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

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.

Medienart:

E-Artikel

Erscheinungsjahr:

2021

Erschienen:

2021

Enthalten in:

Zur Gesamtaufnahme - volume:12

Enthalten in:

Genes - 12(2021), 3 vom: 08. März

Sprache:

Englisch

Beteiligte Personen:

Castellano, Sara [VerfasserIn]
Cestari, Federica [VerfasserIn]
Faglioni, Giovanni [VerfasserIn]
Tenedini, Elena [VerfasserIn]
Marino, Marco [VerfasserIn]
Artuso, Lucia [VerfasserIn]
Manfredini, Rossella [VerfasserIn]
Luppi, Mario [VerfasserIn]
Trenti, Tommaso [VerfasserIn]
Tagliafico, Enrico [VerfasserIn]

Links:

Volltext

Themen:

Clinical genomics
Data management
Database
Journal Article
Next-generation sequencing
Research Support, Non-U.S. Gov't
Variant annotation
Variant classification

Anmerkungen:

Date Completed 03.08.2021

Date Revised 03.08.2021

published: Electronic

Citation Status MEDLINE

doi:

10.3390/genes12030384

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM323559751