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Bioinformatics and Computational Tools for Next-Generation Sequencing Analysis in Clinical Genetics

by 1,2,*, 2,3,† and 1,2,†
1
Laboratory of Cell Biology, Department of Microscopy, Institute of Biomedical Sciences Abel Salazar (ICBAS), University of Porto (UP), 4050-313 Porto, Portugal
2
Biology and Genetics of Reproduction Unit, Multidisciplinary Unit for Biomedical Research (UMIB), ICBAS-UP, 4050-313 Porto, Portugal
3
UnIGENe and CGPP–Centre for Predictive and Preventive Genetics-Institute for Molecular and Cell Biology (IBMC), i3S-Institute for Research and Innovation in Health-UP, 4200-135 Porto, Portugal
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
J. Clin. Med. 2020, 9(1), 132; https://doi.org/10.3390/jcm9010132
Received: 18 November 2019 / Revised: 15 December 2019 / Accepted: 30 December 2019 / Published: 3 January 2020
(This article belongs to the Section Molecular Diagnostics)
Clinical genetics has an important role in the healthcare system to provide a definitive diagnosis for many rare syndromes. It also can have an influence over genetics prevention, disease prognosis and assisting the selection of the best options of care/treatment for patients. Next-generation sequencing (NGS) has transformed clinical genetics making possible to analyze hundreds of genes at an unprecedented speed and at a lower price when comparing to conventional Sanger sequencing. Despite the growing literature concerning NGS in a clinical setting, this review aims to fill the gap that exists among (bio)informaticians, molecular geneticists and clinicians, by presenting a general overview of the NGS technology and workflow. First, we will review the current NGS platforms, focusing on the two main platforms Illumina and Ion Torrent, and discussing the major strong points and weaknesses intrinsic to each platform. Next, the NGS analytical bioinformatic pipelines are dissected, giving some emphasis to the algorithms commonly used to generate process data and to analyze sequence variants. Finally, the main challenges around NGS bioinformatics are placed in perspective for future developments. Even with the huge achievements made in NGS technology and bioinformatics, further improvements in bioinformatic algorithms are still required to deal with complex and genetically heterogeneous disorders. View Full-Text
Keywords: bioinformatics; clinical genetics; high throughput data; NGS pipeline; NGS platforms bioinformatics; clinical genetics; high throughput data; NGS pipeline; NGS platforms
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MDPI and ACS Style

Pereira, R.; Oliveira, J.; Sousa, M. Bioinformatics and Computational Tools for Next-Generation Sequencing Analysis in Clinical Genetics. J. Clin. Med. 2020, 9, 132. https://doi.org/10.3390/jcm9010132

AMA Style

Pereira R, Oliveira J, Sousa M. Bioinformatics and Computational Tools for Next-Generation Sequencing Analysis in Clinical Genetics. Journal of Clinical Medicine. 2020; 9(1):132. https://doi.org/10.3390/jcm9010132

Chicago/Turabian Style

Pereira, Rute, Jorge Oliveira, and Mário Sousa. 2020. "Bioinformatics and Computational Tools for Next-Generation Sequencing Analysis in Clinical Genetics" Journal of Clinical Medicine 9, no. 1: 132. https://doi.org/10.3390/jcm9010132

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