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Li N, Yang J, Zhu W, Liang Y. MVSC: A Multi-variation Simulator of Cancer Genome. Comb Chem High Throughput Screen 2020; 23:326-333. [PMID: 32183666 DOI: 10.2174/1386207323666200317121136] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2019] [Revised: 11/29/2019] [Accepted: 02/27/2020] [Indexed: 11/22/2022]
Abstract
BACKGROUND Many forms of variations exist in the genome, which are the main causes of individual phenotypic differences. The detection of variants, especially those located in the tumor genome, still faces many challenges due to the complexity of the genome structure. Thus, the performance assessment of variation detection tools using next-generation sequencing platforms is urgently needed. METHOD We have created a software package called the Multi-Variation Simulator of Cancer genomes (MVSC) to simulate common genomic variants, including single nucleotide polymorphisms, small insertion and deletion polymorphisms, and structural variations (SVs), which are analogous to human somatically acquired variations. Three sets of variations embedded in genomic sequences in different periods were dynamically and sequentially simulated one by one. RESULTS In cancer genome simulation, complex SVs are important because this type of variation is characteristic of the tumor genome structure. Overlapping variations of different sizes can also coexist in the same genome regions, adding to the complexity of cancer genome architecture. Our results show that MVSC can efficiently simulate a variety of genomic variants that cannot be simulated by existing software packages. CONCLUSION The MVSC-simulated variants can be used to assess the performance of existing tools designed to detect SVs in next-generation sequencing data, and we also find that MVSC is memory and time-efficient compared with similar software packages.
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Affiliation(s)
- Ning Li
- School of Information and Electronic Engineering, Wuzhou University, Wuzhou, China
| | - Jialiang Yang
- Department of Mathematics and Statistics, Hainan Normal University, Haikou, Hainan 571158, China
| | - Wen Zhu
- Department of Mathematics and Statistics, Hainan Normal University, Haikou, Hainan 571158, China.,College of Computer Science and Electronic Engineering, Hunan University, Hunan, China
| | - Ying Liang
- College of Computer Science and Electronic Engineering, Hunan University, Hunan, China.,College of Computer and Information Engineering, Jiangxi Agricultural University, Nanchang 330000, China
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Bravo GA, Antonelli A, Bacon CD, Bartoszek K, Blom MPK, Huynh S, Jones G, Knowles LL, Lamichhaney S, Marcussen T, Morlon H, Nakhleh LK, Oxelman B, Pfeil B, Schliep A, Wahlberg N, Werneck FP, Wiedenhoeft J, Willows-Munro S, Edwards SV. Embracing heterogeneity: coalescing the Tree of Life and the future of phylogenomics. PeerJ 2019; 7:e6399. [PMID: 30783571 PMCID: PMC6378093 DOI: 10.7717/peerj.6399] [Citation(s) in RCA: 67] [Impact Index Per Article: 13.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2018] [Accepted: 01/07/2019] [Indexed: 12/23/2022] Open
Abstract
Building the Tree of Life (ToL) is a major challenge of modern biology, requiring advances in cyberinfrastructure, data collection, theory, and more. Here, we argue that phylogenomics stands to benefit by embracing the many heterogeneous genomic signals emerging from the first decade of large-scale phylogenetic analysis spawned by high-throughput sequencing (HTS). Such signals include those most commonly encountered in phylogenomic datasets, such as incomplete lineage sorting, but also those reticulate processes emerging with greater frequency, such as recombination and introgression. Here we focus specifically on how phylogenetic methods can accommodate the heterogeneity incurred by such population genetic processes; we do not discuss phylogenetic methods that ignore such processes, such as concatenation or supermatrix approaches or supertrees. We suggest that methods of data acquisition and the types of markers used in phylogenomics will remain restricted until a posteriori methods of marker choice are made possible with routine whole-genome sequencing of taxa of interest. We discuss limitations and potential extensions of a model supporting innovation in phylogenomics today, the multispecies coalescent model (MSC). Macroevolutionary models that use phylogenies, such as character mapping, often ignore the heterogeneity on which building phylogenies increasingly rely and suggest that assimilating such heterogeneity is an important goal moving forward. Finally, we argue that an integrative cyberinfrastructure linking all steps of the process of building the ToL, from specimen acquisition in the field to publication and tracking of phylogenomic data, as well as a culture that values contributors at each step, are essential for progress.
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Affiliation(s)
- Gustavo A. Bravo
- Department of Organismic and Evolutionary Biology, Museum of Comparative Zoology, Harvard University, Cambridge, MA, USA
| | - Alexandre Antonelli
- Department of Organismic and Evolutionary Biology, Museum of Comparative Zoology, Harvard University, Cambridge, MA, USA
- Gothenburg Global Biodiversity Centre, Göteborg, Sweden
- Department of Biological and Environmental Sciences, University of Gothenburg, Göteborg, Sweden
- Gothenburg Botanical Garden, Göteborg, Sweden
| | - Christine D. Bacon
- Gothenburg Global Biodiversity Centre, Göteborg, Sweden
- Department of Biological and Environmental Sciences, University of Gothenburg, Göteborg, Sweden
| | - Krzysztof Bartoszek
- Department of Computer and Information Science, Linköping University, Linköping, Sweden
| | - Mozes P. K. Blom
- Department of Bioinformatics and Genetics, Swedish Museum of Natural History, Stockholm, Sweden
| | - Stella Huynh
- Institut de Biologie, Université de Neuchâtel, Neuchâtel, Switzerland
| | - Graham Jones
- Department of Biological and Environmental Sciences, University of Gothenburg, Göteborg, Sweden
| | - L. Lacey Knowles
- Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI, USA
| | - Sangeet Lamichhaney
- Department of Organismic and Evolutionary Biology, Museum of Comparative Zoology, Harvard University, Cambridge, MA, USA
| | - Thomas Marcussen
- Centre for Ecological and Evolutionary Synthesis, University of Oslo, Oslo, Norway
| | - Hélène Morlon
- Institut de Biologie, Ecole Normale Supérieure de Paris, Paris, France
| | - Luay K. Nakhleh
- Department of Computer Science, Rice University, Houston, TX, USA
| | - Bengt Oxelman
- Gothenburg Global Biodiversity Centre, Göteborg, Sweden
- Department of Biological and Environmental Sciences, University of Gothenburg, Göteborg, Sweden
| | - Bernard Pfeil
- Department of Biological and Environmental Sciences, University of Gothenburg, Göteborg, Sweden
| | - Alexander Schliep
- Department of Computer Science and Engineering, Chalmers University of Technology and University of Gothenburg, Göteborg, Sweden
| | | | - Fernanda P. Werneck
- Coordenação de Biodiversidade, Programa de Coleções Científicas Biológicas, Instituto Nacional de Pesquisa da Amazônia, Manaus, AM, Brazil
| | - John Wiedenhoeft
- Department of Computer Science and Engineering, Chalmers University of Technology and University of Gothenburg, Göteborg, Sweden
- Department of Computer Science, Rutgers University, Piscataway, NJ, USA
| | - Sandi Willows-Munro
- School of Life Sciences, University of Kwazulu-Natal, Pietermaritzburg, South Africa
| | - Scott V. Edwards
- Department of Organismic and Evolutionary Biology, Museum of Comparative Zoology, Harvard University, Cambridge, MA, USA
- Gothenburg Centre for Advanced Studies in Science and Technology, Chalmers University of Technology and University of Gothenburg, Göteborg, Sweden
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