A major use of the 1000 Genomes Project (1000GP) data is genotype imputation in genome-wide association studies (GWAS). Here we develop a method to estimate haplotypes from low-coverage sequencing data that can take advantage of single-nucleotide polymorphism (SNP) microarray genotypes on the same samples. First the SNP array data are phased to build a backbone (or 'scaffold') of haplotypes across each chromosome. We then phase the sequence data 'onto' this haplotype scaffold. This approach can take advantage of relatedness between sequenced and non-sequenced samples to improve accuracy. We use this method to create a new 1000GP haplotype reference set for use by the human genetic community. Using a set of validation genotypes at SNP and bi-allelic indels we show that these haplotypes have lower genotype discordance and improved imputation performance into downstream GWAS samples, especially at low-frequency variants. © 2014 Macmillan Publishers Limited. All rights reserved.

Integrating sequence and array data to create an improved 1000 Genomes Project haplotype reference panel / Delaneau, Olivier; Marchini, Jonathan; Mcveanh, Gil A.; Donnelly, Peter; Lunter, Gerton; Marchini, Jonathan L.; Myers, Simon; Gupta Hinch, Anjali; Iqbal, Zamin; Mathieson, Iain; Rimmer, Andy; Xifara, Dionysia K.; Kerasidou, Angeliki; Churchhouse, Claire; Altshuler, David M.; Gabriel, Stacey B.; Lander, Eric S.; Gupta, Namrata; Daly, Mark J.; Depristo, Mark A.; Banks, Eric; Bhatia, Gaurav; Carneiro, Mauricio O.; Del Angel, Guillermo; Genovese, Giulio; Handsaker, Robert E.; Hartl, Chris; Mccarroll, Steven A.; Nemesh, James C.; Poplin, Ryan E.; Schaffner, Stephen F.; Shakir, Khalid; Sabeti, Pardis C.; Grossman, Sharon R.; Tabrizi, Shervin; Tariyal, Ridhi; Li, Heng; Reich, David; Durbin, Richard M.; Hurles, Matthew E.; Balasubramaniam, Senduran; Burton, John; Danecek, Petr; Keane, Thomas M.; Kolb Kokocinski, Anja; Mccarthy, Shane; Stalker, James; Quail, Michael; Ayub, Qasim; Chen, Yuan; Coffey, Alison J.; Colonna, Vincenza; Huang, Ni; Jostins, Luke; Scally, Aylwyn; Walter, Klaudia; Xue, Yali; Zhang, Yujun; Blackburne, Ben; Lindsay, Sarah J.; Ning, Zemin; Frankish, Adam; Harrow, Jennifer; Chris, Tyler S.; Abecasis, Gonalo R.; Kang, Hyun Min; Anderson, Paul; Blackwell, Tom; Busonero, Fabio; Fuchsberger, Christian; Jun, Goo; Maschio, Andrea; Porcu, Eleonora; Sidore, Carlo; Tan, Adrian; Trost, Mary Kate; Bentley, David R.; Grocock, Russell; Humphray, Sean; James, Terena; Kingsbury, Zoya; Bauer, Markus; Cheetham, R. Keira; Cox, Tony; Eberle, Michael; Murray, Lisa; Shaw, Richard; Chakravarti, Aravinda; Clark, Andrew G.; Keinan, Alon; Rodriguez Flores, Juan L.; De LaVega, Francisco M.; Degenhardt, Jeremiah; Eichler, Evan E.; Flicek, Paul; Clarke, Laura; Leinonen, Rasko; Smith, Richard E.; Zheng Bradley, Xiangqun; Beal, Kathryn; Cunningham, Fiona; Herrero, Javier; Mclaren, William M.; Ritchie, Graham R. S.; Barker, Jonathan; Kelman, Gavin; Kulesha, Eugene; Radhakrishnan, Rajesh; Roa, Asier; Smirnov, Dmitriy; Streeter, Ian; Toneva, Iliana; Gibbs, Richard A.; Dinh, Huyen; Kovar, Christie; Lee, Sandra; Lewis, Lora; Muzny, Donna; Reid, Jeff; Wang, Min; Yu, Fuli; Bainbridge, Matthew; Challis, Danny; Evani, Uday S.; Lu, James; Nagaswamy, Uma; Sabo, Aniko; Wang, Yi; Yu, Jin; Fowler, Gerald; Hale, Walker; Kalra, Divya; Green, Eric D.; Knoppers, Bartha M.; Korbel, Jan O.; Rausch, Tobias; Sttz, Adrian M.; Lee, Charles; Griffin, Lauren; Hsieh, Chih Heng; Mills, Ryan E.; Von Grotthuss, Marcin; Zhang, Chengsheng; Shi, Xinghua; Lehrach, Hans; Sudbrak, Ralf; Amstislavskiy, Vyacheslav S.; Lienhard, Matthias; Mertes, Florian; Sultan, Marc; Timmermann, Bernd; Yaspo, Marie Laure; Herwig, Sudbrak Ralf; Mardis, Elaine R.; Wilson, Richard K.; Fulton, Lucinda; Fulton, Robert; Weinstock, George M.; Chinwalla, Asif; Ding, Li; Dooling, David; Koboldt, Daniel C.; Mclellan, Michael D.; Wallis, John W.; Wendl, Michael C.; Zhang, Qunyuan; Marth, Gabor T.; Garrison, Erik P.; Kural, Deniz; Lee, Wan Ping; Leong, Wen Fung; Ward, Alistair N.; Wu, Jiantao; Zhang, Mengyao; Nickerson, Deborah A.; Alkan, Can; Hormozdiari, Fereydoun; Ko, Arthur; Sudmant, Peter H.; Schmidt, Jeanette P.; Davies, Christopher J.; Gollub, Jeremy; Webster, Teresa; Wong, Brant; Zhan, Yiping; Sherry, Stephen T.; Xiao, Chunlin; Church, Deanna; Ananiev, Victor; Belaia, Zinaida; Beloslyudtsev, Dimitriy; Bouk, Nathan; Chen, Chao; Cohen, Robert; Cook, Charles; Garner, John; Hefferon, Timothy; Kimelman, Mikhail; Liu, Chunlei; Lopez, John; Meric, Peter; Ostapchuk, Yuri; Phan, Lon; Ponomarov, Sergiy; Schneider, Valerie; Shekhtman, Eugene; Sirotkin, Karl; Slotta, Douglas; Zhang, Hua; Wang, Jun; Fang, Xiaodong; Guo, Xiaosen; Jian, Min; Jiang, Hui; Jin, Xin; Li, Guoqing; Li, Jingxiang; Li, Yingrui; Liu, Xiao; Lu, Yao; Ma, Xuedi; Tai, Shuaishuai; Tang, Meifang; Wang, Bo; Wang, Guangbiao; Wu, Honglong; Wu, Renhua; Yin, Ye; Zhang, Wenwei; Zhao, Jiao; Zhao, Meiru; Zheng, Xiaole; Lachlan, Hans; Fang, Lin; Li, Qibin; Li, Zhenyu; Lin, Haoxiang; Liu, Binghang; Luo, Ruibang; Shao, Haojing; Wang, Bingqiang; Xie, Yinlong; Ye, Chen; Yu, Chang; Zheng, Hancheng; Zhu, Hongmei; Cai, Hongyu; Cao, Hongzhi; Su, Yeyang; Tian, Zhongming; Yang, Huanming; Yang, Ling; Zhu, Jiayong; Cai, Zhiming; Wang, Jian; Albrecht, Marcus W.; Borodina, Tatiana A.; Auton, Adam; Yoon, Seungtai C.; Lihm, Jayon; Makarov, Vladimir; Jin, Hanjun; Kim, Wook; Kim, Ki Cheol; Gottipati, Srikanth; Jones, Danielle; Cooper, David N.; Ball, Edward V.; Stenson, Peter D.; Barnes, Bret; Kahn, Scott; Ye, Kai; Batzer, Mark A.; Konkel, Miriam K.; Walker, Jerilyn A.; Macarthur, Daniel G.; Lek, Monkol; Shriver, Mark D.; Bustamante, Carlos D.; Gravel, Simon; Kenny, Eimear E.; Kidd, Jeffrey M.; Lacroute, Phil; Maples, Brian K.; Moreno Estrada, Andres; Zakharia, Fouad; Henn, Brenna; Sandoval, Karla; Byrnes, Jake K.; Halperin, Eran; Baran, Yael; Craig, David W.; Christoforides, Alexis; Izatt, Tyler; Kurdoglu, Ahmet A.; Sinari, Shripad A.; Homer, Nils; Squire, Kevin; Sebat, Jonathan; Bafna, Vineet; Ye, Kenny; Burchard, Esteban G.; Hernandez, Ryan D.; Gignoux, Christopher R.; Haussler, David; Katzman, Sol J.; Kent, W. James; Howie, Bryan; Ruiz Linares, Andres; Dermitzakis, Emmanouil T.; Lappalainen, Tuuli; Devine, Scott E.; Liu, Xinyue; Maroo, Ankit; Tallon, Luke J.; Rosenfeld, Jeffrey A.; Michelson, Leslie P.; Angius, Andrea; Cucca, Francesco; Sanna, Serena; Bigham, Abigail; Jones, Chris; Reinier, Fred; Li, Yun; Lyons, Robert; Schlessinger, David; Awadalla, Philip; Hodgkinson, Alan; Oleksyk, Taras K.; Martinez Cruzado, Juan C.; Fu, Yunxin; Liu, Xiaoming; Xiong, Momiao; Jorde, Lynn; Witherspoon, David; Xing, Jinchuan; Browning, Brian L.; Hajirasouliha, Iman; Chen, Ken; Albers, Cornelis A.; Gerstein, Mark B.; Abyzov, Alexej; Chen, Jieming; Fu, Yao; Habegger, Lukas; Harmanci, Arif O.; Mu, Xinmeng Jasmine; Sisu, Cristina; Balasubramanian, Suganthi; Jin, Mike; Khurana, Ekta; Clarke, Declan; Michaelson, Jacob J.; Osullivan, Chris; Barnes, Kathleen C.; Gharani, Neda; Toji, Lorraine H.; Gerry, Norman; Kaye, Jane S.; Kent, Alastair; Mathias, Rasika; Ossorio, Pilar N.; Parker, Michael; Rotimi, Charles N.; Royal, Charmaine D.; Tishkoff, Sarah; Via, Marc; Bodmer, Walter; Bedoya, Gabriel; Yang, Gao; You, Chu Jia; Garcia Montero, Andres; Orfao, Alberto; Dutil, Julie; Brooks, Lisa D.; Felsenfeld, Adam L.; Mcewen, Jean E.; Clemm, Nicholas C.; Guyer, Mark S.; Peterson, Jane L.; Duncanson, Audrey; Dunn, Michael; Peltonen, Leena. - In: NATURE COMMUNICATIONS. - ISSN 2041-1723. - 5:(2014), p. 3934. [10.1038/ncomms4934]

Integrating sequence and array data to create an improved 1000 Genomes Project haplotype reference panel

CUCCA, Francesco;
2014

Abstract

A major use of the 1000 Genomes Project (1000GP) data is genotype imputation in genome-wide association studies (GWAS). Here we develop a method to estimate haplotypes from low-coverage sequencing data that can take advantage of single-nucleotide polymorphism (SNP) microarray genotypes on the same samples. First the SNP array data are phased to build a backbone (or 'scaffold') of haplotypes across each chromosome. We then phase the sequence data 'onto' this haplotype scaffold. This approach can take advantage of relatedness between sequenced and non-sequenced samples to improve accuracy. We use this method to create a new 1000GP haplotype reference set for use by the human genetic community. Using a set of validation genotypes at SNP and bi-allelic indels we show that these haplotypes have lower genotype discordance and improved imputation performance into downstream GWAS samples, especially at low-frequency variants. © 2014 Macmillan Publishers Limited. All rights reserved.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11388/178426
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