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Bioinformatics and Computational Tools for Next-Generation Sequencing Analysis in Clinical Genetics
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 sequen...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7019349/ https://www.ncbi.nlm.nih.gov/pubmed/31947757 http://dx.doi.org/10.3390/jcm9010132 |
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author | Pereira, Rute Oliveira, Jorge Sousa, Mário |
author_facet | Pereira, Rute Oliveira, Jorge Sousa, Mário |
author_sort | Pereira, Rute |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7019349 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-70193492020-03-09 Bioinformatics and Computational Tools for Next-Generation Sequencing Analysis in Clinical Genetics Pereira, Rute Oliveira, Jorge Sousa, Mário J Clin Med Review 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. MDPI 2020-01-03 /pmc/articles/PMC7019349/ /pubmed/31947757 http://dx.doi.org/10.3390/jcm9010132 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Pereira, Rute Oliveira, Jorge Sousa, Mário Bioinformatics and Computational Tools for Next-Generation Sequencing Analysis in Clinical Genetics |
title | Bioinformatics and Computational Tools for Next-Generation Sequencing Analysis in Clinical Genetics |
title_full | Bioinformatics and Computational Tools for Next-Generation Sequencing Analysis in Clinical Genetics |
title_fullStr | Bioinformatics and Computational Tools for Next-Generation Sequencing Analysis in Clinical Genetics |
title_full_unstemmed | Bioinformatics and Computational Tools for Next-Generation Sequencing Analysis in Clinical Genetics |
title_short | Bioinformatics and Computational Tools for Next-Generation Sequencing Analysis in Clinical Genetics |
title_sort | bioinformatics and computational tools for next-generation sequencing analysis in clinical genetics |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7019349/ https://www.ncbi.nlm.nih.gov/pubmed/31947757 http://dx.doi.org/10.3390/jcm9010132 |
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