A bioinformatics pipeline for rare genetic diseases in South African patients

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dc.contributor.author Schoonen, Maryke
dc.contributor.author Seyffert, Albertus S.
dc.contributor.author Van der Westhuizen, Francois H.
dc.contributor.author Smuts, Izelle
dc.date.accessioned 2019-04-03T11:48:48Z
dc.date.available 2019-04-03T11:48:48Z
dc.date.issued 2019-03-27
dc.description.abstract The research fields of bioinformatics and computational biology are growing rapidly in South Africa. Bioinformatics pipelines play an integral part in handling sequencing data, which are used to investigate the aetiology of common and rare diseases. Bioinformatics platforms for common disease aetiology are well supported and continuously being developed in South Africa. However, the same is not the case for rare diseases aetiology research. Investigations into the latter rely on international cloud-based tools for data analyses and ultimately confirmation of a genetic disease. However, these tools are not necessarily optimised for ethnically diverse population groups. We present an in-house developed bioinformatics pipeline to enable researchers to annotate and filter variants in either exome or amplicon next-generation sequencing data. This pipeline was developed using next-generation sequencing data of a predominantly African cohort of patients diagnosed with rare disease. SIGNIFICANCE : • We demonstrate the feasibility of in-country development of ethnicity-sensitive, automated bioinformatics pipelines using free software in a South African context. • We provide a roadmap for development of similarly ethnicity-sensitive bioinformatics pipelines. en_ZA
dc.description.department Paediatrics and Child Health en_ZA
dc.description.librarian am2019 en_ZA
dc.description.sponsorship The Medical Research Council of South Africa en_ZA
dc.description.uri http://www.sajs.co.za en_ZA
dc.identifier.citation Schoonen M, Seyffert AS, Van der Westhuizen FH, Smuts I. A bioinformatics pipeline for rare genetic diseases in South African patients. S Afr J Sci. 2019;115(3/4), Art. #4876, 3 pages. https://DOI. org/ 10.17159/sajs.2019/4876. en_ZA
dc.identifier.issn 0038-2353 (print)
dc.identifier.issn 1996-7489 (online)
dc.identifier.other 10.17159/sajs.2019/4876
dc.identifier.uri http://hdl.handle.net/2263/68768
dc.language.iso en en_ZA
dc.publisher Academy of Science of South Africa en_ZA
dc.rights © 2019. The Author(s). Published under a Creative Commons Attribution Licence. en_ZA
dc.subject Computational tools en_ZA
dc.subject African cohort en_ZA
dc.subject Next-generation sequencing en_ZA
dc.subject Rare disease en_ZA
dc.title A bioinformatics pipeline for rare genetic diseases in South African patients en_ZA
dc.type Article en_ZA


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