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CNV Workshop: an integrated platform for high-throughput copy number variation discovery and clinical diagnostics
BACKGROUND: Recent studies have shown that copy number variations (CNVs) are frequent in higher eukaryotes and associated with a substantial portion of inherited and acquired risk for various human diseases. The increasing availability of high-resolution genome surveillance platforms provides opport...
Autores principales: | , , , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2010
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2827374/ https://www.ncbi.nlm.nih.gov/pubmed/20132550 http://dx.doi.org/10.1186/1471-2105-11-74 |
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author | Gai, Xiaowu Perin, Juan C Murphy, Kevin O'Hara, Ryan D'arcy, Monica Wenocur, Adam Xie, Hongbo M Rappaport, Eric F Shaikh, Tamim H White, Peter S |
author_facet | Gai, Xiaowu Perin, Juan C Murphy, Kevin O'Hara, Ryan D'arcy, Monica Wenocur, Adam Xie, Hongbo M Rappaport, Eric F Shaikh, Tamim H White, Peter S |
author_sort | Gai, Xiaowu |
collection | PubMed |
description | BACKGROUND: Recent studies have shown that copy number variations (CNVs) are frequent in higher eukaryotes and associated with a substantial portion of inherited and acquired risk for various human diseases. The increasing availability of high-resolution genome surveillance platforms provides opportunity for rapidly assessing research and clinical samples for CNV content, as well as for determining the potential pathogenicity of identified variants. However, few informatics tools for accurate and efficient CNV detection and assessment currently exist. RESULTS: We developed a suite of software tools and resources (CNV Workshop) for automated, genome-wide CNV detection from a variety of SNP array platforms. CNV Workshop includes three major components: detection, annotation, and presentation of structural variants from genome array data. CNV detection utilizes a robust and genotype-specific extension of the Circular Binary Segmentation algorithm, and the use of additional detection algorithms is supported. Predicted CNVs are captured in a MySQL database that supports cohort-based projects and incorporates a secure user authentication layer and user/admin roles. To assist with determination of pathogenicity, detected CNVs are also annotated automatically for gene content, known disease loci, and gene-based literature references. Results are easily queried, sorted, filtered, and visualized via a web-based presentation layer that includes a GBrowse-based graphical representation of CNV content and relevant public data, integration with the UCSC Genome Browser, and tabular displays of genomic attributes for each CNV. CONCLUSIONS: To our knowledge, CNV Workshop represents the first cohesive and convenient platform for detection, annotation, and assessment of the biological and clinical significance of structural variants. CNV Workshop has been successfully utilized for assessment of genomic variation in healthy individuals and disease cohorts and is an ideal platform for coordinating multiple associated projects. AVAILABILITY AND IMPLEMENTATION: Available on the web at: http://sourceforge.net/projects/cnv |
format | Text |
id | pubmed-2827374 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-28273742010-02-24 CNV Workshop: an integrated platform for high-throughput copy number variation discovery and clinical diagnostics Gai, Xiaowu Perin, Juan C Murphy, Kevin O'Hara, Ryan D'arcy, Monica Wenocur, Adam Xie, Hongbo M Rappaport, Eric F Shaikh, Tamim H White, Peter S BMC Bioinformatics Software BACKGROUND: Recent studies have shown that copy number variations (CNVs) are frequent in higher eukaryotes and associated with a substantial portion of inherited and acquired risk for various human diseases. The increasing availability of high-resolution genome surveillance platforms provides opportunity for rapidly assessing research and clinical samples for CNV content, as well as for determining the potential pathogenicity of identified variants. However, few informatics tools for accurate and efficient CNV detection and assessment currently exist. RESULTS: We developed a suite of software tools and resources (CNV Workshop) for automated, genome-wide CNV detection from a variety of SNP array platforms. CNV Workshop includes three major components: detection, annotation, and presentation of structural variants from genome array data. CNV detection utilizes a robust and genotype-specific extension of the Circular Binary Segmentation algorithm, and the use of additional detection algorithms is supported. Predicted CNVs are captured in a MySQL database that supports cohort-based projects and incorporates a secure user authentication layer and user/admin roles. To assist with determination of pathogenicity, detected CNVs are also annotated automatically for gene content, known disease loci, and gene-based literature references. Results are easily queried, sorted, filtered, and visualized via a web-based presentation layer that includes a GBrowse-based graphical representation of CNV content and relevant public data, integration with the UCSC Genome Browser, and tabular displays of genomic attributes for each CNV. CONCLUSIONS: To our knowledge, CNV Workshop represents the first cohesive and convenient platform for detection, annotation, and assessment of the biological and clinical significance of structural variants. CNV Workshop has been successfully utilized for assessment of genomic variation in healthy individuals and disease cohorts and is an ideal platform for coordinating multiple associated projects. AVAILABILITY AND IMPLEMENTATION: Available on the web at: http://sourceforge.net/projects/cnv BioMed Central 2010-02-04 /pmc/articles/PMC2827374/ /pubmed/20132550 http://dx.doi.org/10.1186/1471-2105-11-74 Text en Copyright ©2010 Gai 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 | Software Gai, Xiaowu Perin, Juan C Murphy, Kevin O'Hara, Ryan D'arcy, Monica Wenocur, Adam Xie, Hongbo M Rappaport, Eric F Shaikh, Tamim H White, Peter S CNV Workshop: an integrated platform for high-throughput copy number variation discovery and clinical diagnostics |
title | CNV Workshop: an integrated platform for high-throughput copy number variation discovery and clinical diagnostics |
title_full | CNV Workshop: an integrated platform for high-throughput copy number variation discovery and clinical diagnostics |
title_fullStr | CNV Workshop: an integrated platform for high-throughput copy number variation discovery and clinical diagnostics |
title_full_unstemmed | CNV Workshop: an integrated platform for high-throughput copy number variation discovery and clinical diagnostics |
title_short | CNV Workshop: an integrated platform for high-throughput copy number variation discovery and clinical diagnostics |
title_sort | cnv workshop: an integrated platform for high-throughput copy number variation discovery and clinical diagnostics |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2827374/ https://www.ncbi.nlm.nih.gov/pubmed/20132550 http://dx.doi.org/10.1186/1471-2105-11-74 |
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