vavilovВавиловский журнал генетики и селекцииVavilov Journal of Genetics and Breeding2500-3259Institute of Cytology and Genetics of Siberian Branch of the RAS10.18699/vjgb-24-70vavilov-4292Research ArticleГЕНЕТИКА ЧЕЛОВЕКАHUMAN GENETICSИмпутация генотипов в геномных исследованиях человекаGenotype imputation in human genomic studieshttps://orcid.org/0009-0008-4835-3354БердниковаА. А.BerdnikovaA. A.

 Новосибирск

Novosibirsk

https://orcid.org/0000-0002-2726-0350ЗоркольцеваИ. В.ZorkoltsevaI. V.

 Новосибирск

Novosibirsk

https://orcid.org/0000-0002-4931-6052ЦепиловЯ. А.TsepilovY. A.

 Новосибирск

Novosibirsk

https://orcid.org/0000-0002-2484-553XЕлгаеваЕ. Е.ElgaevaE. E.

 Новосибирск

Novosibirsk

Федеральный исследовательский центр Институт цитологии и генетики Сибирского отделения Российской академии наук; Новосибирский национальный исследовательский государственный университетРоссияInstitute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences; Novosibirsk State University,Russian FederationФедеральный исследовательский центр Институт цитологии и генетики Сибирского отделения Российской академии наукРоссияInstitute of Cytology and Genetics of the Siberian Branch of the Russian Academy of SciencesRussian FederationФедеральный исследовательский центр Институт цитологии и генетики Сибирского отделения Российской академии наукРоссияInstitute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences; Novosibirsk State University,Russian FederationФедеральный исследовательский центр Институт цитологии и генетики Сибирского отделения Российской академии наук; Новосибирский национальный исследовательский государственный университетРоссияInstitute of Cytology and Genetics of the Siberian Branch of the Russian Academy of SciencesRussian Federation202409102024286628639Copyright © Бердникова А.А., Зоркольцева И.В., Цепилов Я.А., Елгаева Е.Е., 20242024Бердникова А.А., Зоркольцева И.В., Цепилов Я.А., Елгаева Е.Е.Berdnikova A.A., Zorkoltseva I.V., Tsepilov Y.A., Elgaeva E.E.This work is licensed under a Creative Commons Attribution 4.0 License.https://vavilov.elpub.ru/jour/article/view/4292

Импутация – это метод, позволяющий восстанавливать недостающую информацию о генетических вариантах, которые не удалось генотипировать напрямую с помощью ДНК-микрочипов или секвенирования с низким покрытием. Импутация играет важнейшую роль в полногеномном анализе ассоциаций (genome wide associations study, GWAS). Она приводит к существенному увеличению количества изучаемых вариантов, что повышает разрешающую способность метода и увеличивает сопоставимость данных, полученных в разных когортах и/или с помощью разных технологий, что важно при проведении метаанализов. При ее выполнении информацию о генотипах в исследуемой выборке, у которой известна только часть генетических вариантов, дополняют за счет эталонной (референсной) выборки, имеющей более полные данные о генотипах (чаще всего это результаты полногеномного секвенирования). Импутация стала неотъемлемой частью геномных исследований человека благодаря преимуществам, которые она дает, а также увеличению доступности инструментов для импутации и данных референсных выборок. Обзор посвящен импутации в геномных исследованиях человека. В первом разделе приводятся описание технологий получения информации о генотипах человека и характеристика получаемых типов данных. Во втором разделе представлена методология импутации, перечисляются этапы ее проведения и соответствующие программы, дается описание наиболее популярных референсных панелей и способов оценки качества импутации. В заключении представлены примеры использования импутации в геномных исследованиях выборок из России. Настоящий обзор показывает важность проведения импутации, дает информацию о том, как ее выполнять, и систематизирует результаты ее применения на примере российских выборок. 

Imputation is a method that supplies missing information about genetic variants that could not be directly genotyped with DNA microarrays or low-coverage sequencing. Imputation plays a critical role in genome-wide association studies (GWAS). It leads to a significant increase in the number of studied variants, which improves the resolution of the method and enhances the comparability of data obtained in different cohorts and/or by using different technologies, which is important for conducting meta-analyses. When performing imputation, genotype information from the study sample, in which only part of the genetic variants are known, is complemented using the standard (reference) sample, which has more complete genotype data (most often the results of whole-genome sequencing). Imputation has become an integral part of human genomic research due to the benefits it provides and the increasing availability of imputation tools and reference sample data. This review focuses on imputation in human genomic research. The first section of the review provides a description of technologies for obtaining information about human genotypes and characteristics of these types of data. The second section describes the imputation methodology, lists the stages of its implementation and the corresponding programs, provides a description of the most popular reference panels and methods for assessing the quality of imputation. The review concludes with examples of the use of imputation in genomic studies of samples from Russia. This review shows the importance of imputation, provides information on how to carry it out, and systematizes the results of its application using Russian samples. 

импутациягенотипированиесеквенированиеполногеномный анализ ассоциацийчеловекДНК-микрочипimputationgenotypingsequencinggenome-wide association studyhumanDNA-microarrayReferencesAbraham G., Qiu Y., Inouye M. FlashPCA2: principal component analysis of Biobank-scale genotype datasets. Bioinformatics. 2017; 33(17):2776-2778. DOI 10.1093/bioinformatics/btx299Abraham G., Qiu Y., Inouye M. FlashPCA2: principal component analysis of Biobank-scale genotype datasets. Bioinformatics. 2017; 33(17):2776-2778. DOI 10.1093/bioinformatics/btx299Ali A.T., Liebert A., Lau W., Maniatis N., Swallow D.M. The hazards of genotype imputation in chromosomal regions under selection: A case study using the lactase gene region. Ann. Hum. Genet. 2022; 86(1):24-33. DOI 10.1111/ahg.12444Ali A.T., Liebert A., Lau W., Maniatis N., Swallow D.M. The hazards of genotype imputation in chromosomal regions under selection: A case study using the lactase gene region. Ann. Hum. Genet. 2022; 86(1):24-33. DOI 10.1111/ahg.12444Anderson C.A., Pettersson F.H., Clarke G.M., Cardon L.R., Morris A.P., Zondervan K.T. Data quality control in genetic case-control association studies. Nat. Protoc. 2010;5(9):1564-1573. DOI 10.1038/nprot.2010.116Anderson C.A., Pettersson F.H., Clarke G.M., Cardon L.R., Morris A.P., Zondervan K.T. Data quality control in genetic case-control association studies. Nat. Protoc. 2010;5(9):1564-1573. DOI 10.1038/nprot.2010.116Auton A., Abecasis G.R., Altshuler D.M., Durbin R.M., Abecasis G.R., Bentley D.R., … Min Kang H., Korbel J.O., Marchini J.L., McCarthy S., McVean G.A., Abecasis G.R. A global reference for human genetic variation. Nature. 2015;526(7571):68-74. DOI 10.1038/nature15393Auton A., Abecasis G.R., Altshuler D.M., Durbin R.M., Abecasis G.R., Bentley D.R., … Min Kang H., Korbel J.O., Marchini J.L., McCarthy S., McVean G.A., Abecasis G.R. A global reference for human genetic variation. Nature. 2015;526(7571):68-74. DOI 10.1038/nature15393Barton A.R., Sherman M.A., Mukamel R.E., Loh P.-R. Whole-exome imputation within UK Biobank powers rare coding variant association and fine-mapping analyses. Nat. Genet. 2021;53(8):1260-1269. DOI 10.1038/s41588-021-00892-1Barton A.R., Sherman M.A., Mukamel R.E., Loh P.-R. Whole-exome imputation within UK Biobank powers rare coding variant association and fine-mapping analyses. Nat. Genet. 2021;53(8):1260-1269. DOI 10.1038/s41588-021-00892-1Bhattacharyya A. On a measure of divergence between two multinomial populations. Sankhyā: Ind. J. Stat. 1946;7(4):401-406Bhattacharyya A. On a measure of divergence between two multinomial populations. Sankhyā: Ind. J. Stat. 1946;7(4):401-406Bourke P.M., Voorrips R.E., Visser R.G.F., Maliepaard C. Tools for genetic studies in experimental populations of polyploids. Front. Plant. Sci. 2018;9:513. DOI 10.3389/fpls.2018.00513Bourke P.M., Voorrips R.E., Visser R.G.F., Maliepaard C. Tools for genetic studies in experimental populations of polyploids. Front. Plant. Sci. 2018;9:513. DOI 10.3389/fpls.2018.00513Brown A., Ampratwum P.O., Ray S.D. Microarray analysis. In: Encyclopedia of Toxicology. 4 ed. 2024;6:385-392. DOI 10.1016/B978-0-12-824315-2.00210-4Brown A., Ampratwum P.O., Ray S.D. Microarray analysis. In: Encyclopedia of Toxicology. 4 ed. 2024;6:385-392. DOI 10.1016/B978-0-12-824315-2.00210-4Browning B.L., Zhou Y., Browning S.R. A One-penny imputed genome from next-generation reference panels. Am. J. Hum. Genet. 2018;103(3):338-348. DOI 10.1016/j.ajhg.2018.07.015Browning B.L., Zhou Y., Browning S.R. A One-penny imputed genome from next-generation reference panels. Am. J. Hum. Genet. 2018;103(3):338-348. DOI 10.1016/j.ajhg.2018.07.015Browning B.L., Tian X., Zhou Y., Browning S.R. Fast two-stage phasing of large-scale sequence data. Am. J. Hum. Genet. 2021;108(10): 1880-1890. DOI 10.1016/j.ajhg.2021.08.005Browning B.L., Tian X., Zhou Y., Browning S.R. Fast two-stage phasing of large-scale sequence data. Am. J. Hum. Genet. 2021;108(10): 1880-1890. DOI 10.1016/j.ajhg.2021.08.005Browning S.R., Browning B.L. Haplotype phasing: existing methods and new developments. Nat. Rev. Genet. 2011;12(10):703-714. DOI 10.1038/nrg3054Browning S.R., Browning B.L. Haplotype phasing: existing methods and new developments. Nat. Rev. Genet. 2011;12(10):703-714. DOI 10.1038/nrg3054Cann H.M., de Toma C., Cazes L., Legrand M.F., Morel V., Piouffre L., Bodmer J., … Zhu S., Weber J.L., Greely H.T., Feldman M.W., Thomas G., Dausset J., Cavalli-Sforza L.L. A human genome diversity cell line panel. Science. 2002;296(5566):261-262. DOI 10.1126/science.296.5566.261bCann H.M., de Toma C., Cazes L., Legrand M.F., Morel V., Piouffre L., Bodmer J., … Zhu S., Weber J.L., Greely H.T., Feldman M.W., Thomas G., Dausset J., Cavalli-Sforza L.L. A human genome diversity cell line panel. Science. 2002;296(5566):261-262. DOI 10.1126/science.296.5566.261bChang C.C., Chow C.C., Tellier L.C., Vattikuti S., Purcell S.M., Lee J.J. Second-generation PLINK: rising to the challenge of larger and richer datasets. GigaScience. 2015;4(1):7. DOI 10.1186/s13742-015-0047-8Chang C.C., Chow C.C., Tellier L.C., Vattikuti S., Purcell S.M., Lee J.J. Second-generation PLINK: rising to the challenge of larger and richer datasets. GigaScience. 2015;4(1):7. DOI 10.1186/s13742-015-0047-8Chat V., Ferguson R., Morales L., Kirchhoff T. Ultra low-coverage whole-genome sequencing as an alternative to genotyping arrays in genome-wide association studies. Front. Genet. 2022;12:790445. DOI 10.3389/fgene.2021.790445Chat V., Ferguson R., Morales L., Kirchhoff T. Ultra low-coverage whole-genome sequencing as an alternative to genotyping arrays in genome-wide association studies. Front. Genet. 2022;12:790445. DOI 10.3389/fgene.2021.790445Check Hayden E. Genome sequencing: the third generation. Nature. 2009;457(7231):768-769. DOI 10.1038/news.2009.86Check Hayden E. Genome sequencing: the third generation. Nature. 2009;457(7231):768-769. DOI 10.1038/news.2009.86Choi S.W., Mak T.S.-H., O’Reilly P.F. Tutorial: a guide to performing polygenic risk score analyses. Nat. Protoc. 2020;15(9):2759-2772. DOI 10.1038/s41596-020-0353-1Choi S.W., Mak T.S.-H., O’Reilly P.F. Tutorial: a guide to performing polygenic risk score analyses. Nat. Protoc. 2020;15(9):2759-2772. DOI 10.1038/s41596-020-0353-1Chundru V.K., Marioni R.E., Prendergast J.G.D., Vallerga C.L., Lin T., Beveridge A.J., Gratten J., Hume D.A., Deary I.J., Wray N.R., Visscher P.M., McRae A.F. Examining the impact of imputation errors on fine-mapping using DNA methylation QTL as a model trait. Genetics. 2019;212(3):577-586. DOI 10.1534/genetics.118. 301861Chundru V.K., Marioni R.E., Prendergast J.G.D., Vallerga C.L., Lin T., Beveridge A.J., Gratten J., Hume D.A., Deary I.J., Wray N.R., Visscher P.M., McRae A.F. Examining the impact of imputation errors on fine-mapping using DNA methylation QTL as a model trait. Genetics. 2019;212(3):577-586. DOI 10.1534/genetics.118. 301861Clark A.G. Inference of haplotypes from PCR-amplified samples of diploid populations. Mol. Biol. Evol. 1990;7(2):111-122. DOI 10.1093/oxfordjournals.molbev.a040591Clark A.G. Inference of haplotypes from PCR-amplified samples of diploid populations. Mol. Biol. Evol. 1990;7(2):111-122. DOI 10.1093/oxfordjournals.molbev.a040591Collister J.A., Liu X., Clifton L. Calculating polygenic risk scores (PRS) in UK biobank: A practical guide for epidemiologists. Front. Genet. 2022;13:818574. DOI 10.3389/fgene.2022.818574Collister J.A., Liu X., Clifton L. Calculating polygenic risk scores (PRS) in UK biobank: A practical guide for epidemiologists. Front. Genet. 2022;13:818574. DOI 10.3389/fgene.2022.818574Connell C., Fung S., Heiner C., Bridgham J., Chakerian V., Heron E., Jones B., Menchen S., Mordan W., Raff M., Recknor M., Smith L.M., Springer J., Woo S., Hunkapiller M. Automated DNA-sequence analysis. Biotechniques. 1987;5:342-348Connell C., Fung S., Heiner C., Bridgham J., Chakerian V., Heron E., Jones B., Menchen S., Mordan W., Raff M., Recknor M., Smith L.M., Springer J., Woo S., Hunkapiller M. Automated DNA-sequence analysis. Biotechniques. 1987;5:342-348Das S., Forer L., Schönherr S., Sidore C., Locke A.E., Kwong A., Vrieze S.I., Chew E.Y., Levy S., McGue M., Schlessinger D., Stambolian D., Loh P.-R., Iacono W.G., Swaroop A., Scott L.J., Cucca F., Kronenberg F., Boehnke M., Abecasis G.R., Fuchsberger C. Nextgeneration genotype imputation service and methods. Nat. Genet. 2016;48(10):1284-1287. DOI 10.1038/ng.3656Das S., Forer L., Schönherr S., Sidore C., Locke A.E., Kwong A., Vrieze S.I., Chew E.Y., Levy S., McGue M., Schlessinger D., Stambolian D., Loh P.-R., Iacono W.G., Swaroop A., Scott L.J., Cucca F., Kronenberg F., Boehnke M., Abecasis G.R., Fuchsberger C. Nextgeneration genotype imputation service and methods. Nat. Genet. 2016;48(10):1284-1287. DOI 10.1038/ng.3656De Marino A., Mahmoud A.A., Bose M., Bircan K.O., Terpolovsky A., Bamunusinghe V., Bohn S., Khan U., Novković B., Yazdi P.G. A comparative analysis of current phasing and imputation software. PLoS One. 2022;17(10):e0260177. DOI 10.1371/journal.pone.0260177De Marino A., Mahmoud A.A., Bose M., Bircan K.O., Terpolovsky A., Bamunusinghe V., Bohn S., Khan U., Novković B., Yazdi P.G. A comparative analysis of current phasing and imputation software. PLoS One. 2022;17(10):e0260177. DOI 10.1371/journal.pone.0260177Deamer D., Akeson M., Branton D. Three decades of nanopore sequencing. Nat. Biotechnol. 2016;34(5):518-524. DOI 10.1038/nbt.3423Deamer D., Akeson M., Branton D. Three decades of nanopore sequencing. Nat. Biotechnol. 2016;34(5):518-524. DOI 10.1038/nbt.3423Delaneau O., Marchini J., Zagury J.-F. A linear complexity phasing method for thousands of genomes. Nat. Methods. 2012;9(2):179- 181. DOI 10.1038/nmeth.1785Delaneau O., Marchini J., Zagury J.-F. A linear complexity phasing method for thousands of genomes. Nat. Methods. 2012;9(2):179- 181. DOI 10.1038/nmeth.1785Dempster A.P., Laird N.M., Rubin D.B. Maximum likelihood from incomplete data via the EM algorithm. J. Royal Statist. Society. 1977;39(1):1-38. DOI 10.1111/j.2517-6161.1977.tb01600.xDempster A.P., Laird N.M., Rubin D.B. Maximum likelihood from incomplete data via the EM algorithm. J. Royal Statist. Society. 1977;39(1):1-38. DOI 10.1111/j.2517-6161.1977.tb01600.xDePristo M.A., Banks E., Poplin R., Garimella K.V., Maguire J.R., Hartl C., Philippakis A.A., del Angel G., Rivas M.A., Hanna M., McKenna A., Fennell T.J., Kernytsky A.M., Sivachenko A.Y., Cibulskis K., Gabriel S.B., Altshuler D., Daly M.J. A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat. Genet. 2011;43(5):491-498. DOI 10.1038/ng.806DePristo M.A., Banks E., Poplin R., Garimella K.V., Maguire J.R., Hartl C., Philippakis A.A., del Angel G., Rivas M.A., Hanna M., McKenna A., Fennell T.J., Kernytsky A.M., Sivachenko A.Y., Cibulskis K., Gabriel S.B., Altshuler D., Daly M.J. A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat. Genet. 2011;43(5):491-498. DOI 10.1038/ng.806Drmanac R., Sparks A.B., Callow M.J., Halpern A.L., Burns N.L., Kermani B.G., Carnevali P., … Drmanac S., Oliphant A.R., Banyai W.C., Martin B., Ballinger D.G., Church G.M., Reid C.A. Human genome sequencing using unchained base reads on selfassembling DNA nanoarrays. Science. 2010;327(5961):78-81. DOI 10.1126/science.1181498Drmanac R., Sparks A.B., Callow M.J., Halpern A.L., Burns N.L., Kermani B.G., Carnevali P., … Drmanac S., Oliphant A.R., Banyai W.C., Martin B., Ballinger D.G., Church G.M., Reid C.A. Human genome sequencing using unchained base reads on selfassembling DNA nanoarrays. Science. 2010;327(5961):78-81. DOI 10.1126/science.1181498Fan J.B., Oliphant A., Shen R., Kermani B.G., Garcia F., Gunderson K.L., Hansen M., … Kruglyak S., Bentley D., Haas J., Rigault P., Zhou L., Stuelpnagel J., Chee M.S. Highly parallel SNP genotyping. Cold Spring Harb. Symp. Quant. Biol. 2003;68:69-78. DOI 10.1101/sqb.2003.68.69Fan J.B., Oliphant A., Shen R., Kermani B.G., Garcia F., Gunderson K.L., Hansen M., … Kruglyak S., Bentley D., Haas J., Rigault P., Zhou L., Stuelpnagel J., Chee M.S. Highly parallel SNP genotyping. Cold Spring Harb. Symp. Quant. Biol. 2003;68:69-78. DOI 10.1101/sqb.2003.68.69Fatumo S., Mugisha J., Soremekun O.S., Kalungi A., Mayanja R., Kintu C., Makanga R., Kakande A., Abaasa A., Asiki G., Kalyesubula R., Newton R., Nyirenda M., Sandhu M.S., Kaleebu P. Uganda genome resource: A rich research database for genomic studies of communicable and non-communicable diseases in Africa. Cell Genom. 2022;2(11):100209. DOI 10.1016/j.xgen.2022.100209Fatumo S., Mugisha J., Soremekun O.S., Kalungi A., Mayanja R., Kintu C., Makanga R., Kakande A., Abaasa A., Asiki G., Kalyesubula R., Newton R., Nyirenda M., Sandhu M.S., Kaleebu P. Uganda genome resource: A rich research database for genomic studies of communicable and non-communicable diseases in Africa. Cell Genom. 2022;2(11):100209. DOI 10.1016/j.xgen.2022.100209Feng Z., Peng F., Xie F., Liu Y., Zhang H., Ma J., Xing J., Guo X. Comparison of capture-based mtDNA sequencing performance between MGI and illumina sequencing platforms in various sample types. BMC Genomics. 2024;25(1):41. DOI 10.1186/s12864-023-09938-6Feng Z., Peng F., Xie F., Liu Y., Zhang H., Ma J., Xing J., Guo X. Comparison of capture-based mtDNA sequencing performance between MGI and illumina sequencing platforms in various sample types. BMC Genomics. 2024;25(1):41. DOI 10.1186/s12864-023-09938-6Govindarajan R., Duraiyan J., Kaliyappan K., Palanisamy M. Microarray and its applications. J. Pharm. Bioallied Sci. 2012;4(6):310. DOI 10.4103/0975-7406.100283Govindarajan R., Duraiyan J., Kaliyappan K., Palanisamy M. Microarray and its applications. J. Pharm. Bioallied Sci. 2012;4(6):310. DOI 10.4103/0975-7406.100283Gresham D., Dunham M.J., Botstein D. Comparing whole genomes using DNA microarrays. Nat. Rev. Genet. 2008;9(4):291-302. DOI 10.1038/nrg2335Gresham D., Dunham M.J., Botstein D. Comparing whole genomes using DNA microarrays. Nat. Rev. Genet. 2008;9(4):291-302. DOI 10.1038/nrg2335Guo Y., He J., Zhao S., Wu H., Zhong X., Sheng Q., Samuels D.C., Shyr Y., Long J. Illumina human exome genotyping array clustering and quality control. Nat. Protoc. 2014;9(11):2643-2662. DOI 10.1038/nprot.2014.174Guo Y., He J., Zhao S., Wu H., Zhong X., Sheng Q., Samuels D.C., Shyr Y., Long J. Illumina human exome genotyping array clustering and quality control. Nat. Protoc. 2014;9(11):2643-2662. DOI 10.1038/nprot.2014.174Hayat M.A. DNA microarrays technology. In: Handbook of Immunohistochemistry and in situ Hybridization of Human Carcinomas. 2002;49-55. DOI 10.1016/S1874-5784(04)80015-1Hayat M.A. DNA microarrays technology. In: Handbook of Immunohistochemistry and in situ Hybridization of Human Carcinomas. 2002;49-55. DOI 10.1016/S1874-5784(04)80015-1Huang G.-H., Tseng Y.-C. Genotype imputation accuracy with different reference panels in admixed populations. BMC Proc. 2014;8(S1): S64. DOI 10.1186/1753-6561-8-S1-S64Huang G.-H., Tseng Y.-C. Genotype imputation accuracy with different reference panels in admixed populations. BMC Proc. 2014;8(S1): S64. DOI 10.1186/1753-6561-8-S1-S64Jeon S.A., Park J.L., Park S.-J., Kim J.H., Goh S.-H., Han J.-Y., Kim S.-Y. Comparison between MGI and illumina sequencing platforms for whole genome sequencing. Genes Genom. 2021;43(7): 713-724. DOI 10.1007/s13258-021-01096-xJeon S.A., Park J.L., Park S.-J., Kim J.H., Goh S.-H., Han J.-Y., Kim S.-Y. Comparison between MGI and illumina sequencing platforms for whole genome sequencing. Genes Genom. 2021;43(7): 713-724. DOI 10.1007/s13258-021-01096-xKolosov N., Rezapova V., Rotar O., Loboda A., Freylikhman O., Melnik O., Sergushichev A., Stevens C., Voortman T., Kostareva A., Konradi A., Daly M.J., Artomov M. Genotype imputation and polygenic score estimation in northwestern Russian population. PLoS One. 2022;17(6):e0269434. DOI 10.1371/journal.pone.Kolosov N., Rezapova V., Rotar O., Loboda A., Freylikhman O., Melnik O., Sergushichev A., Stevens C., Voortman T., Kostareva A., Konradi A., Daly M.J., Artomov M. Genotype imputation and polygenic score estimation in northwestern Russian population. PLoS One. 2022;17(6):e0269434. DOI 10.1371/journal.pone.0269434 Korostin D., Kulemin N., Naumov V., Belova V., Kwon D., Gorbachev A. Comparative analysis of novel MGISEQ-2000 sequencing platform vs Illumina HiSeq 2500 for whole-genome sequencing. PLoS One. 2020;15(3):e0230301. DOI 10.1371/journal.pone.02303010269434 Korostin D., Kulemin N., Naumov V., Belova V., Kwon D., Gorbachev A. Comparative analysis of novel MGISEQ-2000 sequencing platform vs Illumina HiSeq 2500 for whole-genome sequencing. PLoS One. 2020;15(3):e0230301. DOI 10.1371/journal.pone.0230301Kurg A., Tõnisson N., Georgiou I., Shumaker J., Tollett J., Metspalu A. Arrayed primer extension: solid-phase four-color DNA resequencing and mutation detection technology. Genet. Test. 2000;4(1):1-7. DOI 10.1089/109065700316408Kurg A., Tõnisson N., Georgiou I., Shumaker J., Tollett J., Metspalu A. Arrayed primer extension: solid-phase four-color DNA resequencing and mutation detection technology. Genet. Test. 2000;4(1):1-7. DOI 10.1089/109065700316408Lam M., Awasthi S., Watson H.J., Goldstein J., Panagiotaropoulou G., Trubetskoy V., Karlsson R., Frei O., Fan C.-C., De Witte W., Mota N.R., Mullins N., Brügger K., Lee S.H., Wray N.R., Skarabis N., Huang H., Neale B., Daly M.J., Mattheisen M., Walters R., Ripke S. RICOPILI: rapid imputation for COnsortias PIpeLIne. Bioinformatics. 2020;36(3):930-933. DOI 10.1093/bioinformatics/btz633Lam M., Awasthi S., Watson H.J., Goldstein J., Panagiotaropoulou G., Trubetskoy V., Karlsson R., Frei O., Fan C.-C., De Witte W., Mota N.R., Mullins N., Brügger K., Lee S.H., Wray N.R., Skarabis N., Huang H., Neale B., Daly M.J., Mattheisen M., Walters R., Ripke S. RICOPILI: rapid imputation for COnsortias PIpeLIne. Bioinformatics. 2020;36(3):930-933. DOI 10.1093/bioinformatics/btz633Lamy P., Andersen C.L., Wikman F.P., Wiuf C. Genotyping and annotation of Affymetrix SNP arrays. Nucleic Acids Res. 2006;34(14):e100. DOI 10.1093/nar/gkl475Lamy P., Andersen C.L., Wikman F.P., Wiuf C. Genotyping and annotation of Affymetrix SNP arrays. Nucleic Acids Res. 2006;34(14):e100. DOI 10.1093/nar/gkl475Lau W., Ali A., Maude H., Andrew T., Swallow D.M., Maniatis N. The hazards of genotype imputation when mapping disease susceptibility variants. Genome Biol. 2024;25(1):7. DOI 10.1186/s13059-023-03140-3Lau W., Ali A., Maude H., Andrew T., Swallow D.M., Maniatis N. The hazards of genotype imputation when mapping disease susceptibility variants. Genome Biol. 2024;25(1):7. DOI 10.1186/s13059-023-03140-3Li L., Huang P., Sun X., Wang S., Xu M., Liu S., Feng Z., Zhang Q., Wang X., Zheng X., Dai M., Bi Y., Ning G., Cao Y., Wang W. The ChinaMAP reference panel for the accurate genotype imputation in Chinese populations. Cell Res. 2021;31(12):1308-1310. DOI 10.1038/s41422-021-00564-zLi L., Huang P., Sun X., Wang S., Xu M., Liu S., Feng Z., Zhang Q., Wang X., Zheng X., Dai M., Bi Y., Ning G., Cao Y., Wang W. The ChinaMAP reference panel for the accurate genotype imputation in Chinese populations. Cell Res. 2021;31(12):1308-1310. DOI 10.1038/s41422-021-00564-zLi N., Stephens M. Modeling linkage disequilibrium and identifying recombination hotspots using single-nucleotide polymorphism data. Genetics. 2003;165(4):2213-2233. DOI 10.1093/genetics/165.4.2213Li N., Stephens M. Modeling linkage disequilibrium and identifying recombination hotspots using single-nucleotide polymorphism data. Genetics. 2003;165(4):2213-2233. DOI 10.1093/genetics/165.4.2213Li Y., Willer C., Sanna S., Abecasis G. Genotype imputation. Annu. Rev. Genomics Hum. Genet. 2009;10(1):387-406. DOI 10.1146/annurev.genom.9.081307.164242Li Y., Willer C., Sanna S., Abecasis G. Genotype imputation. Annu. Rev. Genomics Hum. Genet. 2009;10(1):387-406. DOI 10.1146/annurev.genom.9.081307.164242Lin P., Hartz S.M., Zhang Z., Saccone S.F., Wang J., Tischfield J.A., Edenberg H.J., Kramer J.R., Goate A.M., Bierut L.J., Rice J.P. A new statistic to evaluate imputation reliability. PLoS One. 2010; 5(3):e9697. DOI 10.1371/journal.pone.0009697Lin P., Hartz S.M., Zhang Z., Saccone S.F., Wang J., Tischfield J.A., Edenberg H.J., Kramer J.R., Goate A.M., Bierut L.J., Rice J.P. A new statistic to evaluate imputation reliability. PLoS One. 2010; 5(3):e9697. DOI 10.1371/journal.pone.0009697Loh P.-R., Danecek P., Palamara P.F., Fuchsberger C., Reshef Y.A., Finucane H.K., Schoenherr S., Forer L., McCarthy S., Abecasis G.R., Durbin R., L Price A. Reference-based phasing using the haplotype reference consortium panel. Nat. Genet. 2016;48(11):1443-1448. DOI 10.1038/ng.3679Loh P.-R., Danecek P., Palamara P.F., Fuchsberger C., Reshef Y.A., Finucane H.K., Schoenherr S., Forer L., McCarthy S., Abecasis G.R., Durbin R., L Price A. Reference-based phasing using the haplotype reference consortium panel. Nat. Genet. 2016;48(11):1443-1448. DOI 10.1038/ng.3679Marchini J., Howie B. Genotype imputation for genome-wide association studies. Nat. Rev. Genet. 2010;11(7):499-511. DOI 10.1038/nrg2796Marchini J., Howie B. Genotype imputation for genome-wide association studies. Nat. Rev. Genet. 2010;11(7):499-511. DOI 10.1038/nrg2796Marees A.T., de Kluiver H., Stringer S., Vorspan F., Curis E., Marie Claire C., Derks E.M. A tutorial on conducting genome wide association studies: Quality control and statistical analysis. Int. J. Methods Psychiatr. Res. 2018;27(2). DOI 10.1002/mpr.1608Marees A.T., de Kluiver H., Stringer S., Vorspan F., Curis E., Marie Claire C., Derks E.M. A tutorial on conducting genome wide association studies: Quality control and statistical analysis. Int. J. Methods Psychiatr. Res. 2018;27(2). DOI 10.1002/mpr.1608Martin A.R., Atkinson E.G., Chapman S.B., Stevenson A., Stroud R.E., Abebe T., Akena D., … Ramesar R., Shiferaw W., Stein D.J., Teferra S., van der Merwe C., Zingela Z. Low-coverage sequencing cost-effectively detects known and novel variation in underrepresented populations. Am. J. Hum. Genet. 2021;108(4):656-668. DOI 10.1016/j.ajhg.2021.03.012Martin A.R., Atkinson E.G., Chapman S.B., Stevenson A., Stroud R.E., Abebe T., Akena D., … Ramesar R., Shiferaw W., Stein D.J., Teferra S., van der Merwe C., Zingela Z. Low-coverage sequencing cost-effectively detects known and novel variation in underrepresented populations. Am. J. Hum. Genet. 2021;108(4):656-668. DOI 10.1016/j.ajhg.2021.03.012Maxam A.M., Gilbert W. A new method for sequencing DNA. Proc. Natl. Acad. Sci. USA. 1977;74(2):560-564. DOI 10.1073/pnas.74. 2.560Maxam A.M., Gilbert W. A new method for sequencing DNA. Proc. Natl. Acad. Sci. USA. 1977;74(2):560-564. DOI 10.1073/pnas.74. 2.560Mills M.C., Barban N., Tropf F.C. An Introduction to Statistical Genetic Data Analysis. Cambridge, MA: MIT Press, 2020Mills M.C., Barban N., Tropf F.C. An Introduction to Statistical Genetic Data Analysis. Cambridge, MA: MIT Press, 2020Mirzabekov A.D. Biochips in the biology and medicine of the XXI century. Vestnik Rossiyskoj Akademii Nauk = Herald of the Russian Academy of Sciences. 2003;73(5):412 (in Russian)Mirzabekov A.D. Biochips in the biology and medicine of the XXI century. Vestnik Rossiyskoj Akademii Nauk = Herald of the Russian Academy of Sciences. 2003;73(5):412 (in Russian)Moreland E., Borisov O.V., Semenova E.A., Larin A.K., Andryushchenko O.N., Andryushchenko L.B., Generozov E.V., Williams A.G., Ahmetov I.I. Polygenic profile of elite strength athletes. J. Strength. Cond. Res. 2022;36(9):2509-2514. DOI 10.1519/JSC.0000000000003901Moreland E., Borisov O.V., Semenova E.A., Larin A.K., Andryushchenko O.N., Andryushchenko L.B., Generozov E.V., Williams A.G., Ahmetov I.I. Polygenic profile of elite strength athletes. J. Strength. Cond. Res. 2022;36(9):2509-2514. DOI 10.1519/JSC.0000000000003901O’Connell J., Yun T., Moreno M., Li H., Litterman N., Kolesnikov A., Noblin E., … Wang W., Weldon C.H., Wilton P., Wong C., Auton A., Carroll A., McLean C.Y. A population-specific reference panel for improved genotype imputation in African Americans. Commun. Biol. 2021;4(1):1269. DOI 10.1038/s42003-021-02777-9O’Connell J., Yun T., Moreno M., Li H., Litterman N., Kolesnikov A., Noblin E., … Wang W., Weldon C.H., Wilton P., Wong C., Auton A., Carroll A., McLean C.Y. A population-specific reference panel for improved genotype imputation in African Americans. Commun. Biol. 2021;4(1):1269. DOI 10.1038/s42003-021-02777-9Pasaniuc B., Rohland N., McLaren P.J., Garimella K., Zaitlen N., Li H., Gupta N., … Haas D.W., Liang L., Sunyaev S., Patterson N., de Bakker P.I.W., Reich D., Price A.L. Extremely low-coverage sequencing and imputation increases power for genome-wide association studies. Nat. Genet. 2012;44(6):631-635. DOI 10.1038/ng.2283Pasaniuc B., Rohland N., McLaren P.J., Garimella K., Zaitlen N., Li H., Gupta N., … Haas D.W., Liang L., Sunyaev S., Patterson N., de Bakker P.I.W., Reich D., Price A.L. Extremely low-coverage sequencing and imputation increases power for genome-wide association studies. Nat. Genet. 2012;44(6):631-635. DOI 10.1038/ng.2283Pinakhina D., Yermakovich D., Vergasova E., Kasyanov E., Rukavishnikov G., Rezapova V., Kolosov, … Plotnikov N., Ilinsky V., Neznanov N., Mazo G., Kibitov A., Rakitko A., Artomov M. GWAS of depression in 4,520 individuals from the Russian population highlights the role of MAGI2 (S-SCAM) in the gut-brain axis. Front. Genet. 2022;13:972196. DOI 10.3389/fgene.2022.972196Pinakhina D., Yermakovich D., Vergasova E., Kasyanov E., Rukavishnikov G., Rezapova V., Kolosov, … Plotnikov N., Ilinsky V., Neznanov N., Mazo G., Kibitov A., Rakitko A., Artomov M. GWAS of depression in 4,520 individuals from the Russian population highlights the role of MAGI2 (S-SCAM) in the gut-brain axis. Front. Genet. 2022;13:972196. DOI 10.3389/fgene.2022.972196Price A.L., Patterson N.J., Plenge R.M., Weinblatt M.E., Shadick N.A., Reich D. Principal components analysis corrects for stratification in genome-wide association studies. Nat. Genet. 2006;38(8):904-909. DOI 10.1038/ng1847Price A.L., Patterson N.J., Plenge R.M., Weinblatt M.E., Shadick N.A., Reich D. Principal components analysis corrects for stratification in genome-wide association studies. Nat. Genet. 2006;38(8):904-909. DOI 10.1038/ng1847Purcell S., Neale B., Todd-Brown K., Thomas L., Ferreira M.A.R., Bender D., Maller J., Sklar P., de Bakker P.I.W., Daly M.J., Sham P.C. PLINK: a tool set for whole-genome association and populationbased linkage analyses. Am. J. Hum. Genet. 2007;81(3):559-575. DOI 10.1086/519795Purcell S., Neale B., Todd-Brown K., Thomas L., Ferreira M.A.R., Bender D., Maller J., Sklar P., de Bakker P.I.W., Daly M.J., Sham P.C. PLINK: a tool set for whole-genome association and populationbased linkage analyses. Am. J. Hum. Genet. 2007;81(3):559-575. DOI 10.1086/519795Ramirez A.H., Sulieman L., Schlueter D.J., Halvorson A., Qian J., Ratsimbazafy F., Loperena R., … Denny J.C., Carroll R.J., Glazer D., Harris P.A., Hripcsak G., Philippakis A., Roden D.M.; All of Us research program. The All of Us research program: Data quality, utility, and diversity. Patterns (N Y ). 2022;3(8):100570. DOI 10.1016/j.patter.2022.100570Ramirez A.H., Sulieman L., Schlueter D.J., Halvorson A., Qian J., Ratsimbazafy F., Loperena R., … Denny J.C., Carroll R.J., Glazer D., Harris P.A., Hripcsak G., Philippakis A., Roden D.M.; All of Us research program. The All of Us research program: Data quality, utility, and diversity. Patterns (N Y ). 2022;3(8):100570. DOI 10.1016/j.patter.2022.100570Rhoads A., Au K.F. PacBio Sequencing and its applications. Genomics Proteomics Bioinformatics. 2015;13(5):278-289. DOI 10.1016/j.gpb.2015.08.002Rhoads A., Au K.F. PacBio Sequencing and its applications. Genomics Proteomics Bioinformatics. 2015;13(5):278-289. DOI 10.1016/j.gpb.2015.08.002Roshyara N.R., Kirsten H., Horn K., Ahnert P., Scholz M. Impact of pre-imputation SNP-filtering on genotype imputation results. BMC Genet. 2014;15(1):88. DOI 10.1186/s12863-014-0088-5Roshyara N.R., Kirsten H., Horn K., Ahnert P., Scholz M. Impact of pre-imputation SNP-filtering on genotype imputation results. BMC Genet. 2014;15(1):88. DOI 10.1186/s12863-014-0088-5Rubinacci S., Delaneau O., Marchini J. Genotype imputation using the Positional Burrows Wheeler Transform. PLoS Genet. 2020;16(11): e1009049. DOI 10.1371/journal.pgen.1009049Rubinacci S., Delaneau O., Marchini J. Genotype imputation using the Positional Burrows Wheeler Transform. PLoS Genet. 2020;16(11): e1009049. DOI 10.1371/journal.pgen.1009049Sanger F., Nicklen S., Coulson A.R. DNA sequencing with chain-terminating inhibitors. Proc. Natl. Acad. Sci. USA. 1977;74(12):5463- 5467. DOI 10.1073/pnas.74.12.5463Sanger F., Nicklen S., Coulson A.R. DNA sequencing with chain-terminating inhibitors. Proc. Natl. Acad. Sci. USA. 1977;74(12):5463- 5467. DOI 10.1073/pnas.74.12.5463Scheet P., Stephens M. A fast and flexible statistical model for largescale population genotype data: Applications to inferring missing genotypes and haplotypic phase. Am. J. Hum. Genet. 2006;78(4): 629-644. DOI 10.1086/502802Scheet P., Stephens M. A fast and flexible statistical model for largescale population genotype data: Applications to inferring missing genotypes and haplotypic phase. Am. J. Hum. Genet. 2006;78(4): 629-644. DOI 10.1086/502802Shendure J., Balasubramanian S., Church G.M., Gilbert W., Rogers J., Schloss J.A., Waterston R.H. DNA sequencing at 40: past, present and future. Nature. 2017;550(7676):345-353. DOI 10.1038/nature 24286Shendure J., Balasubramanian S., Church G.M., Gilbert W., Rogers J., Schloss J.A., Waterston R.H. DNA sequencing at 40: past, present and future. Nature. 2017;550(7676):345-353. DOI 10.1038/nature 24286Smith L.M., Sanders J.Z., Kaiser R.J., Hughes P., Dodd C., Connell C.R., Heiner C., Kent S.B.H., Hood L.E. Fluorescence detection in automated DNA sequence analysis. Nature. 1986;321(6071): 674-679. DOI 10.1038/321674a0Smith L.M., Sanders J.Z., Kaiser R.J., Hughes P., Dodd C., Connell C.R., Heiner C., Kent S.B.H., Hood L.E. Fluorescence detection in automated DNA sequence analysis. Nature. 1986;321(6071): 674-679. DOI 10.1038/321674a0Stahl K., Gola D., König I.R. Assessment of imputation quality: comparison of phasing and imputation algorithms in real data. Front. Genet. 2021;12:724037. DOI 10.3389/fgene.2021.724037Stahl K., Gola D., König I.R. Assessment of imputation quality: comparison of phasing and imputation algorithms in real data. Front. Genet. 2021;12:724037. DOI 10.3389/fgene.2021.724037Sudlow C., Gallacher J., Allen N., Beral V., Burton P., Danesh J., Downey P., Elliott P., Green J., Landray M., Liu B., Matthews P., Ong G., Pell J., Silman A., Young A., Sprosen T., Peakman T., Collins R. UK Biobank: An open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med. 2015;12(3):e1001779. DOI 10.1371/journal.pmed.1001779Sudlow C., Gallacher J., Allen N., Beral V., Burton P., Danesh J., Downey P., Elliott P., Green J., Landray M., Liu B., Matthews P., Ong G., Pell J., Silman A., Young A., Sprosen T., Peakman T., Collins R. UK Biobank: An open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med. 2015;12(3):e1001779. DOI 10.1371/journal.pmed.1001779Sudmant P.H., Rausch T., Gardner E.J., Handsaker R.E., Abyzov A., Huddleston J., Zhang Y., … Gerstein M.B., Bashir A., Stegle O., Devine S.E., Lee C., Eichler E.E., Korbel J.O. An integrated map of structural variation in 2,504 human genomes. Nature. 2015; 526(7571):75-81. DOI 10.1038/nature15394Sudmant P.H., Rausch T., Gardner E.J., Handsaker R.E., Abyzov A., Huddleston J., Zhang Y., … Gerstein M.B., Bashir A., Stegle O., Devine S.E., Lee C., Eichler E.E., Korbel J.O. An integrated map of structural variation in 2,504 human genomes. Nature. 2015; 526(7571):75-81. DOI 10.1038/nature15394Taliun D., Harris D.N., Kessler M.D., Carlson J., Szpiech Z.A., Torres R., … Cupples L.A., Laurie C.C., Jaquish C.E., Hernandez R.D., O’Connor T.D., Abecasis G.R. Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program. Nature. 2021; 590(7845):290-299. DOI 10.1038/s41586-021-03205-yTaliun D., Harris D.N., Kessler M.D., Carlson J., Szpiech Z.A., Torres R., … Cupples L.A., Laurie C.C., Jaquish C.E., Hernandez R.D., O’Connor T.D., Abecasis G.R. Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program. Nature. 2021; 590(7845):290-299. DOI 10.1038/s41586-021-03205-yThe Haplotype Reference Consortium. A reference panel of 64,976 haplotypes for genotype imputation. Nat. Genet. 2016;48:1279- 1283. DOI 10.1038/ng.3643The Haplotype Reference Consortium. A reference panel of 64,976 haplotypes for genotype imputation. Nat. Genet. 2016;48:1279- 1283. DOI 10.1038/ng.3643Usoltsev D., Kolosov N., Rotar O., Loboda A., Boyarinova M., Moguchaya E., Kolesova E., … Laiho P., Kostareva A., Konradi A., Shlyakhto E., Palotie A., Daly M.J., Artomov M. Understanding complex trait susceptibilities and ethnical diversity in a sample of 4,145 Russians through analysis of clinical and genetic data. bioRxiv. 2023. DOI 10.1101/2023.03.23.534000Usoltsev D., Kolosov N., Rotar O., Loboda A., Boyarinova M., Moguchaya E., Kolesova E., … Laiho P., Kostareva A., Konradi A., Shlyakhto E., Palotie A., Daly M.J., Artomov M. Understanding complex trait susceptibilities and ethnical diversity in a sample of 4,145 Russians through analysis of clinical and genetic data. bioRxiv. 2023. DOI 10.1101/2023.03.23.534000Wall J.D., Stawiski E.W., Ratan A., Kim H.L., Kim C., Gupta R., Suryamohan K., … Radha V., Mohan V., Majumder P.P., Seshagiri S., Seo J.-S., Schuster S.C., Peterson A.S. The GenomeAsia 100K Project enables genetic discoveries across Asia. Nature. 2019; 576(7785):106-111. DOI 10.1038/s41586-019-1793-zWall J.D., Stawiski E.W., Ratan A., Kim H.L., Kim C., Gupta R., Suryamohan K., … Radha V., Mohan V., Majumder P.P., Seshagiri S., Seo J.-S., Schuster S.C., Peterson A.S. The GenomeAsia 100K Project enables genetic discoveries across Asia. Nature. 2019; 576(7785):106-111. DOI 10.1038/s41586-019-1793-zWang D.G., Fan J.-B., Siao C.-J., Berno A., Young P., Sapolsky R., Ghandour G., Perkins N., Winchester E., Spencer J., Kruglyak L., Stein L., Hsie L., Topaloglou T., Hubbell E., Robinson E., Mittmann M., Morris M.S., Shen N., Kilburn D., Rioux J., Nusbaum C., Rozen S., Hudson T.J., Lipshutz R., Chee M., Lander E.S. Large-scale identification, mapping, and genotyping of single-nucleotide polymorphisms in the human genome. Science. 1998;280(5366):1077- 1082. DOI 10.1126/science.280.5366.1077Wang D.G., Fan J.-B., Siao C.-J., Berno A., Young P., Sapolsky R., Ghandour G., Perkins N., Winchester E., Spencer J., Kruglyak L., Stein L., Hsie L., Topaloglou T., Hubbell E., Robinson E., Mittmann M., Morris M.S., Shen N., Kilburn D., Rioux J., Nusbaum C., Rozen S., Hudson T.J., Lipshutz R., Chee M., Lander E.S. Large-scale identification, mapping, and genotyping of single-nucleotide polymorphisms in the human genome. Science. 1998;280(5366):1077- 1082. DOI 10.1126/science.280.5366.1077Wang Q.S., Huang H. Methods for statistical fine-mapping and their applications to auto-immune diseases. Semin. Immunopathol. 2022; 44(1):101-113. DOI 10.1007/s00281-021-00902-8Wang Q.S., Huang H. Methods for statistical fine-mapping and their applications to auto-immune diseases. Semin. Immunopathol. 2022; 44(1):101-113. DOI 10.1007/s00281-021-00902-8Weale M.E. A survey of current software for haplotype phase inference. Hum. Genomics. 2004;1(2):141. DOI 10.1186/1479-7364-1-2-141Weale M.E. A survey of current software for haplotype phase inference. Hum. Genomics. 2004;1(2):141. DOI 10.1186/1479-7364-1-2-141Weng Z.-Q., Saatchi M., Schnabel R.D., Taylor J.F., Garrick D.J. Recombination locations and rates in beef cattle assessed from parentoffspring pairs. Gen. Select. Evol. 2014;46(1):34. DOI 10.1186/ 1297-9686-46-34Weng Z.-Q., Saatchi M., Schnabel R.D., Taylor J.F., Garrick D.J. Recombination locations and rates in beef cattle assessed from parentoffspring pairs. Gen. Select. Evol. 2014;46(1):34. DOI 10.1186/ 1297-9686-46-34Wu D., Dou J., Chai X., Bellis C., Wilm A., Shih C.C., … Wong W.-C., Xie Z., Yeo K.K., Zhang L., Zhai W., Zhao Y. Large-scale wholegenome sequencing of three diverse Asian populations in Singapore. Cell. 2019;179(3):736-749.e15. DOI 10.1016/j.cell.2019.09.019Wu D., Dou J., Chai X., Bellis C., Wilm A., Shih C.C., … Wong W.-C., Xie Z., Yeo K.K., Zhang L., Zhai W., Zhao Y. Large-scale wholegenome sequencing of three diverse Asian populations in Singapore. Cell. 2019;179(3):736-749.e15. DOI 10.1016/j.cell.2019.09.019Yang H.-C., Lin H.-C., Kang M., Chen C.-H., Lin C.-W., Li L.-H., Wu J.-Y., Chen Y.-T., Pan W.-H. SAQC: SNP array quality control. BMC Bioinformatics. 2011;12(1):100. DOI 10.1186/1471-2105-12-100Yang H.-C., Lin H.-C., Kang M., Chen C.-H., Lin C.-W., Li L.-H., Wu J.-Y., Chen Y.-T., Pan W.-H. SAQC: SNP array quality control. BMC Bioinformatics. 2011;12(1):100. DOI 10.1186/1471-2105-12-100Yoo S.-K., Kim C.-U., Kim H.L., Kim S., Shin J.-Y., Kim N., Yang J.S.W., Lo K.-W., Cho B., Matsuda F., Schuster S.C., Kim C., Kim J.-I., Seo J.-S. NARD: whole-genome reference panel of 1779 Northeast Asians improves imputation accuracy of rare and lowfrequency variants. Genome Med. 2019;11(1):64. DOI 10.1186/ s13073-019-0677-zYoo S.-K., Kim C.-U., Kim H.L., Kim S., Shin J.-Y., Kim N., Yang J.S.W., Lo K.-W., Cho B., Matsuda F., Schuster S.C., Kim C., Kim J.-I., Seo J.-S. NARD: whole-genome reference panel of 1779 Northeast Asians improves imputation accuracy of rare and lowfrequency variants. Genome Med. 2019;11(1):64. DOI 10.1186/ s13073-019-0677-zYu K., Das S., LeFaive J., Kwong A., Pleiness J., Forer L., Schönherr S., Fuchsberger C., Smith A.V., Abecasis G.R. Meta-imputation: An efficient method to combine genotype data after imputation with multiple reference panels. Am. J. Hum. Genet. 2022;109(6):1007-1015. DOI 10.1016/j.ajhg.2022.04.002Yu K., Das S., LeFaive J., Kwong A., Pleiness J., Forer L., Schönherr S., Fuchsberger C., Smith A.V., Abecasis G.R. Meta-imputation: An efficient method to combine genotype data after imputation with multiple reference panels. Am. J. Hum. Genet. 2022;109(6):1007-1015. DOI 10.1016/j.ajhg.2022.04.002Zhao S., Jing W., Samuels D.C., Sheng Q., Shyr Y., Guo Y. Strategies for processing and quality control of Illumina genotyping arrays. Brief. Bioinform. 2018;19(5):765-775. DOI 10.1093/bib/bbx012Zhao S., Jing W., Samuels D.C., Sheng Q., Shyr Y., Guo Y. Strategies for processing and quality control of Illumina genotyping arrays. Brief. Bioinform. 2018;19(5):765-775. DOI 10.1093/bib/bbx012

The authors declare that there are no conflicts of interest present.