HIBLUP: an integration of statistical models on the BLUP framework for efficient genetic evaluation using big genomic data.

ABSTRACT: Human diseases and agricultural traits can be predicted by modeling a genetic random polygenic effect in linear mixed models. To estimate variance components and predict random effects of the model efficiently with limited computational resources has always been of primary concern, especially when it involves increasing the genotype data scale in the current genomic era. Here, we thoroughly reviewed the development history of statistical algorithms used in genetic evaluation and theoretically compared their computational complexity and applicability for different data scenarios. Most importantly, we presented a computationally efficient, functionally enriched, multi-platform and user-friendly software package named 'HIBLUP' to address the challenges that are faced currently using big genom

SUBMITTER: Yin L 

PROVIDER: S-EPMC10164590 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature