EVA: Exome Variation Analyzer, an efficient and versatile tool for filtering strategies in medical genomics

Abstract

BackgroundWhole exome sequencing (WES) has become the strategy of choice to identify a coding allelic variant for a rare human monogenic disorder. This approach is a revolution in medical genetics history, impacting both fundamental research, and diagnostic methods leading to personalized medicine. A plethora of efficient algorithms has been developed to ensure the variant discovery. They generally lead to ~20,000 variations that have to be narrow down to find the potential pathogenic allelic variant(s) and the affected gene(s). For this purpose, commonly adopted procedures which implicate various filtering strategies have emerged: exclusion of common variations, type of the allelics variants, pathogenicity effect prediction, modes of inheritance and multiple individuals for exome comparison. To deal with the expansion of WES in medical genomics individual laboratories, new convivial and versatile software tools have to implement these filtering steps. Non-programmer biologists have to be autonomous combining themselves different filtering criteria and conduct a personal strategy depending on their assumptions and study design.ResultsWe describe EVA (Exome Variation Analyzer), a user-friendly web-interfaced software dedicated to the filtering strategies for medical WES. Thanks to different modules, EVA (i) integrates and stores annotated exome variation data as strictly confidential to the project owner, (ii) allows to combine the main filters dealing with common variations, molecular types, inheritance mode and multiple samples, (iii) offers the browsing of annotated data and filtered results in various interactive tables, graphical visualizations and statistical charts, (iv) and finally offers export files and cross-links to external useful databases and softwares for further prioritization of the small subset of sorted candidate variations and genes. We report a demonstrative case study that allowed to identify a new candidate gene related to a rare form of Alzheimer disease.ConclusionsEVA is developed to be a user-friendly, versatile, and efficient-filtering assisting software for WES. It constitutes a platform for data storage and for drastic screening of clinical relevant genetics variations by non-programmer geneticists. Thereby, it provides a response to new needs at the expanding era of medical genomics investigated by WES for both fundamental research and clinical diagnostics.

VariantDB: A flexible annotation and filtering portal for next generation sequencing data

“…User-accessible sample genotypes are used to calculate a private set of MAFs. PriVar, and web-based but single-user approaches such as EVA [30,31,55]. As a centralized solution, VariantDB enables intuitive retrospective or multi-sample analysis, and collaboration between researchers from multiple laboratories.…”

“…Many of these tools were developed for specific research questions, such as either family-based [22,23] or case/control-based experiments [24], or provide broad annotation in text-based output without dynamic filtering options [23,[25][26][27][28]. Other available tools provide dynamic filtering options but can only handle a limited set of annotations [29][30][31]. Direct integration of the first and second analysis stage, bypassing manual handling of intermediate results, is a feature currently only available in the WEP platform [32].…”

Next generation sequencing and rare genetic variants: From human population studies to medical genetics

“…A big challenge remains in the identification of clinically significant variants from within the broader set of variants that are putatively functional, but have no obvious clinical significance. To this end, tools and pipelines for filtering data and excluding false positive associations have been proposed [Coutant et al, 2012;Liu et al, 2012]. NGS experiments highlight the big potential of rare variants to provide true associations with Mendelian disorders [Choi et al, 2009;Ng et al, 2009Ng et al, , 2010Lupski et al, 2010;Roach et al, 2010;Gilissen et al, 2011;Rabbani et al, 2012;Schmidts et al, 2013] or sporadic developmental disorders, even when analyzing only a small number of individuals [Hoischen et al, 2010;Riviere et al, 2012].…”

Var2GO: a web-based tool for gene variants selection

“…However, they often require advanced computational skills for both the installation process and their usage [10, 11]. When a web service is available, as in [12], usually only a list of genes is given in output, thus requiring further processing to match the initial data with the list of new annotations.…”

“…One available tool for visualizing annotated sequence variants and interacting with the VCF input file is SVA [18], which requires high-performance workstations or servers to properly work. Other available software include VCF-Miner [10] and EVA [11], but both of them need the installation of a complete web stack as a prerequisite. The most user-friendly tool is VarSifter [19], a Java-based software which requires a minimal installation.…”