Mutalisk: a web-based somatic MUTation AnaLyIS toolKit for genomic, transcriptional and epigenomic signatures
 Authors and Affiliations
 Authors and Affiliations
Jongkeun Lee1,†, Andy Jinseok Lee1,†, June-Koo Lee2,†, Jongkeun Park1, Youngoh Kwon1, Seongyeol Park2, Hyonho Chun3, Young Seok Ju2,*,‡ and Dongwan Hong1,*,‡
1Clinical Genomics Analysis Branch, National Cancer Center, Goyang 10408, Republic of Korea, 2Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology, Daejeon 34141, Republic of Korea and 3Department of Mathematics and Statistics, Boston University, Boston, MA 02215, USA
†The authors wish it to be known that, in their opinion, the first three authors should be regarded as Joint First Authors.
‡Principal investigators with equal contribution.
*Correspondence may also be addressed Young Seok Ju
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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