NeuroX, a fast and efficient genotyping platform for investigation of neurodegenerative diseases.
Identifieur interne : 000479 ( Ncbi/Merge ); précédent : 000478; suivant : 000480NeuroX, a fast and efficient genotyping platform for investigation of neurodegenerative diseases.
Auteurs : Mike. Nalls ; Jose Bras ; Dena. Hernandez ; Margaux. Keller ; Elisa Majounie ; Alan. Renton ; Mohamad Saad ; Iris Jansen ; Rita Guerreiro ; Steven Lubbe ; Vincent Plagnol ; J Gibbs ; Claudia Schulte ; Nathan Pankratz ; Margaret Sutherland ; Lars Bertram ; Christina. Lill ; Anita. Destefano ; Tatiana Faroud ; Nicholas Eriksson ; Joyce. Tung ; Connor Edsall ; Noah Nichols ; Janet Brooks ; Sampath Arepalli ; Hannah Pliner ; Chris Letson ; Peter Heutink ; Maria Martinez ; Thomas Gasser ; Bryan. Traynor ; Nick Wood ; John Hardy ; Andrew. SingletonSource :
- Neurobiology of aging ; 2015.
English descriptors
- KwdEn :
- MESH :
Abstract
Our objective was to design a genotyping platform that would allow rapid genetic characterization of samples in the context of genetic mutations and risk factors associated with common neurodegenerative diseases. The platform needed to be relatively affordable, rapid to deploy, and use a common and accessible technology. Central to this project, we wanted to make the content of the platform open to any investigator without restriction. In designing this array we prioritized a number of types of genetic variability for inclusion, such as known risk alleles, disease-causing mutations, putative risk alleles, and other functionally important variants. The array was primarily designed to allow rapid screening of samples for disease-causing mutations and large population studies of risk factors. Notably, an explicit aim was to make this array widely available to facilitate data sharing across and within diseases. The resulting array, NeuroX, is a remarkably cost and time effective solution for high-quality genotyping. NeuroX comprises a backbone of standard Illumina exome content of approximately 240,000 variants, and over 24,000 custom content variants focusing on neurologic diseases. Data are generated at approximately $50-$60 per sample using a 12-sample format chip and regular Infinium infrastructure; thus, genotyping is rapid and accessible to many investigators. Here, we describe the design of NeuroX, discuss the utility of NeuroX in the analyses of rare and common risk variants, and present quality control metrics and a brief primer for the analysis of NeuroX derived data.
DOI: 10.1016/j.neurobiolaging.2014.07.028
PubMed: 25444595
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pubmed:25444595Le document en format XML
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<term>Genetic Predisposition to Disease (genetics)</term>
<term>Genetic Variation</term>
<term>Genotyping Techniques (economics)</term>
<term>Genotyping Techniques (methods)</term>
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<front><div type="abstract" xml:lang="en">Our objective was to design a genotyping platform that would allow rapid genetic characterization of samples in the context of genetic mutations and risk factors associated with common neurodegenerative diseases. The platform needed to be relatively affordable, rapid to deploy, and use a common and accessible technology. Central to this project, we wanted to make the content of the platform open to any investigator without restriction. In designing this array we prioritized a number of types of genetic variability for inclusion, such as known risk alleles, disease-causing mutations, putative risk alleles, and other functionally important variants. The array was primarily designed to allow rapid screening of samples for disease-causing mutations and large population studies of risk factors. Notably, an explicit aim was to make this array widely available to facilitate data sharing across and within diseases. The resulting array, NeuroX, is a remarkably cost and time effective solution for high-quality genotyping. NeuroX comprises a backbone of standard Illumina exome content of approximately 240,000 variants, and over 24,000 custom content variants focusing on neurologic diseases. Data are generated at approximately $50-$60 per sample using a 12-sample format chip and regular Infinium infrastructure; thus, genotyping is rapid and accessible to many investigators. Here, we describe the design of NeuroX, discuss the utility of NeuroX in the analyses of rare and common risk variants, and present quality control metrics and a brief primer for the analysis of NeuroX derived data.</div>
</front>
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<Title>Neurobiology of aging</Title>
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<ArticleTitle>NeuroX, a fast and efficient genotyping platform for investigation of neurodegenerative diseases.</ArticleTitle>
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<Abstract><AbstractText>Our objective was to design a genotyping platform that would allow rapid genetic characterization of samples in the context of genetic mutations and risk factors associated with common neurodegenerative diseases. The platform needed to be relatively affordable, rapid to deploy, and use a common and accessible technology. Central to this project, we wanted to make the content of the platform open to any investigator without restriction. In designing this array we prioritized a number of types of genetic variability for inclusion, such as known risk alleles, disease-causing mutations, putative risk alleles, and other functionally important variants. The array was primarily designed to allow rapid screening of samples for disease-causing mutations and large population studies of risk factors. Notably, an explicit aim was to make this array widely available to facilitate data sharing across and within diseases. The resulting array, NeuroX, is a remarkably cost and time effective solution for high-quality genotyping. NeuroX comprises a backbone of standard Illumina exome content of approximately 240,000 variants, and over 24,000 custom content variants focusing on neurologic diseases. Data are generated at approximately $50-$60 per sample using a 12-sample format chip and regular Infinium infrastructure; thus, genotyping is rapid and accessible to many investigators. Here, we describe the design of NeuroX, discuss the utility of NeuroX in the analyses of rare and common risk variants, and present quality control metrics and a brief primer for the analysis of NeuroX derived data.</AbstractText>
<CopyrightInformation>Published by Elsevier Inc.</CopyrightInformation>
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<ForeName>Thomas</ForeName>
<Initials>T</Initials>
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<Author ValidYN="Y"><LastName>Traynor</LastName>
<ForeName>Bryan J</ForeName>
<Initials>BJ</Initials>
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<ForeName>Nick</ForeName>
<Initials>N</Initials>
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<Author ValidYN="Y"><LastName>Hardy</LastName>
<ForeName>John</ForeName>
<Initials>J</Initials>
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<Author ValidYN="Y"><LastName>Singleton</LastName>
<ForeName>Andrew B</ForeName>
<Initials>AB</Initials>
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<Author ValidYN="Y"><CollectiveName>International Parkinson's Disease Genomics Consortium (IPDGC)</CollectiveName>
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<Author ValidYN="Y"><CollectiveName>Parkinson's Disease meta-analysis consortium</CollectiveName>
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<Language>eng</Language>
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<Agency>Wellcome Trust</Agency>
<Country>United Kingdom</Country>
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<Grant><GrantID>HL-102923</GrantID>
<Acronym>HL</Acronym>
<Agency>NHLBI NIH HHS</Agency>
<Country>United States</Country>
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<Country>United States</Country>
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<Grant><GrantID>HL-103010</GrantID>
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<Agency>NHLBI NIH HHS</Agency>
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<Investigator ValidYN="Y"><LastName>Singleton</LastName>
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<Investigator ValidYN="Y"><LastName>Saunders-Pullman</LastName>
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<Initials>K</Initials>
</Investigator>
<Investigator ValidYN="Y"><LastName>Costan-Toth</LastName>
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</Investigator>
<Investigator ValidYN="Y"><LastName>Ohmann</LastName>
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</Investigator>
<Investigator ValidYN="Y"><LastName>Sudarsky</LastName>
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<Investigator ValidYN="Y"><LastName>Joubert</LastName>
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</Investigator>
<Investigator ValidYN="Y"><LastName>Friedman</LastName>
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</Investigator>
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<Investigator ValidYN="Y"><LastName>Fernandez</LastName>
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</Investigator>
<Investigator ValidYN="Y"><LastName>Lannon</LastName>
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</Investigator>
<Investigator ValidYN="Y"><LastName>Galvez-Jimenez</LastName>
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</Investigator>
<Investigator ValidYN="Y"><LastName>Podichetty</LastName>
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</Investigator>
<Investigator ValidYN="Y"><LastName>Thompson</LastName>
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</Investigator>
<Investigator ValidYN="Y"><LastName>Lewitt</LastName>
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</Investigator>
<Investigator ValidYN="Y"><LastName>DeAngelis</LastName>
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</Investigator>
<Investigator ValidYN="Y"><LastName>O'Brien</LastName>
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</Investigator>
<Investigator ValidYN="Y"><LastName>Seeberger</LastName>
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</Investigator>
<Investigator ValidYN="Y"><LastName>Dingmann</LastName>
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</Investigator>
<Investigator ValidYN="Y"><LastName>Judd</LastName>
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</Investigator>
<Investigator ValidYN="Y"><LastName>Marder</LastName>
<ForeName>K</ForeName>
<Initials>K</Initials>
</Investigator>
<Investigator ValidYN="Y"><LastName>Fraser</LastName>
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</Investigator>
<Investigator ValidYN="Y"><LastName>Harris</LastName>
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<Initials>J</Initials>
</Investigator>
<Investigator ValidYN="Y"><LastName>Bertoni</LastName>
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</Investigator>
<Investigator ValidYN="Y"><LastName>Peterson</LastName>
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<Initials>C</Initials>
</Investigator>
<Investigator ValidYN="Y"><LastName>Rezak</LastName>
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</Investigator>
<Investigator ValidYN="Y"><LastName>Medalle</LastName>
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</Investigator>
<Investigator ValidYN="Y"><LastName>Chouinard</LastName>
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</Investigator>
<Investigator ValidYN="Y"><LastName>Panisset</LastName>
<ForeName>M</ForeName>
<Initials>M</Initials>
</Investigator>
<Investigator ValidYN="Y"><LastName>Hall</LastName>
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</Investigator>
<Investigator ValidYN="Y"><LastName>Poiffaut</LastName>
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<Initials>H</Initials>
</Investigator>
<Investigator ValidYN="Y"><LastName>Calabrese</LastName>
<ForeName>V</ForeName>
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</Investigator>
<Investigator ValidYN="Y"><LastName>Roberge</LastName>
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<Initials>P</Initials>
</Investigator>
<Investigator ValidYN="Y"><LastName>Wojcieszek</LastName>
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</Investigator>
<Investigator ValidYN="Y"><LastName>Belden</LastName>
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</Investigator>
<Investigator ValidYN="Y"><LastName>Jennings</LastName>
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</Investigator>
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</Investigator>
<Investigator ValidYN="Y"><LastName>Mendick</LastName>
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</Investigator>
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<ForeName>S</ForeName>
<Initials>S</Initials>
</Investigator>
<Investigator ValidYN="Y"><LastName>Dunlop</LastName>
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<Initials>B</Initials>
</Investigator>
<Investigator ValidYN="Y"><LastName>Jog</LastName>
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<Initials>M</Initials>
</Investigator>
<Investigator ValidYN="Y"><LastName>Horn</LastName>
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</Investigator>
<Investigator ValidYN="Y"><LastName>Uitti</LastName>
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</Investigator>
<Investigator ValidYN="Y"><LastName>Turk</LastName>
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<Initials>M</Initials>
</Investigator>
<Investigator ValidYN="Y"><LastName>Ajax</LastName>
<ForeName>T</ForeName>
<Initials>T</Initials>
</Investigator>
<Investigator ValidYN="Y"><LastName>Mannetter</LastName>
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</Investigator>
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</Investigator>
<Investigator ValidYN="Y"><LastName>Carpenter</LastName>
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</Investigator>
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</Investigator>
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<Initials>L</Initials>
</Investigator>
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</Investigator>
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</Investigator>
<Investigator ValidYN="Y"><LastName>Blindauer</LastName>
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</Investigator>
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</Investigator>
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</Investigator>
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</Investigator>
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</Investigator>
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</Investigator>
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</Investigator>
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</Investigator>
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</Investigator>
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</Investigator>
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</Investigator>
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</Investigator>
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</Investigator>
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<Investigator ValidYN="Y"><LastName>Pfeiffer</LastName>
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</Investigator>
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</Investigator>
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</Investigator>
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</Investigator>
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</Investigator>
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</Investigator>
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</Investigator>
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<name sortKey="Lill, Christina M" sort="Lill, Christina M" uniqKey="Lill C" first="Christina" last="Lill">Christina. Lill</name>
<name sortKey="Lubbe, Steven" sort="Lubbe, Steven" uniqKey="Lubbe S" first="Steven" last="Lubbe">Steven Lubbe</name>
<name sortKey="Majounie, Elisa" sort="Majounie, Elisa" uniqKey="Majounie E" first="Elisa" last="Majounie">Elisa Majounie</name>
<name sortKey="Martinez, Maria" sort="Martinez, Maria" uniqKey="Martinez M" first="Maria" last="Martinez">Maria Martinez</name>
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<name sortKey="Nichols, Noah" sort="Nichols, Noah" uniqKey="Nichols N" first="Noah" last="Nichols">Noah Nichols</name>
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<name sortKey="Renton, Alan E" sort="Renton, Alan E" uniqKey="Renton A" first="Alan" last="Renton">Alan. Renton</name>
<name sortKey="Saad, Mohamad" sort="Saad, Mohamad" uniqKey="Saad M" first="Mohamad" last="Saad">Mohamad Saad</name>
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