Alternative Applications of Genotyping Array Data Using Multivariant Methods
One of the forerunners that pioneered the revolution of high-throughput genomic technologies is the genotyping microarray technology, which can genotype millions of single-nucleotide variants simultaneously. Owing to apparent benefits, such as high speed, low cost, and high throughput, the genotypin...
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description | One of the forerunners that pioneered the revolution of high-throughput genomic technologies is the genotyping microarray technology, which can genotype millions of single-nucleotide variants simultaneously. Owing to apparent benefits, such as high speed, low cost, and high throughput, the genotyping array has gained lasting applications in genome-wide association studies (GWAS) and thus accumulated an enormous amount of data. Empowered by continuous manufactural upgrades and analytical innovation, unconventional applications of genotyping array data have emerged to address more diverse genetic problems, holding promise of boosting genetic research into human diseases through the re-mining of the rich accumulated data. Here, we review several unconventional genotyping array analysis techniques that have been built on the idea of large-scale multivariant analysis and provide empirical application examples. These unconventional outcomes of genotyping arrays include polygenic score, runs of homozygosity (ROH)/heterozygosity ratio, distant pedigree computation, and mitochondrial DNA (mtDNA) copy number inference.
High-throughput genotyping arrays have been the driving force for identifying genetic variant associations with traits and phenotypes, but they can be used for far more.Novel statistical and bioinformatics methods have been developed to leverage the data from genotyping arrays, allowing a new and broader application of this established technology. These new techniques include: polygenic scores, detection of runs of homozygosity or the heterozygosity ratio, distant pedigree reconstruction, and inference of mitochondrial DNA copy number and heteroplasmy.A large amount of genotyping data has been accumulated in publicly accessible data repositories, forming a valuable resource for the use of these alternative applications to greatly extend the information that can be obtained from existing genetics studies. |
doi_str_mv | 10.1016/j.tig.2020.07.006 |
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High-throughput genotyping arrays have been the driving force for identifying genetic variant associations with traits and phenotypes, but they can be used for far more.Novel statistical and bioinformatics methods have been developed to leverage the data from genotyping arrays, allowing a new and broader application of this established technology. These new techniques include: polygenic scores, detection of runs of homozygosity or the heterozygosity ratio, distant pedigree reconstruction, and inference of mitochondrial DNA copy number and heteroplasmy.A large amount of genotyping data has been accumulated in publicly accessible data repositories, forming a valuable resource for the use of these alternative applications to greatly extend the information that can be obtained from existing genetics studies.</description><identifier>ISSN: 0168-9525</identifier><identifier>DOI: 10.1016/j.tig.2020.07.006</identifier><identifier>PMID: 32773169</identifier><language>eng</language><publisher>England: Elsevier Ltd</publisher><subject>Animals ; Computational Biology - methods ; Genome ; Genome-Wide Association Study ; Genomics ; Genotype ; Genotyping Techniques - methods ; Humans ; Oligonucleotide Array Sequence Analysis - methods ; Polymorphism, Single Nucleotide</subject><ispartof>Trends in genetics, 2020-11, Vol.36 (11), p.857-867</ispartof><rights>2020 Elsevier Ltd</rights><rights>Copyright © 2020 Elsevier Ltd. All rights reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c396t-bb748981be32a68cd1acebbd023c2c47fc592ce0c1ec8c52cc0e34caca40a7c53</citedby><cites>FETCH-LOGICAL-c396t-bb748981be32a68cd1acebbd023c2c47fc592ce0c1ec8c52cc0e34caca40a7c53</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.tig.2020.07.006$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32773169$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Samuels, David C.</creatorcontrib><creatorcontrib>Below, Jennifer E.</creatorcontrib><creatorcontrib>Ness, Scott</creatorcontrib><creatorcontrib>Yu, Hui</creatorcontrib><creatorcontrib>Leng, Shuguang</creatorcontrib><creatorcontrib>Guo, Yan</creatorcontrib><title>Alternative Applications of Genotyping Array Data Using Multivariant Methods</title><title>Trends in genetics</title><addtitle>Trends Genet</addtitle><description>One of the forerunners that pioneered the revolution of high-throughput genomic technologies is the genotyping microarray technology, which can genotype millions of single-nucleotide variants simultaneously. Owing to apparent benefits, such as high speed, low cost, and high throughput, the genotyping array has gained lasting applications in genome-wide association studies (GWAS) and thus accumulated an enormous amount of data. Empowered by continuous manufactural upgrades and analytical innovation, unconventional applications of genotyping array data have emerged to address more diverse genetic problems, holding promise of boosting genetic research into human diseases through the re-mining of the rich accumulated data. Here, we review several unconventional genotyping array analysis techniques that have been built on the idea of large-scale multivariant analysis and provide empirical application examples. These unconventional outcomes of genotyping arrays include polygenic score, runs of homozygosity (ROH)/heterozygosity ratio, distant pedigree computation, and mitochondrial DNA (mtDNA) copy number inference.
High-throughput genotyping arrays have been the driving force for identifying genetic variant associations with traits and phenotypes, but they can be used for far more.Novel statistical and bioinformatics methods have been developed to leverage the data from genotyping arrays, allowing a new and broader application of this established technology. These new techniques include: polygenic scores, detection of runs of homozygosity or the heterozygosity ratio, distant pedigree reconstruction, and inference of mitochondrial DNA copy number and heteroplasmy.A large amount of genotyping data has been accumulated in publicly accessible data repositories, forming a valuable resource for the use of these alternative applications to greatly extend the information that can be obtained from existing genetics studies.</description><subject>Animals</subject><subject>Computational Biology - methods</subject><subject>Genome</subject><subject>Genome-Wide Association Study</subject><subject>Genomics</subject><subject>Genotype</subject><subject>Genotyping Techniques - methods</subject><subject>Humans</subject><subject>Oligonucleotide Array Sequence Analysis - methods</subject><subject>Polymorphism, Single Nucleotide</subject><issn>0168-9525</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kE1PAjEQhnvQCKI_wIvZoxfWabuf8URQ0QTiRc5Nd3bAkmV3bQsJ_94S0KOnmUye903mYeyOQ8yBZ4-b2Jt1LEBADHkMkF2wYbgX4zIV6YBdO7cBgDSX6RUbSJHnkmflkM0njSfbam_2FE36vjEY9q51UbeKZtR2_tCbdh1NrNWH6Fl7HS3d8bDYNSGjrdGtjxbkv7ra3bDLlW4c3Z7niC1fXz6nb-P5x-x9OpmPUZaZH1dVnhRlwSuSQmcF1lwjVVUNQqLAJF9hWgokQE5YYCoQgWSCGnUCOsdUjtjDqbe33feOnFdb45CaRrfU7ZwSiRRFJkrgAeUnFG3nnKWV6q3ZantQHNRRnNqoIE4dxSnIVRAXMvfn-l21pfov8WstAE8ngMKTe0NWOTTUItXGEnpVd-af-h-USIG5</recordid><startdate>202011</startdate><enddate>202011</enddate><creator>Samuels, David C.</creator><creator>Below, Jennifer E.</creator><creator>Ness, Scott</creator><creator>Yu, Hui</creator><creator>Leng, Shuguang</creator><creator>Guo, Yan</creator><general>Elsevier Ltd</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>202011</creationdate><title>Alternative Applications of Genotyping Array Data Using Multivariant Methods</title><author>Samuels, David C. ; Below, Jennifer E. ; Ness, Scott ; Yu, Hui ; Leng, Shuguang ; Guo, Yan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c396t-bb748981be32a68cd1acebbd023c2c47fc592ce0c1ec8c52cc0e34caca40a7c53</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Animals</topic><topic>Computational Biology - methods</topic><topic>Genome</topic><topic>Genome-Wide Association Study</topic><topic>Genomics</topic><topic>Genotype</topic><topic>Genotyping Techniques - methods</topic><topic>Humans</topic><topic>Oligonucleotide Array Sequence Analysis - methods</topic><topic>Polymorphism, Single Nucleotide</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Samuels, David C.</creatorcontrib><creatorcontrib>Below, Jennifer E.</creatorcontrib><creatorcontrib>Ness, Scott</creatorcontrib><creatorcontrib>Yu, Hui</creatorcontrib><creatorcontrib>Leng, Shuguang</creatorcontrib><creatorcontrib>Guo, Yan</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Trends in genetics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Samuels, David C.</au><au>Below, Jennifer E.</au><au>Ness, Scott</au><au>Yu, Hui</au><au>Leng, Shuguang</au><au>Guo, Yan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Alternative Applications of Genotyping Array Data Using Multivariant Methods</atitle><jtitle>Trends in genetics</jtitle><addtitle>Trends Genet</addtitle><date>2020-11</date><risdate>2020</risdate><volume>36</volume><issue>11</issue><spage>857</spage><epage>867</epage><pages>857-867</pages><issn>0168-9525</issn><abstract>One of the forerunners that pioneered the revolution of high-throughput genomic technologies is the genotyping microarray technology, which can genotype millions of single-nucleotide variants simultaneously. 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High-throughput genotyping arrays have been the driving force for identifying genetic variant associations with traits and phenotypes, but they can be used for far more.Novel statistical and bioinformatics methods have been developed to leverage the data from genotyping arrays, allowing a new and broader application of this established technology. These new techniques include: polygenic scores, detection of runs of homozygosity or the heterozygosity ratio, distant pedigree reconstruction, and inference of mitochondrial DNA copy number and heteroplasmy.A large amount of genotyping data has been accumulated in publicly accessible data repositories, forming a valuable resource for the use of these alternative applications to greatly extend the information that can be obtained from existing genetics studies.</abstract><cop>England</cop><pub>Elsevier Ltd</pub><pmid>32773169</pmid><doi>10.1016/j.tig.2020.07.006</doi><tpages>11</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Animals Computational Biology - methods Genome Genome-Wide Association Study Genomics Genotype Genotyping Techniques - methods Humans Oligonucleotide Array Sequence Analysis - methods Polymorphism, Single Nucleotide |
title | Alternative Applications of Genotyping Array Data Using Multivariant Methods |
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