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. 2023 Jan 11;3(2):100246.
doi: 10.1016/j.xgen.2022.100246. eCollection 2023 Feb 8.

Remote visualization of large-scale genomic alignments for collaborative clinical research and diagnosis of rare diseases

Alberto Corvò  1 , Leslie Matalonga  1 , Dylan Spalding  2   3 , Alexander Senf  2   4 , Steven Laurie  1 , Daniel Picó-Amador  1 , Marcos Fernandez-Callejo  1 , Ida Paramonov  1 , Anna Foix Romero  2 , Emilio Garcia-Rios  2 , Jorge Izquierdo Ciges  2 , Anand Mohan  2 , Coline Thomas  2 , Andres Felipe Silva Valencia  2 , Csaba Halmagyi  2 , Mallory Ann Freeberg  2 , Ana Töpf  5 , Rita Horvath  6 , Gary Saunders  7 , Ivo Gut  1 , Thomas Keane  2 , Davide Piscia  1 , Sergi Beltran  1   8   9
Affiliations

Remote visualization of large-scale genomic alignments for collaborative clinical research and diagnosis of rare diseases

Alberto Corvò et al. Cell Genom. .

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.

Keywords: data sharing; data visualization; diagnosis; exome analysis; federated infrastructures; genome analysis; rare diseases; remote data access; standards.

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Conflict of interest statement

The authors declare that they have no conflict of interest.

Figures

None
Graphical abstract
Figure 1
Figure 1
Remote real-time visualization workflow (A and B) An RD-Connect GPAP authorized user (A) identifies a variant of interest and requests to visualize the associated genomic alignments by (B) clicking on the IGV links provided in the interface. (C) The request is sent to the EGA, which directs access to the corresponding EGA box and alignment file (BAM/CRAM). (D and E) The htsget protocol generates a slice of the requested alignment as an answer (D), which is rendered by the IGV application implementation in RD-Connect GPAP (E). (F) The user is able to visualize the alignment in the region of interest.
Figure 2
Figure 2
Visualization of slices of genomic alignments archived at the EGA A screenshot of the GPAP’s embedded IGV displaying a slice of a BAM file, archived at the EGA, from a patient with cerebellar hypoplasia and spinal muscular atrophy. The genomic data show a homozygous single-nucleotide change at position 15:64698591C>T (NM_016213.5:c.760C>T [pArg254Ter]). This variant has been reported as disease causing.
See this image and copyright information in PMC

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