forestSV: structural variant discovery through statistical learning

Detecting genomic structural variants from high-throughput sequencing data is a complex and unresolved challenge. We have developed a statistical learning approach, based on Random Forests, which integrates prior knowledge about the characteristics of structural variants and leads to improved discov...

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Detalles Bibliográficos
Autores principales: Michaelson, Jacob J., Sebat, Jonathan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2012
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3427657/
https://www.ncbi.nlm.nih.gov/pubmed/22751202
http://dx.doi.org/10.1038/nmeth.2085
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author Michaelson, Jacob J.
Sebat, Jonathan
author_facet Michaelson, Jacob J.
Sebat, Jonathan
author_sort Michaelson, Jacob J.
collection PubMed
description Detecting genomic structural variants from high-throughput sequencing data is a complex and unresolved challenge. We have developed a statistical learning approach, based on Random Forests, which integrates prior knowledge about the characteristics of structural variants and leads to improved discovery in high throughput sequencing data. The implementation of this technique, forestSV, offers high sensitivity and specificity coupled with the flexibility of a data-driven approach.
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spelling pubmed-34276572013-02-01 forestSV: structural variant discovery through statistical learning Michaelson, Jacob J. Sebat, Jonathan Nat Methods Article Detecting genomic structural variants from high-throughput sequencing data is a complex and unresolved challenge. We have developed a statistical learning approach, based on Random Forests, which integrates prior knowledge about the characteristics of structural variants and leads to improved discovery in high throughput sequencing data. The implementation of this technique, forestSV, offers high sensitivity and specificity coupled with the flexibility of a data-driven approach. 2012-07-01 /pmc/articles/PMC3427657/ /pubmed/22751202 http://dx.doi.org/10.1038/nmeth.2085 Text en Users may view, print, copy, download and text and data- mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#terms
spellingShingle Article
Michaelson, Jacob J.
Sebat, Jonathan
forestSV: structural variant discovery through statistical learning
title forestSV: structural variant discovery through statistical learning
title_full forestSV: structural variant discovery through statistical learning
title_fullStr forestSV: structural variant discovery through statistical learning
title_full_unstemmed forestSV: structural variant discovery through statistical learning
title_short forestSV: structural variant discovery through statistical learning
title_sort forestsv: structural variant discovery through statistical learning
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3427657/
https://www.ncbi.nlm.nih.gov/pubmed/22751202
http://dx.doi.org/10.1038/nmeth.2085
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