A new genotype imputation method with tolerance to high missing rate and rare variants
We report a novel algorithm, iBLUP, to impute missing genotypes by simultaneously and comprehensively using identity by descent and linkage disequilibrium information. The simulation studies showed that the algorithm exhibited drastically tolerance to high missing rate, especially for rare variants...
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| Veröffentlicht in: | PloS one 2014-06, Vol.9 (6), p.e101025-e101025 |
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| creator | Yang, Yumei Wang, Qishan Chen, Qiang Liao, Rongrong Zhang, Xiangzhe Yang, Hongjie Zheng, Youmin Zhang, Zhiwu Pan, Yuchun |
| description | We report a novel algorithm, iBLUP, to impute missing genotypes by simultaneously and comprehensively using identity by descent and linkage disequilibrium information. The simulation studies showed that the algorithm exhibited drastically tolerance to high missing rate, especially for rare variants than other common imputation methods, e.g. BEAGLE and fastPHASE. At a missing rate of 70%, the accuracy of BEAGLE and fastPHASE dropped to 0.82 and 0.74 respectively while iBLUP retained an accuracy of 0.95. For minor allele, the accuracy of BEAGLE and fastPHASE decreased to -0.1 and 0.03, while iBLUP still had an accuracy of 0.61.We implemented the algorithm in a publicly available software package also named iBLUP. The application of iBLUP for processing real sequencing data in an outbred pig population was demonstrated. |
| doi_str_mv | 10.1371/journal.pone.0101025 |
| format | Article |
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The simulation studies showed that the algorithm exhibited drastically tolerance to high missing rate, especially for rare variants than other common imputation methods, e.g. BEAGLE and fastPHASE. At a missing rate of 70%, the accuracy of BEAGLE and fastPHASE dropped to 0.82 and 0.74 respectively while iBLUP retained an accuracy of 0.95. For minor allele, the accuracy of BEAGLE and fastPHASE decreased to -0.1 and 0.03, while iBLUP still had an accuracy of 0.61.We implemented the algorithm in a publicly available software package also named iBLUP. The application of iBLUP for processing real sequencing data in an outbred pig population was demonstrated.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0101025</identifier><identifier>PMID: 24972110</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Algorithms ; Analysis ; Animals ; Bioinformatics ; Biology ; Biology and Life Sciences ; Breeding of animals ; Computer simulation ; Data processing ; Gene loci ; Genetics ; Genomes ; Genomics ; Genotype & phenotype ; Genotypes ; Haplotypes ; Hogs ; Linkage disequilibrium ; Methods ; Polymorphism, Genetic ; Population ; Sensitivity and Specificity ; Software ; Soil sciences ; Studies ; Suidae ; Swine</subject><ispartof>PloS one, 2014-06, Vol.9 (6), p.e101025-e101025</ispartof><rights>COPYRIGHT 2014 Public Library of Science</rights><rights>2014 Yang et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2014 Yang et al 2014 Yang et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c692t-c62779faf3d5b63b7c36c2bc742ef19aa1c72025760608fac06cb97f3108085d3</citedby><cites>FETCH-LOGICAL-c692t-c62779faf3d5b63b7c36c2bc742ef19aa1c72025760608fac06cb97f3108085d3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4074155/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4074155/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2095,2914,23846,27903,27904,53770,53772,79347,79348</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/24972110$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Cai, Xiaodong</contributor><creatorcontrib>Yang, Yumei</creatorcontrib><creatorcontrib>Wang, Qishan</creatorcontrib><creatorcontrib>Chen, Qiang</creatorcontrib><creatorcontrib>Liao, Rongrong</creatorcontrib><creatorcontrib>Zhang, Xiangzhe</creatorcontrib><creatorcontrib>Yang, Hongjie</creatorcontrib><creatorcontrib>Zheng, Youmin</creatorcontrib><creatorcontrib>Zhang, Zhiwu</creatorcontrib><creatorcontrib>Pan, Yuchun</creatorcontrib><title>A new genotype imputation method with tolerance to high missing rate and rare variants</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>We report a novel algorithm, iBLUP, to impute missing genotypes by simultaneously and comprehensively using identity by descent and linkage disequilibrium information. The simulation studies showed that the algorithm exhibited drastically tolerance to high missing rate, especially for rare variants than other common imputation methods, e.g. BEAGLE and fastPHASE. At a missing rate of 70%, the accuracy of BEAGLE and fastPHASE dropped to 0.82 and 0.74 respectively while iBLUP retained an accuracy of 0.95. For minor allele, the accuracy of BEAGLE and fastPHASE decreased to -0.1 and 0.03, while iBLUP still had an accuracy of 0.61.We implemented the algorithm in a publicly available software package also named iBLUP. The application of iBLUP for processing real sequencing data in an outbred pig population was demonstrated.</description><subject>Algorithms</subject><subject>Analysis</subject><subject>Animals</subject><subject>Bioinformatics</subject><subject>Biology</subject><subject>Biology and Life Sciences</subject><subject>Breeding of animals</subject><subject>Computer simulation</subject><subject>Data processing</subject><subject>Gene loci</subject><subject>Genetics</subject><subject>Genomes</subject><subject>Genomics</subject><subject>Genotype & phenotype</subject><subject>Genotypes</subject><subject>Haplotypes</subject><subject>Hogs</subject><subject>Linkage disequilibrium</subject><subject>Methods</subject><subject>Polymorphism, Genetic</subject><subject>Population</subject><subject>Sensitivity and Specificity</subject><subject>Software</subject><subject>Soil 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disequilibrium</topic><topic>Methods</topic><topic>Polymorphism, Genetic</topic><topic>Population</topic><topic>Sensitivity and Specificity</topic><topic>Software</topic><topic>Soil sciences</topic><topic>Studies</topic><topic>Suidae</topic><topic>Swine</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Yang, Yumei</creatorcontrib><creatorcontrib>Wang, Qishan</creatorcontrib><creatorcontrib>Chen, Qiang</creatorcontrib><creatorcontrib>Liao, Rongrong</creatorcontrib><creatorcontrib>Zhang, Xiangzhe</creatorcontrib><creatorcontrib>Yang, Hongjie</creatorcontrib><creatorcontrib>Zheng, Youmin</creatorcontrib><creatorcontrib>Zhang, Zhiwu</creatorcontrib><creatorcontrib>Pan, Yuchun</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Gale In Context: 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One</addtitle><date>2014-06-27</date><risdate>2014</risdate><volume>9</volume><issue>6</issue><spage>e101025</spage><epage>e101025</epage><pages>e101025-e101025</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>We report a novel algorithm, iBLUP, to impute missing genotypes by simultaneously and comprehensively using identity by descent and linkage disequilibrium information. The simulation studies showed that the algorithm exhibited drastically tolerance to high missing rate, especially for rare variants than other common imputation methods, e.g. BEAGLE and fastPHASE. At a missing rate of 70%, the accuracy of BEAGLE and fastPHASE dropped to 0.82 and 0.74 respectively while iBLUP retained an accuracy of 0.95. For minor allele, the accuracy of BEAGLE and fastPHASE decreased to -0.1 and 0.03, while iBLUP still had an accuracy of 0.61.We implemented the algorithm in a publicly available software package also named iBLUP. The application of iBLUP for processing real sequencing data in an outbred pig population was demonstrated.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>24972110</pmid><doi>10.1371/journal.pone.0101025</doi><oa>free_for_read</oa></addata></record> |
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| subjects | Algorithms Analysis Animals Bioinformatics Biology Biology and Life Sciences Breeding of animals Computer simulation Data processing Gene loci Genetics Genomes Genomics Genotype & phenotype Genotypes Haplotypes Hogs Linkage disequilibrium Methods Polymorphism, Genetic Population Sensitivity and Specificity Software Soil sciences Studies Suidae Swine |
| title | A new genotype imputation method with tolerance to high missing rate and rare variants |
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