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VIVID: A Web Application for Variant Interpretation and Visualization in Multi-dimensional Analyses.
Tichkule, Swapnil; Myung, Yoochan; Naung, Myo T; Ansell, Brendan R E; Guy, Andrew J; Srivastava, Namrata; Mehra, Somya; Cacciò, Simone M; Mueller, Ivo; Barry, Alyssa E; van Oosterhout, Cock; Pope, Bernard; Ascher, David B; Jex, Aaron R.
Affiliation
  • Tichkule S; Population Health and Immunity, Walter and Eliza Hall Institute of Medical Research, Melbourne, Australia.
  • Myung Y; Department of Medical Biology, University of Melbourne, Melbourne, Australia.
  • Naung MT; Systems and Computational Biology, Bio21 Institute, University of Melbourne, Melbourne, Australia.
  • Ansell BRE; Computational Biology and Clinical Informatics, Baker Heart and Diabetes, Melbourne, Australia.
  • Guy AJ; Population Health and Immunity, Walter and Eliza Hall Institute of Medical Research, Melbourne, Australia.
  • Srivastava N; Department of Medical Biology, University of Melbourne, Melbourne, Australia.
  • Mehra S; Population Health and Immunity, Walter and Eliza Hall Institute of Medical Research, Melbourne, Australia.
  • Cacciò SM; School of Science, RMIT University, Melbourne, Australia.
  • Mueller I; Department of Data Science and AI, Monash University, Melbourne, Australia.
  • Barry AE; Life Sciences Discipline, Burnet Institute, Melbourne, Australia.
  • van Oosterhout C; Department of Infectious Disease, Istituto Superiore di Sanità, Rome, Italy.
  • Pope B; Population Health and Immunity, Walter and Eliza Hall Institute of Medical Research, Melbourne, Australia.
  • Ascher DB; Life Sciences Discipline, Burnet Institute, Melbourne, Australia.
  • Jex AR; Institute of Mental and Physical Health and Clinical Translation (IMPACT) and School of Medicine, Deakin University, Geelong, Australia.
Mol Biol Evol ; 39(9)2022 09 01.
Article in En | MEDLINE | ID: mdl-36103257
Large-scale comparative genomics- and population genetic studies generate enormous amounts of polymorphism data in the form of DNA variants. Ultimately, the goal of many of these studies is to associate genetic variants to phenotypes or fitness. We introduce VIVID, an interactive, user-friendly web application that integrates a wide range of approaches for encoding genotypic to phenotypic information in any organism or disease, from an individual or population, in three-dimensional (3D) space. It allows mutation mapping and annotation, calculation of interactions and conservation scores, prediction of harmful effects, analysis of diversity and selection, and 3D visualization of genotypic information encoded in Variant Call Format on AlphaFold2 protein models. VIVID enables the rapid assessment of genes of interest in the study of adaptive evolution and the genetic load, and it helps prioritizing targets for experimental validation. We demonstrate the utility of VIVID by exploring the evolutionary genetics of the parasitic protist Plasmodium falciparum, revealing geographic variation in the signature of balancing selection in potential targets of functional antibodies.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Software / Genomics Type of study: Prognostic_studies Language: En Journal: Mol Biol Evol Journal subject: BIOLOGIA MOLECULAR Year: 2022 Type: Article Affiliation country: Australia

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Software / Genomics Type of study: Prognostic_studies Language: En Journal: Mol Biol Evol Journal subject: BIOLOGIA MOLECULAR Year: 2022 Type: Article Affiliation country: Australia