Loading…

New quality measure for SNP array based CNV detection

Only a few large systematic studies have evaluated the impact of copy number variants (CNVs) on common diseases. Several million individuals have been genotyped on single nucleotide variation arrays, which could be used for genome-wide CNVs association studies. However, CNV calls remain prone to fal...

Full description

Saved in:
Bibliographic Details
Published in:Bioinformatics (Oxford, England) England), 2016-11, Vol.32 (21), p.3298-3305
Main Authors: Macé, A, Tuke, M A, Beckmann, J S, Lin, L, Jacquemont, S, Weedon, M N, Reymond, A, Kutalik, Z
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c389t-9632040b5da2670fe99c7dc677631eb131dc6feb0c776a145f90b0ec9675d5e23
cites cdi_FETCH-LOGICAL-c389t-9632040b5da2670fe99c7dc677631eb131dc6feb0c776a145f90b0ec9675d5e23
container_end_page 3305
container_issue 21
container_start_page 3298
container_title Bioinformatics (Oxford, England)
container_volume 32
creator Macé, A
Tuke, M A
Beckmann, J S
Lin, L
Jacquemont, S
Weedon, M N
Reymond, A
Kutalik, Z
description Only a few large systematic studies have evaluated the impact of copy number variants (CNVs) on common diseases. Several million individuals have been genotyped on single nucleotide variation arrays, which could be used for genome-wide CNVs association studies. However, CNV calls remain prone to false positives and only empirical filtering strategies exist in the literature. To overcome this issue, we defined a new quality score (QS) estimating the probability of a CNV called by PennCNV to be confirmed by other software. Out-of-sample comparison showed that the correlation between the consensus CNV status and the QS is twice as high as it is for any previously proposed CNV filters. ROC curves displayed an AUC higher than 0.8 and simulations showed an increase up to 20% in statistical power when using QS in comparison to other filtering strategies. Superior performance was confirmed also for alternative consensus CNV definition and through improving known CNV-trait associations. http://goo.gl/T6yuFM CONTACT: zoltan.kutalik@unil.ch or aurelien@mace@unil.chSupplementary information: Supplementary data are available at Bioinformatics online.
doi_str_mv 10.1093/bioinformatics/btw477
format article
fullrecord <record><control><sourceid>pubmed_cross</sourceid><recordid>TN_cdi_crossref_primary_10_1093_bioinformatics_btw477</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>27402902</sourcerecordid><originalsourceid>FETCH-LOGICAL-c389t-9632040b5da2670fe99c7dc677631eb131dc6feb0c776a145f90b0ec9675d5e23</originalsourceid><addsrcrecordid>eNpVkF1LwzAUhoMobk5_gpI_UHfSNMlyKUWnMKrgx21J0lOorOtMUkb_vZXqwKtzzgvPC-ch5JrBLQPNl7bpml3d-dbExoWljYdMqRMyZ1yqJFsxdnrcgc_IRQifACBAyHMyS1UGqYZ0TkSBB_rVm20TB9qiCb1HOtbS1-KFGu_NQK0JWNG8-KAVRnSx6XaX5Kw224BXv3NB3h_u3_LHZPO8fsrvNonjKx0TLXkKGVhRmVQqqFFrpyonlZKcoWWcjUeNFtyYGJaJWoMFdFoqUQlM-YKIqdf5LgSPdbn3TWv8UDIofzSU_zWUk4aRu5m4fW9brI7U39_8G0tQXbs</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>New quality measure for SNP array based CNV detection</title><source>Oxford Journals Open Access Collection</source><source>PubMed Central</source><creator>Macé, A ; Tuke, M A ; Beckmann, J S ; Lin, L ; Jacquemont, S ; Weedon, M N ; Reymond, A ; Kutalik, Z</creator><creatorcontrib>Macé, A ; Tuke, M A ; Beckmann, J S ; Lin, L ; Jacquemont, S ; Weedon, M N ; Reymond, A ; Kutalik, Z</creatorcontrib><description>Only a few large systematic studies have evaluated the impact of copy number variants (CNVs) on common diseases. Several million individuals have been genotyped on single nucleotide variation arrays, which could be used for genome-wide CNVs association studies. However, CNV calls remain prone to false positives and only empirical filtering strategies exist in the literature. To overcome this issue, we defined a new quality score (QS) estimating the probability of a CNV called by PennCNV to be confirmed by other software. Out-of-sample comparison showed that the correlation between the consensus CNV status and the QS is twice as high as it is for any previously proposed CNV filters. ROC curves displayed an AUC higher than 0.8 and simulations showed an increase up to 20% in statistical power when using QS in comparison to other filtering strategies. Superior performance was confirmed also for alternative consensus CNV definition and through improving known CNV-trait associations. http://goo.gl/T6yuFM CONTACT: zoltan.kutalik@unil.ch or aurelien@mace@unil.chSupplementary information: Supplementary data are available at Bioinformatics online.</description><identifier>ISSN: 1367-4803</identifier><identifier>EISSN: 1367-4811</identifier><identifier>DOI: 10.1093/bioinformatics/btw477</identifier><identifier>PMID: 27402902</identifier><language>eng</language><publisher>England</publisher><subject>DNA Copy Number Variations ; Genome-Wide Association Study ; Humans ; Polymorphism, Single Nucleotide ; Software</subject><ispartof>Bioinformatics (Oxford, England), 2016-11, Vol.32 (21), p.3298-3305</ispartof><rights>The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c389t-9632040b5da2670fe99c7dc677631eb131dc6feb0c776a145f90b0ec9675d5e23</citedby><cites>FETCH-LOGICAL-c389t-9632040b5da2670fe99c7dc677631eb131dc6feb0c776a145f90b0ec9675d5e23</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/27402902$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Macé, A</creatorcontrib><creatorcontrib>Tuke, M A</creatorcontrib><creatorcontrib>Beckmann, J S</creatorcontrib><creatorcontrib>Lin, L</creatorcontrib><creatorcontrib>Jacquemont, S</creatorcontrib><creatorcontrib>Weedon, M N</creatorcontrib><creatorcontrib>Reymond, A</creatorcontrib><creatorcontrib>Kutalik, Z</creatorcontrib><title>New quality measure for SNP array based CNV detection</title><title>Bioinformatics (Oxford, England)</title><addtitle>Bioinformatics</addtitle><description>Only a few large systematic studies have evaluated the impact of copy number variants (CNVs) on common diseases. Several million individuals have been genotyped on single nucleotide variation arrays, which could be used for genome-wide CNVs association studies. However, CNV calls remain prone to false positives and only empirical filtering strategies exist in the literature. To overcome this issue, we defined a new quality score (QS) estimating the probability of a CNV called by PennCNV to be confirmed by other software. Out-of-sample comparison showed that the correlation between the consensus CNV status and the QS is twice as high as it is for any previously proposed CNV filters. ROC curves displayed an AUC higher than 0.8 and simulations showed an increase up to 20% in statistical power when using QS in comparison to other filtering strategies. Superior performance was confirmed also for alternative consensus CNV definition and through improving known CNV-trait associations. http://goo.gl/T6yuFM CONTACT: zoltan.kutalik@unil.ch or aurelien@mace@unil.chSupplementary information: Supplementary data are available at Bioinformatics online.</description><subject>DNA Copy Number Variations</subject><subject>Genome-Wide Association Study</subject><subject>Humans</subject><subject>Polymorphism, Single Nucleotide</subject><subject>Software</subject><issn>1367-4803</issn><issn>1367-4811</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><recordid>eNpVkF1LwzAUhoMobk5_gpI_UHfSNMlyKUWnMKrgx21J0lOorOtMUkb_vZXqwKtzzgvPC-ch5JrBLQPNl7bpml3d-dbExoWljYdMqRMyZ1yqJFsxdnrcgc_IRQifACBAyHMyS1UGqYZ0TkSBB_rVm20TB9qiCb1HOtbS1-KFGu_NQK0JWNG8-KAVRnSx6XaX5Kw224BXv3NB3h_u3_LHZPO8fsrvNonjKx0TLXkKGVhRmVQqqFFrpyonlZKcoWWcjUeNFtyYGJaJWoMFdFoqUQlM-YKIqdf5LgSPdbn3TWv8UDIofzSU_zWUk4aRu5m4fW9brI7U39_8G0tQXbs</recordid><startdate>20161101</startdate><enddate>20161101</enddate><creator>Macé, A</creator><creator>Tuke, M A</creator><creator>Beckmann, J S</creator><creator>Lin, L</creator><creator>Jacquemont, S</creator><creator>Weedon, M N</creator><creator>Reymond, A</creator><creator>Kutalik, Z</creator><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>20161101</creationdate><title>New quality measure for SNP array based CNV detection</title><author>Macé, A ; Tuke, M A ; Beckmann, J S ; Lin, L ; Jacquemont, S ; Weedon, M N ; Reymond, A ; Kutalik, Z</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c389t-9632040b5da2670fe99c7dc677631eb131dc6feb0c776a145f90b0ec9675d5e23</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>DNA Copy Number Variations</topic><topic>Genome-Wide Association Study</topic><topic>Humans</topic><topic>Polymorphism, Single Nucleotide</topic><topic>Software</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Macé, A</creatorcontrib><creatorcontrib>Tuke, M A</creatorcontrib><creatorcontrib>Beckmann, J S</creatorcontrib><creatorcontrib>Lin, L</creatorcontrib><creatorcontrib>Jacquemont, S</creatorcontrib><creatorcontrib>Weedon, M N</creatorcontrib><creatorcontrib>Reymond, A</creatorcontrib><creatorcontrib>Kutalik, Z</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><jtitle>Bioinformatics (Oxford, England)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Macé, A</au><au>Tuke, M A</au><au>Beckmann, J S</au><au>Lin, L</au><au>Jacquemont, S</au><au>Weedon, M N</au><au>Reymond, A</au><au>Kutalik, Z</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>New quality measure for SNP array based CNV detection</atitle><jtitle>Bioinformatics (Oxford, England)</jtitle><addtitle>Bioinformatics</addtitle><date>2016-11-01</date><risdate>2016</risdate><volume>32</volume><issue>21</issue><spage>3298</spage><epage>3305</epage><pages>3298-3305</pages><issn>1367-4803</issn><eissn>1367-4811</eissn><abstract>Only a few large systematic studies have evaluated the impact of copy number variants (CNVs) on common diseases. Several million individuals have been genotyped on single nucleotide variation arrays, which could be used for genome-wide CNVs association studies. However, CNV calls remain prone to false positives and only empirical filtering strategies exist in the literature. To overcome this issue, we defined a new quality score (QS) estimating the probability of a CNV called by PennCNV to be confirmed by other software. Out-of-sample comparison showed that the correlation between the consensus CNV status and the QS is twice as high as it is for any previously proposed CNV filters. ROC curves displayed an AUC higher than 0.8 and simulations showed an increase up to 20% in statistical power when using QS in comparison to other filtering strategies. Superior performance was confirmed also for alternative consensus CNV definition and through improving known CNV-trait associations. http://goo.gl/T6yuFM CONTACT: zoltan.kutalik@unil.ch or aurelien@mace@unil.chSupplementary information: Supplementary data are available at Bioinformatics online.</abstract><cop>England</cop><pmid>27402902</pmid><doi>10.1093/bioinformatics/btw477</doi><tpages>8</tpages><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 1367-4803
ispartof Bioinformatics (Oxford, England), 2016-11, Vol.32 (21), p.3298-3305
issn 1367-4803
1367-4811
language eng
recordid cdi_crossref_primary_10_1093_bioinformatics_btw477
source Oxford Journals Open Access Collection; PubMed Central
subjects DNA Copy Number Variations
Genome-Wide Association Study
Humans
Polymorphism, Single Nucleotide
Software
title New quality measure for SNP array based CNV detection
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-03T08%3A27%3A09IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-pubmed_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=New%20quality%20measure%20for%20SNP%20array%20based%20CNV%20detection&rft.jtitle=Bioinformatics%20(Oxford,%20England)&rft.au=Mac%C3%A9,%20A&rft.date=2016-11-01&rft.volume=32&rft.issue=21&rft.spage=3298&rft.epage=3305&rft.pages=3298-3305&rft.issn=1367-4803&rft.eissn=1367-4811&rft_id=info:doi/10.1093/bioinformatics/btw477&rft_dat=%3Cpubmed_cross%3E27402902%3C/pubmed_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c389t-9632040b5da2670fe99c7dc677631eb131dc6feb0c776a145f90b0ec9675d5e23%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/27402902&rfr_iscdi=true