Dissemin is shutting down on January 1st, 2025

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Nature Research, Nature Methods, 8(9), p. 819-821, 2012

DOI: 10.1038/nmeth.2085

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forestSV: structural variant discovery through statistical learning

Journal article published in 2012 by Jacob J. Michaelson, Jonathan Sebat ORCID
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

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.