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. 2019 Sep;40(9):1202-1214.
doi: 10.1002/humu.23858. Epub 2019 Aug 17.

VIPdb, a genetic Variant Impact Predictor Database

Zhiqiang Hu  1 , Changhua Yu  1   2 , Mabel Furutsuki  1   3 , Gaia Andreoletti  1 , Melissa Ly  1   4 , Roger Hoskins  1 , Aashish N Adhikari  1 , Steven E Brenner  1
Affiliations

VIPdb, a genetic Variant Impact Predictor Database

Zhiqiang Hu et al. Hum Mutat. 2019 Sep.

Abstract

Genome sequencing identifies vast number of genetic variants. Predicting these variants' molecular and clinical effects is one of the preeminent challenges in human genetics. Accurate prediction of the impact of genetic variants improves our understanding of how genetic information is conveyed to molecular and cellular functions, and is an essential step towards precision medicine. Over one hundred tools/resources have been developed specifically for this purpose. We summarize these tools as well as their characteristics, in the genetic Variant Impact Predictor Database (VIPdb). This database will help researchers and clinicians explore appropriate tools, and inform the development of improved methods. VIPdb can be browsed and downloaded at https://genomeinterpretation.org/vipdb.

Keywords: SNV phenotype; SV impact; VIPdb; genotype-phenotype relationship; variant impact; variant impact prediction.

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Conflict of interest statement

Conflict of interest

Support from Tata Consultancy Services Ltd.

Figures

Figure 1.
Figure 1.. Wordle of variant impact predictors.
Only tools primarily designed for variant impact prediction were plotted. Character sizes represent the logarithm of recent citations (from Jan 1, 2017 to Jun 1, 2019). For tools with multiple publications, we plotted the sum of all citations. Colors were randomly selected. The Wordle tool (http://www.wordle.net) was used to generate the plot.
See this image and copyright information in PMC

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