e-Article
Remote visualization of large-scale genomic alignments for collaborative clinical research and diagnosis of rare diseases
Document Type
article
Author
Alberto Corvò; Leslie Matalonga; Dylan Spalding; Alexander Senf; Steven Laurie; Daniel Picó-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 Töpf; Rita Horvath; Gary Saunders; Ivo Gut; Thomas Keane; Davide Piscia; Sergi Beltran
Source
Cell Genomics, Vol 3, Iss 2, Pp 100246- (2023)
Subject
Language
English
ISSN
2666-979X
Abstract
Summary: 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.