Remote Visualization of Large-scale Genomic Alignments for Collaborative Clinical Research and Diagnosis of Rare Diseases

Overview

Journal Cell Genom

Date 2023 Feb 23

PMID 36819661

Authors

Alberto Corvo

Leslie Matalonga

Dylan Spalding

Alexander Senf

Steven Laurie

Daniel Pico-Amador

Marcos Fernandez-Callejo

Ida Paramonov

Anna Foix Romero

Emilio Garcia-Rios

Jorge Izquierdo Ciges

Anand Mohan

Coline Thomas

Andres Felipe Silva Valencia

Csaba Halmagyi

Mallory Ann Freeberg

Ana Topf

Rita Horvath

Gary Saunders

Ivo Gut

Thomas Keane

Davide Piscia

Sergi Beltran

Affiliations

Soon will be listed here.

Abstract

The Solve-RD project objectives include solving undiagnosed rare diseases (RD) through collaborative research on shared genome-phenome datasets. The RD-Connect Genome-Phenome Analysis Platform (GPAP), for data collation and analysis, and the European Genome-Phenome Archive (EGA), for file storage, are two key components of the Solve-RD infrastructure. Clinical researchers can identify candidate genetic variants within the RD-Connect GPAP and, thanks to the developments presented here as part of joint ELIXIR activities, are able to remotely visualize the corresponding alignments stored at the EGA. The Global Alliance for Genomics and Health (GA4GH) htsget streaming application programming interface (API) is used to retrieve alignment slices, which are rendered by an integrated genome viewer (IGV) instance embedded in the GPAP. As a result, it is no longer necessary for over 11,000 datasets to download large alignment files to visualize them locally. This work highlights the advantages, from both the user and infrastructure perspectives, of implementing interoperability standards for establishing federated genomics data networks.

Citing Articles

An interconnected data infrastructure to support large-scale rare disease research.

Johansson L, Laurie S, Spalding D, Gibson S, Ruvolo D, Thomas C Gigascience. 2024; 13.

PMID: 39302238 PMC: 11413801. DOI: 10.1093/gigascience/giae058.

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