ELIXIR-CONVERGE D7.3 COVID-19 metadata mapping model across COVID-19 studies in federated EGA

descriptionPublicationkeyboard_double_arrow_right Project deliverable , Other literature type , Article 01 Jan 2021 English Publisher:ZenodoFunded by:EC | ELIXIR-CONVERGE

Authors: Morello, Francesca; Lehväslaiho, Heikki; Lappalainen, Ilkka; Rambla, Jordi;

doi: 10.5281/zenodo.4893222 , 10.5281/zenodo.4893221

ELIXIR-CONVERGE D7.3 COVID-19 metadata mapping model across COVID-19 studies in federated EGA

- Summary
- Subjects
- Metrics

Abstract

We summarise efforts from the past year of the COVID-19 pandemic to categorise and guide the collection of phenotype information from patients infected with the SARS-CoV-2. The COVID-19 Host Genetics Initiative data dictionary brings together observations from many independent sources and has been revised multiple times to match availability of data and research needs. In this document, we describe how these data, deposited in controlled access repositories such as EGA and dbGaP, were mapped to the data dictionary and each other, to form the basis of the proposed CONVERGE minimal COVID-19 phenotype metadata model.

Keywords

FEGA, COVID-19, CONVERGE, Federated EGA, ELIXIR-CONVERGE, metadata mapping, ELIXIR, FAIR, Data Management

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