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Breaking the waves: improved detection of copy number variation from microarray-based comparative genomic hybridization

Marioni, John C; Thorne, Natalie P; Valsesia, Armand; Fitzgerald, Tomas; Redon, Richard; Fiegler, Heike; Andrews, T Daniel; Stranger, Barbara E; Lynch, Andrew G; Dermitzakis, Emmanouil T; Carter, Nigel P; Tavaré, Simon; Hurles, Matthew E

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BACKGROUND Large-scale high throughput studies using microarray technology have established that copy number variation (CNV) throughout the genome is more frequent than previously thought. Such variation is known to play an important role in the presence and development of phenotypes such as HIV-1 infection and Alzheimer's disease. However, methods for analyzing the complex data produced and identifying regions of CNV are still being refined. RESULTS We describe the presence of a genome-wide...[Show more]

dc.contributor.authorMarioni, John C
dc.contributor.authorThorne, Natalie P
dc.contributor.authorValsesia, Armand
dc.contributor.authorFitzgerald, Tomas
dc.contributor.authorRedon, Richard
dc.contributor.authorFiegler, Heike
dc.contributor.authorAndrews, T Daniel
dc.contributor.authorStranger, Barbara E
dc.contributor.authorLynch, Andrew G
dc.contributor.authorDermitzakis, Emmanouil T
dc.contributor.authorCarter, Nigel P
dc.contributor.authorTavaré, Simon
dc.contributor.authorHurles, Matthew E
dc.date.accessioned2016-01-13T00:14:00Z
dc.date.available2016-01-13T00:14:00Z
dc.identifier.issn1465-6906
dc.identifier.urihttp://hdl.handle.net/1885/95363
dc.description.abstractBACKGROUND Large-scale high throughput studies using microarray technology have established that copy number variation (CNV) throughout the genome is more frequent than previously thought. Such variation is known to play an important role in the presence and development of phenotypes such as HIV-1 infection and Alzheimer's disease. However, methods for analyzing the complex data produced and identifying regions of CNV are still being refined. RESULTS We describe the presence of a genome-wide technical artifact, spatial autocorrelation or 'wave', which occurs in a large dataset used to determine the location of CNV across the genome. By removing this artifact we are able to obtain both a more biologically meaningful clustering of the data and an increase in the number of CNVs identified by current calling methods without a major increase in the number of false positives detected. Moreover, removing this artifact is critical for the development of a novel model-based CNV calling algorithm - CNVmix - that uses cross-sample information to identify regions of the genome where CNVs occur. For regions of CNV that are identified by both CNVmix and current methods, we demonstrate that CNVmix is better able to categorize samples into groups that represent copy number gains or losses. CONCLUSION Removing artifactual 'waves' (which appear to be a general feature of array comparative genomic hybridization (aCGH) datasets) and using cross-sample information when identifying CNVs enables more biological information to be extracted from aCGH experiments designed to investigate copy number variation in normal individuals.
dc.description.sponsorshipCancer Research UK supports JCM, NPT, AGL and ST. ST is a Royal Society/Wolfson Research Merit Award holder. The Wellcome Trust funds RR, HF, AV, TDA, TF, BES, ETD, NPC and MEH.
dc.publisherBioMed Central
dc.rights© 2007 Marioni et al.; licensee BioMed Central Ltd. 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.
dc.sourceGenome Biology
dc.subjectdata interpretation, statistical
dc.subjectgene dosage
dc.subjectmicroarray analysis
dc.subjectnucleic acid hybridization
dc.subjectalgorithms
dc.subjectgenetic variation
dc.titleBreaking the waves: improved detection of copy number variation from microarray-based comparative genomic hybridization
dc.typeJournal article
local.description.notesImported from ARIES. At the time of publication the author Andrews was affiliated with The Wellcome Trust Sanger Institute, The Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK
local.identifier.citationvolume8
dc.date.issued2007-10-25
local.identifier.absfor060102
local.identifier.absfor060408
local.identifier.ariespublicationu6800332xPUB154
local.publisher.urlhttp://www.biomedcentral.com/
local.type.statusPublished Version
local.contributor.affiliationMarioni, John, University of Cambridge, United Kingdom
local.contributor.affiliationThorne, Natalie, University of Cambridge, United Kingdom
local.contributor.affiliationValsesia, Armand, The Wellcome Trust Genome Campus, United Kingdom
local.contributor.affiliationFitzgerald, Tomas, The Wellcome Trust Genome Campus, United Kingdom
local.contributor.affiliationRedon, Richard, Wellcome Trust Genome Campus, United Kingdom
local.contributor.affiliationFiegler, Heike, The Wellcome Trust Genome Campus, United Kingdom
local.contributor.affiliationAndrews, Thomas Daniel, College of Medicine, Biology and Environment, CMBE John Curtin School of Medical Research, Immunology and Infectious Disease, The Australian National University
local.contributor.affiliationStranger, Barbara, The Wellcome Trust Genome Campus, United Kingdom
local.contributor.affiliationLynch, Andrew, University of Cambridge, United Kingdom
local.contributor.affiliationDermitzakis, Emmanouil, University of Geneva, Switzerland
local.contributor.affiliationCarter, Nigel, The Wellcome Trust Genome Campus, United Kingdom
local.contributor.affiliationTavare, Simon, University of Cambridge, United Kingdom
local.contributor.affiliationHurles, Matthew, Wellcome Trust Genome Campus, United Kingdom
local.identifier.essn1474-760X
local.bibliographicCitation.issue10
local.bibliographicCitation.startpageR228
local.identifier.doi10.1186/gb-2007-8-10-r228
dc.date.updated2016-02-24T11:38:00Z
local.identifier.scopusID2-s2.0-42949174747
CollectionsANU Research Publications

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