattmann; Ramon L Perez; Peter E Huber; Michal Kovac; Beate Amthor; Gabriele Neu-Yilik; Andreas E Kulozik
Journal:  Int J Cancer       Date:  2019-12-19       Impact factor: 7.396

9.  Genome-wide methylation patterns predict clinical benefit of immunotherapy in lung cancer.

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Journal:  Clin Epigenetics       Date:  2020-08-06       Impact factor: 6.551

10.  Helmsman: fast and efficient mutation signature analysis for massive sequencing datasets.

Authors:  Jedidiah Carlson; Jun Z Li; Sebastian Zöllner
Journal:  BMC Genomics       Date:  2018-11-28       Impact factor: 3.969

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