MixFit: Methodology for Computing Ancestry-Related Genetic Scores at the Individual Level and Its Application to the Estonian and Finnish Population Studies.
MixFit: Methodology for Computing Ancestry-Related Genetic Scores at the Individual Level and Its Application to the Estonian and Finnish Population Studies.
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MixFit：计算个人水平上与祖先相关的遗传评分的方法及其在爱沙尼亚和芬兰人群研究中的应用。
DOI：
10.1371/journal.pone.0170325
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发表时间：
2017
期刊：
影响因子：
3.7
通讯作者：
Metspalu A
中科院分区：
文献类型：
--
作者：
Haller T;Leitsalu L;Fischer K;Nuotio ML;Esko T;Boomsma DI;Kyvik KO;Spector TD;Perola M;Metspalu A
个人层面的医学信息可以成为个性化医学、医学、人口学和历史研究以及追溯个人历史的宝贵资源。我们报告了一种基于全基因组数据定量确定个人遗传祖先的新方法。根据与参考人群的比较，将数字祖先成分评分分配给个体。这些比较是利用现有的分析管道进行的，利用基因型定相，相似性矩阵计算和我们的MixFit添加多维最佳拟合。该方法是通过研究爱沙尼亚和芬兰人口的地理环境。我们展示了这些其他接近的欧洲人群的遗传组成的主要差异，以及它们如何相互影响。我们的分析流程的组成部分是免费提供的计算机程序和脚本，其中一个是内部开发的（可在www.geenivaramu.ee/en/tools/mixfit上获得）。
Ancestry information at the individual level can be a valuable resource for personalized medicine, medical, demographical and history research, as well as for tracing back personal history. We report a new method for quantitatively determining personal genetic ancestry based on genome-wide data. Numerical ancestry component scores are assigned to individuals based on comparisons with reference populations. These comparisons are conducted with an existing analytical pipeline making use of genotype phasing, similarity matrix computation and our addition—multidimensional best fitting by MixFit. The method is demonstrated by studying Estonian and Finnish populations in geographical context. We show the main differences in the genetic composition of these otherwise close European populations and how they have influenced each other. The components of our analytical pipeline are freely available computer programs and scripts one of which was developed in house (available at: www.geenivaramu.ee/en/tools/mixfit).