VIVID: A web application for variant interpretation and visualization in multi-dimensional analyses

Swapnil Tichkule, Yoochan Myung, Myo T. Naung, Brendan R. E. Ansell, Andrew J. Guy, Namrata Srivastava, Somya Mehra, Simone M. Cacciò, Ivo Mueller, Alyssa E. Barry, Cock van Oosterhout, Bernard Pope, David B. Ascher, Aaron R. Jex, Emma Teeling (Editor)

Research output: Contribution to journalArticlepeer-review

Abstract

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.
Original languageEnglish
Article numbermsac196
JournalMolecular Biology and Evolution
Volume39
Issue number9
DOIs
Publication statusPublished - 14 Sep 2022

Keywords

  • data visualization
  • evolution
  • multi-dimensional analysis
  • population genetics
  • protein structure
  • variant interpretation

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