loading page

iVar, an interpretation-oriented tool to manage the update and revision of variant annotation and classification
  • +7
  • Sara Castellano,
  • Federica Cestari,
  • Giovanni Faglioni,
  • Elena Tenedini,
  • Marco Marino,
  • Lucia Artuso,
  • Rossella Manfredini,
  • Mario Luppi,
  • Tommaso Trenti,
  • Enrico Tagliafico
Sara Castellano
University of Modena and Reggio Emilia

Corresponding Author:[email protected]

Author Profile
Federica Cestari
Nabla2 s.r.l
Author Profile
Giovanni Faglioni
Nabla2 s.r.l
Author Profile
Elena Tenedini
University Hospital Modena
Author Profile
Marco Marino
University Hospital Modena
Author Profile
Lucia Artuso
University Hospital Modena
Author Profile
Rossella Manfredini
University of Modena and Reggio Emilia
Author Profile
Mario Luppi
University of Modena and Reggio Emilia
Author Profile
Tommaso Trenti
University Hospital Modena
Author Profile
Enrico Tagliafico
University of Modena and Reggio Emilia
Author Profile

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