A bioinformatics pipeline for rare genetic diseases in South African patients
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.contributor.researchID | 20574495 - Schoonen, Maryke | |
dc.contributor.researchID | 10213503 - Van der Westhuizen, Francois Hendrikus | |
dc.contributor.researchID | 20126999 - Seyffert, Albertus Stefanus | |
dc.date.accessioned | 2019-05-13T13:17:49Z | |
dc.date.available | 2019-05-13T13:17:49Z | |
dc.date.issued | 2019 | |
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 | en_US |
dc.identifier.citation | Schoonen, M. et al. 2019. A bioinformatics pipeline for rare genetic diseases in South African patients. South African journal of science, 115(3-4):99-101. [https://doi.org/10.17159/sajs.2019/4876] | en_US |
dc.identifier.issn | 0038-2353 | |
dc.identifier.issn | 1996-7489 (Online) | |
dc.identifier.uri | http://hdl.handle.net/10394/32327 | |
dc.identifier.uri | https://www.sajs.co.za/article/view/4876 | |
dc.identifier.uri | https://doi.org/10.17159/sajs.2019/4876 | |
dc.language.iso | en | en_US |
dc.publisher | ASSAf | en_US |
dc.subject | Computational tools | en_US |
dc.subject | African cohort | en_US |
dc.subject | Next-generation sequencing | en_US |
dc.subject | Rare disease | en_US |
dc.title | A bioinformatics pipeline for rare genetic diseases in South African patients | en_US |
dc.type | Article | en_US |