A bioinformatics pipeline for rare genetic diseases in South African patients
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 aetiol...
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doaj-6851da80528343c48288165a10fe8dde2020-11-25T01:55:52ZengAcademy of Science of South AfricaSouth African Journal of Science1996-74892019-03-011153/410.17159/sajs.2019/48764876A bioinformatics pipeline for rare genetic diseases in South African patientsMaryke Schoonen0Albertus S. Seyffert1Francois H. van der Westhuizen2Izelle Smuts3Human Metabolomics, North-West University, Potchefstroom, South AfricaCentre for Space Research, North-West University, Potchefstroom, South AfricaHuman Metabolomics, North-West University, Potchefstroom, South AfricaDepartment of Paediatrics and Child Health, Steve Biko Academic Hospital, University of Pretoria, Pretoria, South AfricaThe 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.https://www.sajs.co.za/article/view/4876computational toolsafrican cohortnext-generation sequencingrare disease |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Maryke Schoonen Albertus S. Seyffert Francois H. van der Westhuizen Izelle Smuts |
spellingShingle |
Maryke Schoonen Albertus S. Seyffert Francois H. van der Westhuizen Izelle Smuts A bioinformatics pipeline for rare genetic diseases in South African patients South African Journal of Science computational tools african cohort next-generation sequencing rare disease |
author_facet |
Maryke Schoonen Albertus S. Seyffert Francois H. van der Westhuizen Izelle Smuts |
author_sort |
Maryke Schoonen |
title |
A bioinformatics pipeline for rare genetic diseases in South African patients |
title_short |
A bioinformatics pipeline for rare genetic diseases in South African patients |
title_full |
A bioinformatics pipeline for rare genetic diseases in South African patients |
title_fullStr |
A bioinformatics pipeline for rare genetic diseases in South African patients |
title_full_unstemmed |
A bioinformatics pipeline for rare genetic diseases in South African patients |
title_sort |
bioinformatics pipeline for rare genetic diseases in south african patients |
publisher |
Academy of Science of South Africa |
series |
South African Journal of Science |
issn |
1996-7489 |
publishDate |
2019-03-01 |
description |
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. |
topic |
computational tools african cohort next-generation sequencing rare disease |
url |
https://www.sajs.co.za/article/view/4876 |
work_keys_str_mv |
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