iVar, an Interpretation-Oriented Tool to Manage the Update and Revision of Variant Annotation and Classification

• Main Authors: Sara Castellano, Federica Cestari, Giovanni Faglioni, Elena Tenedini, Marco Marino, Lucia Artuso, Rossella Manfredini, Mario Luppi, Tommaso Trenti, Enrico Tagliafico
• Format: Article
• Language: English
• Published: MDPI AG 2021-03-01
• Series: Genes
• Subjects: next-generation sequencing; database; variant annotation; variant classification; data management; clinical genomics
• Online Access: https://www.mdpi.com/2073-4425/12/3/384

The rapid evolution of Next Generation Sequencing in clinical settings, and the resulting challenge of variant reinterpretation given the constantly updated information, require robust data management systems and organized approaches. In this paper, we present iVar: a freely available and highly customizable tool with a user-friendly web interface. It represents a platform for the unified management of variants identified by different sequencing technologies. iVar accepts variant call format (VCF) files and text annotation files and elaborates them, optimizing data organization and avoiding redundancies. Updated annotations can be periodically re-uploaded and associated with variants as historically tracked attributes, i.e., modifications can be recorded whenever an updated value is imported, thus keeping track of all changes. Data can be visualized through variant-centered and sample-centered interfaces. A customizable search function can be exploited to periodically check if pathogenicity-related data of a variant has changed over time. Patient recontacting ensuing from variant reinterpretation is made easier by iVar through the effective identification of all patients present in the database carrying a specific variant. We tested iVar by uploading 4171 VCF files and 1463 annotation files, obtaining a database of 4166 samples and 22,569 unique variants. iVar has proven to be a useful tool with good performance in terms of collecting and managing data from a medium-throughput laboratory.