Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

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

Version 1 : Received: 14 December 2020 / Approved: 15 December 2020 / Online: 15 December 2020 (13:14:21 CET)

A peer-reviewed article of this Preprint also exists.

Castellano, S.; Cestari, F.; Faglioni, G.; Tenedini, E.; Marino, M.; Artuso, L.; Manfredini, R.; Luppi, M.; Trenti, T.; Tagliafico, E. iVar, an Interpretation-Oriented Tool to Manage the Update and Revision of Variant Annotation and Classification. Genes 2021, 12, 384. Castellano, S.; Cestari, F.; Faglioni, G.; Tenedini, E.; Marino, M.; Artuso, L.; Manfredini, R.; Luppi, M.; Trenti, T.; Tagliafico, E. iVar, an Interpretation-Oriented Tool to Manage the Update and Revision of Variant Annotation and Classification. Genes 2021, 12, 384.

Journal reference: Genes 2021, 12, 384
DOI: 10.3390/genes12030384

Abstract

The rapid evolution of Next Generation Sequencing in clinical settings and the resulting challenge of variants interpretation in the light of constantly updated information, requires robust data management systems and organized approaches to variant reinterpretation. In this paper, we present iVar: a freely available and highly customizable tool provided with a user-friendly web interface. It represents a platform for the unified management of variants identified by different sequencing technologies. iVar accepts, as input, VCF files and text annotation files and elaborates them, optimizing data organization and avoiding redundancies. Updated annotations can be periodically re-uploaded and associated to variants as historicize attributes. Data can be visualized through variant-centered and sample-centered interfaces. A customizable search functionality can be exploited to periodically check if pathogenicity related data of a variant are 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 and carrying a specific variant. We tested iVar by uploading 4171 VCF files and 1463 annotation files, obtaining a database of 4166 samples and 22569 unique variants. iVar has proven to be a useful tool with good performances for collecting and managing data from medium-throughput

Subject Areas

next-generation sequencing; database; variant annotation; variant classification; data management; clinical genomics

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