Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Conference object . 2018
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Other literature type . 2018
License: CC BY
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Conference object . 2018
License: CC BY
Data sources: Datacite
versions View all 2 versions
addClaim

Rd-Connect: An Integrated Infrastructure For Data Sharing And Analysis In Rare Disease Research

Authors: Badowska, Dorota; Thompson, Rachel; Beltran, Sergi; Gut, Ivo; Monaco, Lucia; Béroud, Christophe; Lochmüller, Hanns; +1 Authors

Rd-Connect: An Integrated Infrastructure For Data Sharing And Analysis In Rare Disease Research

Abstract

RD-Connect is an infrastructure for rare disease research bringing together multiple data types in three systems: Genome-Phenome Analysis Platform (platform.rd-connect.eu), Sample Catalogue (samples.rd-connect.eu) and Registry & Biobank Finder (catalogue.rd-connect.eu). All these systems are open to any rare disease and available free of charge. The Genome-Phenome Analysis Platform is a centralized data repository and a user-friendly online analysis system combining omics data (genomics, proteomics, transcriptomics) with clinical information at individual-patient, family or cohort level. Whole-genome, exome and gene panel datasets are submitted by the end-user and processed by RD-Connect's standardised analysis and annotation pipeline to make data from different sequencing providers comparable. Raw data is deposited at the European Genome-phenome Archive (EGA) for long-term storage. Clinical information is recorded in the PhenoTips system, which simplifies entry of clinical data using the Human Phenotype Ontology. Results are available to the submitter and authorised users through the highly configurable platform, which enables advanced filtering and prioritization of variants. Users can analyse their own patients and compare results with other submitted cohorts, including queries such as: “Does this variant exist in this cohort?” and “Are there patients in other databases with matching phenotype and candidate variant in the same gene?”. The Platform already includes thousands of datasets from partner projects such as NeurOmics (www.rd-neuromics.eu) and BBMRI-LPC (www.bbmri-lpc.org). In 2018, it became the primary data sharing and analysis platform for the new Solve-RD project, which will bring in 19,000 unsolved cases from European Reference Networks over 5 years. RD-Connect is free and open for contributions from individual research groups and other projects: contact platform@rd-connect.eu. The Sample Catalogue allows browsing biosample collections stored in rare disease biobanks using powerful filtering functions. It provides detailed information about individual biosamples, including disease, diagnosis type, sample type, sex, availability of genetic and registry data and of samples from the patient’s relatives. Currently, the Sample Catalogue includes over 25,000 samples stored by rare disease biobanks in the EuroBioBank Network. The work is ongoing to make the Sample Catalogue interconnected with the Platform, to enable finding biosamples from patients with a specific genetic variant, and with the Registry & Biobank Finder, to allow direct link from the global directory of rare disease databases to the sample collections.

Keywords

patient engagement, data sharing, rare diseases, patient registries, bioinformatics, omics, ELSI, research infrastructure, genomics, biobanks, data linkage

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
    OpenAIRE UsageCounts
    Usage byUsageCounts
    visibility views 3
    download downloads 2
  • 3
    views
    2
    downloads
    Powered byOpenAIRE UsageCounts
Powered by OpenAIRE graph
Found an issue? Give us feedback
visibility
download
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
OpenAIRE UsageCountsDownloads provided by UsageCounts
0
Average
Average
Average
3
2
Green