A A Berdnikova, I V Zorkoltseva, Y A Tsepilov, E E Elgaeva
{"title":"Genotype imputation in human genomic studies.","authors":"A A Berdnikova, I V Zorkoltseva, Y A Tsepilov, E E Elgaeva","doi":"10.18699/vjgb-24-70","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":44339,"journal":{"name":"Vavilovskii Zhurnal Genetiki i Selektsii","volume":null,"pages":null},"PeriodicalIF":0.9000,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11491486/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Vavilovskii Zhurnal Genetiki i Selektsii","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18699/vjgb-24-70","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"AGRICULTURE, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
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.
对于 DNA 微阵列或低覆盖率测序无法直接进行基因分型的遗传变异,估算是一种提供缺失信息的方法。估算在全基因组关联研究(GWAS)中发挥着至关重要的作用。它能显著增加研究变异的数量,从而提高方法的分辨率,增强不同队列和/或使用不同技术获得的数据的可比性,这对进行荟萃分析非常重要。在进行估算时,研究样本中只有部分基因变异是已知的,而标准(参考)样本拥有更完整的基因型数据(通常是全基因组测序的结果),可以对研究样本的基因型信息进行补充。由于估算所带来的益处以及估算工具和参考样本数据的日益普及,估算已成为人类基因组研究不可或缺的一部分。本综述的重点是人类基因组研究中的估算。综述的第一部分介绍了获取人类基因型信息的技术以及这些类型数据的特点。第二部分介绍了估算方法,列出了其实施阶段和相应的程序,介绍了最流行的参考面板和评估估算质量的方法。综述最后列举了在俄罗斯样本基因组研究中使用估算的实例。这篇综述说明了估算的重要性,提供了如何进行估算的信息,并系统地介绍了利用俄罗斯样本进行估算的结果。
期刊介绍:
The "Vavilov Journal of genetics and breeding" publishes original research and review articles in all key areas of modern plant, animal and human genetics, genomics, bioinformatics and biotechnology. One of the main objectives of the journal is integration of theoretical and applied research in the field of genetics. Special attention is paid to the most topical areas in modern genetics dealing with global concerns such as food security and human health.