大型基因组亲缘矩阵求逆算法的优化研究

doi:10.11843/j.issn.0366-6964.2020.08.004

Abstract

Abstract: Both GBLUP and ssGBLUP methods involved in the inversion of genomic relationship matrices in genomic selection, and large-scale matrix inversion operations were time-consuming. The purpose of this study was to improve the efficiency of the inverse operation of large genomic relationship matrix. The genomic relationship matrix from real data and simulated data was constructed, and the Intel MKL matrix function was introduced, and the efficiency of matrix inversion was improved by reducing the number of iterations (method 1) and repeating the block (method 2), programming to implement algorithms and test computing time on desktop computers and servers. The results showed that the acceleration ratio of the direct inversion function with the MKL was 0.898 when calculating the genomic relationship matrix of 4 000×4 000 using method 1. The calculation speed of 16 000×16 000 was 1.006 times more than that of the inversion function in MKL; The calculation speed of method 2 in the 4 000×4 000 genomic relationship matrix was 1.084 times more than that of the MKL inversion function; For larger 128 000×128 000 matrix inversion operations, the acceleration ratio of this method was 1.805 times more than that of the inversion function in MKL. Compared with MKL direct inversion function, the improved two methods have higher efficiency.

Key words: genomic selection, matrix inversion, block iterative inverse

CLC Number:

S828.2

ZHOU Jie, ZENG Weijun, YANG Tianrui, CHENG Yufei, LONG Xianda, JING Peiqi, ZENG Yangshuang, XU Xu, TANG Guoqing. Optimization Study of Inverse Algorithm of Large Genomic Relationship Matrix[J]. Acta Veterinaria et Zootechnica Sinica, 2020, 51(8): 1804-1810.

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Optimization Study of Inverse Algorithm of Large Genomic Relationship Matrix

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