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Unraveling genomic variation from next generation sequencing data

Elucidating the content of a DNA sequence is critical to deeper understand and decode the genetic information for any biological system. As next generation sequencing (NGS) techniques have become cheaper and more advanced in throughput over time, great innovations and breakthrough conclusions have b...

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Autores principales: Pavlopoulos, Georgios A, Oulas, Anastasis, Iacucci, Ernesto, Sifrim, Alejandro, Moreau, Yves, Schneider, Reinhard, Aerts, Jan, Iliopoulos, Ioannis
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3726446/
https://www.ncbi.nlm.nih.gov/pubmed/23885890
http://dx.doi.org/10.1186/1756-0381-6-13
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author Pavlopoulos, Georgios A
Oulas, Anastasis
Iacucci, Ernesto
Sifrim, Alejandro
Moreau, Yves
Schneider, Reinhard
Aerts, Jan
Iliopoulos, Ioannis
author_facet Pavlopoulos, Georgios A
Oulas, Anastasis
Iacucci, Ernesto
Sifrim, Alejandro
Moreau, Yves
Schneider, Reinhard
Aerts, Jan
Iliopoulos, Ioannis
author_sort Pavlopoulos, Georgios A
collection PubMed
description Elucidating the content of a DNA sequence is critical to deeper understand and decode the genetic information for any biological system. As next generation sequencing (NGS) techniques have become cheaper and more advanced in throughput over time, great innovations and breakthrough conclusions have been generated in various biological areas. Few of these areas, which get shaped by the new technological advances, involve evolution of species, microbial mapping, population genetics, genome-wide association studies (GWAs), comparative genomics, variant analysis, gene expression, gene regulation, epigenetics and personalized medicine. While NGS techniques stand as key players in modern biological research, the analysis and the interpretation of the vast amount of data that gets produced is a not an easy or a trivial task and still remains a great challenge in the field of bioinformatics. Therefore, efficient tools to cope with information overload, tackle the high complexity and provide meaningful visualizations to make the knowledge extraction easier are essential. In this article, we briefly refer to the sequencing methodologies and the available equipment to serve these analyses and we describe the data formats of the files which get produced by them. We conclude with a thorough review of tools developed to efficiently store, analyze and visualize such data with emphasis in structural variation analysis and comparative genomics. We finally comment on their functionality, strengths and weaknesses and we discuss how future applications could further develop in this field.
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spelling pubmed-37264462013-07-30 Unraveling genomic variation from next generation sequencing data Pavlopoulos, Georgios A Oulas, Anastasis Iacucci, Ernesto Sifrim, Alejandro Moreau, Yves Schneider, Reinhard Aerts, Jan Iliopoulos, Ioannis BioData Min Review Elucidating the content of a DNA sequence is critical to deeper understand and decode the genetic information for any biological system. As next generation sequencing (NGS) techniques have become cheaper and more advanced in throughput over time, great innovations and breakthrough conclusions have been generated in various biological areas. Few of these areas, which get shaped by the new technological advances, involve evolution of species, microbial mapping, population genetics, genome-wide association studies (GWAs), comparative genomics, variant analysis, gene expression, gene regulation, epigenetics and personalized medicine. While NGS techniques stand as key players in modern biological research, the analysis and the interpretation of the vast amount of data that gets produced is a not an easy or a trivial task and still remains a great challenge in the field of bioinformatics. Therefore, efficient tools to cope with information overload, tackle the high complexity and provide meaningful visualizations to make the knowledge extraction easier are essential. In this article, we briefly refer to the sequencing methodologies and the available equipment to serve these analyses and we describe the data formats of the files which get produced by them. We conclude with a thorough review of tools developed to efficiently store, analyze and visualize such data with emphasis in structural variation analysis and comparative genomics. We finally comment on their functionality, strengths and weaknesses and we discuss how future applications could further develop in this field. BioMed Central 2013-07-25 /pmc/articles/PMC3726446/ /pubmed/23885890 http://dx.doi.org/10.1186/1756-0381-6-13 Text en Copyright © 2013 Pavlopoulos et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Review
Pavlopoulos, Georgios A
Oulas, Anastasis
Iacucci, Ernesto
Sifrim, Alejandro
Moreau, Yves
Schneider, Reinhard
Aerts, Jan
Iliopoulos, Ioannis
Unraveling genomic variation from next generation sequencing data
title Unraveling genomic variation from next generation sequencing data
title_full Unraveling genomic variation from next generation sequencing data
title_fullStr Unraveling genomic variation from next generation sequencing data
title_full_unstemmed Unraveling genomic variation from next generation sequencing data
title_short Unraveling genomic variation from next generation sequencing data
title_sort unraveling genomic variation from next generation sequencing data
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3726446/
https://www.ncbi.nlm.nih.gov/pubmed/23885890
http://dx.doi.org/10.1186/1756-0381-6-13
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