Computational methods for discovering structural variation with next-generation sequencing

In the last several years, a number of studies have described large-scale structural variation in several genomes. Traditionally, such methods have used whole-genome array comparative genome hybridization or single-nucleotide polymorphism arrays to detect large regions subject to copy-number variati...

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Veröffentlicht in:Nature methods Jg. 6; H. Suppl 11; S. S13 - S20
Hauptverfasser: Medvedev, Paul, Stanciu, Monica, Brudno, Michael
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York Nature Publishing Group US 01.11.2009
Nature Publishing Group
Schlagworte:
Algorithms
Analysis
Base Sequence
Bioinformatics
Biological Microscopy
Biological Techniques
Biomedical and Life Sciences
Biomedical Engineering/Biotechnology
Computational biology
Computational Biology - methods
DNA sequencing
Genetic Variation
Genome
Genomes
Genomics
Genomics - methods
Humans
Hybridization
Innovations
Life Sciences
Methods
Molecular structure
Nucleotide sequencing
Properties
Proteomics
Research methodology
review-article
Sequence Analysis, DNA - methods
Technological change
Canada
ISSN:1548-7091, 1548-7105, 1548-7105
Online-Zugang:Volltext
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Beschreibung
Zusammenfassung:In the last several years, a number of studies have described large-scale structural variation in several genomes. Traditionally, such methods have used whole-genome array comparative genome hybridization or single-nucleotide polymorphism arrays to detect large regions subject to copy-number variation. Later techniques have been based on paired-end mapping of Sanger sequencing data, providing better resolution and accuracy. With the advent of next-generation sequencing, a new generation of methods is being developed to tackle the challenges of short reads, while taking advantage of the high coverage the new sequencing technologies provide. In this survey, we describe these methods, including their strengths and their limitations, and future research directions.
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SourceType-Scholarly Journals-1
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ISSN:1548-7091
1548-7105
1548-7105
DOI:10.1038/nmeth.1374