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Novel measures of linkage disequilibrium that correct the bias due to population structure and relatedness
Among the several linkage disequilibrium measures known to capture different features of the non-independence between alleles at different loci, the most commonly used for diallelic loci is the r 2 measure. In the present study, we tackled the problem of the bias of r 2 estimate, which results from...
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| Published in: | Heredity 2012-03, Vol.108 (3), p.285-291 |
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| creator | Mangin, B Siberchicot, A Nicolas, S Doligez, A This, P Cierco-Ayrolles, C |
| description | Among the several linkage disequilibrium measures known to capture different features of the non-independence between alleles at different loci, the most commonly used for diallelic loci is the
r
2
measure. In the present study, we tackled the problem of the bias of
r
2
estimate, which results from the sample structure and/or the relatedness between genotyped individuals. We derived two novel linkage disequilibrium measures for diallelic loci that are both extensions of the usual
r
2
measure. The first one,
r
S
2
, uses the population structure matrix, which consists of information about the origins of each individual and the admixture proportions of each individual genome. The second one,
r
V
2
, includes the kinship matrix into the calculation. These two corrections can be applied together in order to correct for both biases and are defined either on phased or unphased genotypes.
We proved that these novel measures are linked to the power of association tests under the mixed linear model including structure and kinship corrections. We validated them on simulated data and applied them to real data sets collected on
Vitis vinifera
plants. Our results clearly showed the usefulness of the two corrected
r
2
measures, which actually captured ‘true’ linkage disequilibrium unlike the usual
r
2
measure. |
| doi_str_mv | 10.1038/hdy.2011.73 |
| format | article |
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r
2
measure. In the present study, we tackled the problem of the bias of
r
2
estimate, which results from the sample structure and/or the relatedness between genotyped individuals. We derived two novel linkage disequilibrium measures for diallelic loci that are both extensions of the usual
r
2
measure. The first one,
r
S
2
, uses the population structure matrix, which consists of information about the origins of each individual and the admixture proportions of each individual genome. The second one,
r
V
2
, includes the kinship matrix into the calculation. These two corrections can be applied together in order to correct for both biases and are defined either on phased or unphased genotypes.
We proved that these novel measures are linked to the power of association tests under the mixed linear model including structure and kinship corrections. We validated them on simulated data and applied them to real data sets collected on
Vitis vinifera
plants. Our results clearly showed the usefulness of the two corrected
r
2
measures, which actually captured ‘true’ linkage disequilibrium unlike the usual
r
2
measure.</description><identifier>ISSN: 0018-067X</identifier><identifier>EISSN: 1365-2540</identifier><identifier>EISSN: 0018-067X</identifier><identifier>DOI: 10.1038/hdy.2011.73</identifier><identifier>PMID: 21878986</identifier><identifier>CODEN: HDTYAT</identifier><language>eng</language><publisher>Cham: Springer International Publishing</publisher><subject>Alleles ; Bias ; Biomedical and Life Sciences ; Biomedicine ; Computer Simulation ; Cytogenetics ; Disequilibrium ; Ecology ; Evolutionary Biology ; Gene loci ; Genetics, Population ; Genotype ; Genotypes ; Human Genetics ; Human health and pathology ; Life Sciences ; Linkage Disequilibrium ; Models, Genetic ; Original ; original-article ; Plant Genetics and Genomics ; Polymorphism, Single Nucleotide ; Population structure ; Reproducibility of Results ; Vitis - genetics ; Vitis vinifera</subject><ispartof>Heredity, 2012-03, Vol.108 (3), p.285-291</ispartof><rights>The Genetics Society 2012</rights><rights>Copyright Nature Publishing Group Mar 2012</rights><rights>Distributed under a Creative Commons Attribution 4.0 International License</rights><rights>Copyright © 2012 The Genetics Society 2012 The Genetics Society</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c510t-7e6b816c9d1448558bf246f9690a95832019293a6bfaf66d680a02e004ee8f5d3</citedby><cites>FETCH-LOGICAL-c510t-7e6b816c9d1448558bf246f9690a95832019293a6bfaf66d680a02e004ee8f5d3</cites><orcidid>0000-0002-3159-5903 ; 0000-0002-3024-5813 ; 0000-0002-7638-8318</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3282397/pdf/$$EPDF$$P50$$Gpubmedcentral$$H</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3282397/$$EHTML$$P50$$Gpubmedcentral$$H</linktohtml><link.rule.ids>230,314,723,776,780,881,27901,27902,53766,53768</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/21878986$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink><backlink>$$Uhttps://hal.science/hal-01267769$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Mangin, B</creatorcontrib><creatorcontrib>Siberchicot, A</creatorcontrib><creatorcontrib>Nicolas, S</creatorcontrib><creatorcontrib>Doligez, A</creatorcontrib><creatorcontrib>This, P</creatorcontrib><creatorcontrib>Cierco-Ayrolles, C</creatorcontrib><title>Novel measures of linkage disequilibrium that correct the bias due to population structure and relatedness</title><title>Heredity</title><addtitle>Heredity</addtitle><addtitle>Heredity (Edinb)</addtitle><description>Among the several linkage disequilibrium measures known to capture different features of the non-independence between alleles at different loci, the most commonly used for diallelic loci is the
r
2
measure. In the present study, we tackled the problem of the bias of
r
2
estimate, which results from the sample structure and/or the relatedness between genotyped individuals. We derived two novel linkage disequilibrium measures for diallelic loci that are both extensions of the usual
r
2
measure. The first one,
r
S
2
, uses the population structure matrix, which consists of information about the origins of each individual and the admixture proportions of each individual genome. The second one,
r
V
2
, includes the kinship matrix into the calculation. These two corrections can be applied together in order to correct for both biases and are defined either on phased or unphased genotypes.
We proved that these novel measures are linked to the power of association tests under the mixed linear model including structure and kinship corrections. We validated them on simulated data and applied them to real data sets collected on
Vitis vinifera
plants. Our results clearly showed the usefulness of the two corrected
r
2
measures, which actually captured ‘true’ linkage disequilibrium unlike the usual
r
2
measure.</description><subject>Alleles</subject><subject>Bias</subject><subject>Biomedical and Life Sciences</subject><subject>Biomedicine</subject><subject>Computer Simulation</subject><subject>Cytogenetics</subject><subject>Disequilibrium</subject><subject>Ecology</subject><subject>Evolutionary Biology</subject><subject>Gene loci</subject><subject>Genetics, Population</subject><subject>Genotype</subject><subject>Genotypes</subject><subject>Human Genetics</subject><subject>Human health and pathology</subject><subject>Life Sciences</subject><subject>Linkage Disequilibrium</subject><subject>Models, Genetic</subject><subject>Original</subject><subject>original-article</subject><subject>Plant Genetics and Genomics</subject><subject>Polymorphism, Single Nucleotide</subject><subject>Population structure</subject><subject>Reproducibility of Results</subject><subject>Vitis - genetics</subject><subject>Vitis vinifera</subject><issn>0018-067X</issn><issn>1365-2540</issn><issn>0018-067X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2012</creationdate><recordtype>article</recordtype><recordid>eNqFkstrFEEQxhtRzBo9eZfGi4jO2o-ZflwCISRGWPSi4K3pmanZ7XV2etOPhfz39rAxahA8FV31q6-qiw-hl5QsKeHqw6a_XTJC6VLyR2hBuWgq1tTkMVoQQlVFhPx-gp7FuCWEcMn0U3TCqJJKK7FA28_-ACPegY05QMR-wKObftg14N5FuMludG1weYfTxibc-RCgS-UBuHU24j4DTh7v_T6PNjk_4ZhC7lIRw3bqcYCShn6CGJ-jJ4MdI7y4i6fo29Xl14vravXl46eL81XVNZSkSoJoFRWd7mldq6ZR7cBqMWihidWN4uWrmmluRTvYQYheKGIJA0JqADU0PT9FZ0fdfW530HcwpWBHsw9uZ8Ot8daZvyuT25i1PxjOFONaFoG3R4HNg7br85WZc4QyIaXQB1rYN3fDgr_JEJPZudjBONoJfI5GC0VlLTX5P8mopLpWs-brB-TW5zCVm81QQxlT85LvjlAXfIwBhvtNKTGzL0zxhZl9YSQv9Ks_b3LP_jJCAd4fgVhK0xrC75n_0vsJ6eHDCw</recordid><startdate>20120301</startdate><enddate>20120301</enddate><creator>Mangin, B</creator><creator>Siberchicot, A</creator><creator>Nicolas, S</creator><creator>Doligez, A</creator><creator>This, P</creator><creator>Cierco-Ayrolles, C</creator><general>Springer International Publishing</general><general>Springer Nature B.V</general><general>Nature Publishing Group</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>3V.</scope><scope>7QL</scope><scope>7SN</scope><scope>7SS</scope><scope>7T7</scope><scope>7TK</scope><scope>7U9</scope><scope>7X7</scope><scope>7XB</scope><scope>88A</scope><scope>88E</scope><scope>88I</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M2O</scope><scope>M2P</scope><scope>M7N</scope><scope>M7P</scope><scope>MBDVC</scope><scope>P64</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope><scope>RC3</scope><scope>7X8</scope><scope>1XC</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-3159-5903</orcidid><orcidid>https://orcid.org/0000-0002-3024-5813</orcidid><orcidid>https://orcid.org/0000-0002-7638-8318</orcidid></search><sort><creationdate>20120301</creationdate><title>Novel measures of linkage disequilibrium that correct the bias due to population structure and relatedness</title><author>Mangin, B ; Siberchicot, A ; Nicolas, S ; Doligez, A ; This, P ; Cierco-Ayrolles, C</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c510t-7e6b816c9d1448558bf246f9690a95832019293a6bfaf66d680a02e004ee8f5d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Alleles</topic><topic>Bias</topic><topic>Biomedical and Life Sciences</topic><topic>Biomedicine</topic><topic>Computer Simulation</topic><topic>Cytogenetics</topic><topic>Disequilibrium</topic><topic>Ecology</topic><topic>Evolutionary Biology</topic><topic>Gene loci</topic><topic>Genetics, Population</topic><topic>Genotype</topic><topic>Genotypes</topic><topic>Human Genetics</topic><topic>Human health and pathology</topic><topic>Life Sciences</topic><topic>Linkage Disequilibrium</topic><topic>Models, Genetic</topic><topic>Original</topic><topic>original-article</topic><topic>Plant Genetics and Genomics</topic><topic>Polymorphism, Single Nucleotide</topic><topic>Population structure</topic><topic>Reproducibility of Results</topic><topic>Vitis - 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Academic</collection><collection>Hyper Article en Ligne (HAL)</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Heredity</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Mangin, B</au><au>Siberchicot, A</au><au>Nicolas, S</au><au>Doligez, A</au><au>This, P</au><au>Cierco-Ayrolles, C</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Novel measures of linkage disequilibrium that correct the bias due to population structure and relatedness</atitle><jtitle>Heredity</jtitle><stitle>Heredity</stitle><addtitle>Heredity (Edinb)</addtitle><date>2012-03-01</date><risdate>2012</risdate><volume>108</volume><issue>3</issue><spage>285</spage><epage>291</epage><pages>285-291</pages><issn>0018-067X</issn><eissn>1365-2540</eissn><eissn>0018-067X</eissn><coden>HDTYAT</coden><abstract>Among the several linkage disequilibrium measures known to capture different features of the non-independence between alleles at different loci, the most commonly used for diallelic loci is the
r
2
measure. In the present study, we tackled the problem of the bias of
r
2
estimate, which results from the sample structure and/or the relatedness between genotyped individuals. We derived two novel linkage disequilibrium measures for diallelic loci that are both extensions of the usual
r
2
measure. The first one,
r
S
2
, uses the population structure matrix, which consists of information about the origins of each individual and the admixture proportions of each individual genome. The second one,
r
V
2
, includes the kinship matrix into the calculation. These two corrections can be applied together in order to correct for both biases and are defined either on phased or unphased genotypes.
We proved that these novel measures are linked to the power of association tests under the mixed linear model including structure and kinship corrections. We validated them on simulated data and applied them to real data sets collected on
Vitis vinifera
plants. Our results clearly showed the usefulness of the two corrected
r
2
measures, which actually captured ‘true’ linkage disequilibrium unlike the usual
r
2
measure.</abstract><cop>Cham</cop><pub>Springer International Publishing</pub><pmid>21878986</pmid><doi>10.1038/hdy.2011.73</doi><tpages>7</tpages><orcidid>https://orcid.org/0000-0002-3159-5903</orcidid><orcidid>https://orcid.org/0000-0002-3024-5813</orcidid><orcidid>https://orcid.org/0000-0002-7638-8318</orcidid><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0018-067X |
| ispartof | Heredity, 2012-03, Vol.108 (3), p.285-291 |
| issn | 0018-067X 1365-2540 0018-067X |
| language | eng |
| recordid | cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_3282397 |
| source | PubMed (Medline); Nature Journals Online |
| subjects | Alleles Bias Biomedical and Life Sciences Biomedicine Computer Simulation Cytogenetics Disequilibrium Ecology Evolutionary Biology Gene loci Genetics, Population Genotype Genotypes Human Genetics Human health and pathology Life Sciences Linkage Disequilibrium Models, Genetic Original original-article Plant Genetics and Genomics Polymorphism, Single Nucleotide Population structure Reproducibility of Results Vitis - genetics Vitis vinifera |
| title | Novel measures of linkage disequilibrium that correct the bias due to population structure and relatedness |
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