tetano
Editor, Senior Moderator
Eur J Hum Genet
. 2022 Mar 29.
doi: 10.1038/s41431-022-01089-8. Online ahead of print.
Coronavirus Host Genetics South Africa (COHG-SA) database-a variant database for gene regions associated with SARS-CoV-2 outcomes
Fatima Barmania[SUP] 1 [/SUP], Juanita Mellet[SUP] 1 [/SUP], Megan A Ryder[SUP] 1 [/SUP], Graeme Ford[SUP] 1 2 [/SUP], Candice L Herd[SUP] 1 [/SUP], Tsaone Tamuhla[SUP] 3 [/SUP], Candice Hendricks[SUP] 1 [/SUP], Rachel Giles[SUP] 1 [/SUP], Thumbiko Kalua[SUP] 1 [/SUP], Fourie Joubert[SUP] 2 [/SUP], Nicki Tiffin[SUP] 3 4 [/SUP], Michael S Pepper[SUP] 5 [/SUP]
Affiliations
Abstract
The SARS-CoV-2 virus is responsible for the COVID-19 global public health emergency, and the disease it causes is highly variable in its clinical presentation. Clinical phenotypes are heterogeneous both in terms of presentation of symptoms in the host and response to therapy. Several studies and initiatives have been established to analyse and review host genetic epidemiology associated with COVID-19. Our research group curated these articles into a web-based database using the python application-server framework Django. The database provides a searchable research tool describing current literature surrounding COVID-19 host genetic factors associated with disease outcome. This paper describes the COHG-SA database and provides an overview of the analyses that can be derived from these data.
. 2022 Mar 29.
doi: 10.1038/s41431-022-01089-8. Online ahead of print.
Coronavirus Host Genetics South Africa (COHG-SA) database-a variant database for gene regions associated with SARS-CoV-2 outcomes
Fatima Barmania[SUP] 1 [/SUP], Juanita Mellet[SUP] 1 [/SUP], Megan A Ryder[SUP] 1 [/SUP], Graeme Ford[SUP] 1 2 [/SUP], Candice L Herd[SUP] 1 [/SUP], Tsaone Tamuhla[SUP] 3 [/SUP], Candice Hendricks[SUP] 1 [/SUP], Rachel Giles[SUP] 1 [/SUP], Thumbiko Kalua[SUP] 1 [/SUP], Fourie Joubert[SUP] 2 [/SUP], Nicki Tiffin[SUP] 3 4 [/SUP], Michael S Pepper[SUP] 5 [/SUP]
Affiliations
- PMID: 35351987
- DOI: 10.1038/s41431-022-01089-8
Abstract
The SARS-CoV-2 virus is responsible for the COVID-19 global public health emergency, and the disease it causes is highly variable in its clinical presentation. Clinical phenotypes are heterogeneous both in terms of presentation of symptoms in the host and response to therapy. Several studies and initiatives have been established to analyse and review host genetic epidemiology associated with COVID-19. Our research group curated these articles into a web-based database using the python application-server framework Django. The database provides a searchable research tool describing current literature surrounding COVID-19 host genetic factors associated with disease outcome. This paper describes the COHG-SA database and provides an overview of the analyses that can be derived from these data.