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METHODS AND COMPOSITIONS FOR IMPUTING OR PREDICTING GENOTYPE OR PHENOTYPE

机译:用于实现或预测基因型或表型的方法和组合物

摘要

Methods and compositions to impute or predict genotype, haplotype, molecular phenotype, agronomic phenotypes, and/or coancestry are provided. Methods and compositions provided include using latent space to generate latent space representations or latent vectors that are independent of underlying genotypic or phenotypic data. The methods may include generating a universal latent space representation by encoding discrete or continuous variables derived from genotypic or phenotypic data into latent vectors through a machine learning-based encoder framework. Provided herein are universal methods of parametrically representing genotypic or phenotypic data obtained from one or more populations or sample sets to impute or predict a genotype or phenotype of interest.
机译:提供了推算或预测基因型,单倍型,分子表型,农艺表型和/或同源性的方法和组合物。提供的方法和组成包括使用潜在空间生成独立于基础基因型或表型数据的潜在空间表示或潜在向量。该方法可以包括通过基于机器学习的编码器框架,通过将从基因型或表型数据导出的离散或连续变量编码为潜矢量来生成通用潜空间表示。本文提供了参数化表示从一个或多个群体或样本集获得的基因型或表型数据以推算或预测感兴趣的基因型或表型的通用方法。

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