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

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.

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

“…Different mutational processes leave distinctive "stamps" of somatic alterations in cancer cells; to discern these patterns, the tool "MUTation AnaLyIS toolKit" (Mutalisk [51]) was utilized. Two signatures, COSMIC 1, the so-called aging signature, and COSMIC 5, are seen as the dominant profiles across our samples (Additional file 1: Figure S5a) which is also in accord with previously detected signatures in GBM [52].…”

“…The mutational signature detection for the cohort was performed with the online tool Mutalisk [51]. VCF files for the cohort were used as inputs, and the maximum likelihood with linear regression options was turned on.…”

Mutational signatures in upper tract urothelial carcinoma define etiologically distinct subtypes with prognostic relevance

“…In multivariate Cox regression proportional analyses adjusted for the effects of standard clinicopathologic variables, mutational subtypes were still an independent risk factor for CSS (Hazard Ratio [HR]=4.05, 95% CI: 1.58~10.42, p=0.004) and MFS (HR=3.43, 95% CI: 1.46~8.06, p=0.006) (table S3). We also used the recently described mutational signature deconvolution method, Mutalisk, for comparison(23). This method was based on different statistical frameworks, and therefore some differences were to be expected.…”

Pathogenic NF1 truncating mutation and copy number alterations in a dedifferentiated liposarcoma with multiple lung metastasis: a case report

“…In order to obtain reliable and robust mutation calling, the following variants were eliminated: (i) read depth fewer than 20 in either the tumor or matched constitutional tissues; (ii) polymorphisms listed in the population databases of East Asians with a minor allele frequency 0.1% or more; and (iii) variant allele frequencies less than 5%. Catalogue of Somatic Mutations in Cancer (COSMIC) mutation signatures were obtained via a Mutalisk package [9] using known mutation signatures of soft-tissue sarcoma [2] (signature 1, 2, 5, and 13). To define CNAs, we used the ngCGH module and SNPRank Segmentation statistical algorithm in NEXUS software 9.0 (Biodiscovery, El Segundo, CA).…”