pgen.1011037.s002.pdf (545.03 kB)
Heatmap presenting the role random matrix played in matrix multiplication.
journal contribution
posted on 2024-01-11, 19:00 authored by Qi-Xin Zhang, Tianzi Liu, Xinxin Guo, Jianxin Zhen, Meng-yuan Yang, Saber Khederzadeh, Fang Zhou, Xiaotong Han, Qiwen Zheng, Peilin Jia, Xiaohu Ding, Mingguang He, Xin Zou, Jia-Kai Liao, Hongxin Zhang, Ji He, Xiaofeng Zhu, Daru Lu, Hongyan Chen, Changqing Zeng, Fan Liu, Hou-Feng Zheng, Siyang Liu, Hai-Ming Xu, Guo-Bo ChenWe generate a random matrix Sm×k sampling from N(0,1/k) and plot SST (B) against an identity matrix (A). We also generate two small populations containing 20 and 25 individuals, respectively. Their genotype matrices are noted as X1 and X2, and plot the matrix multiplication product before (C) and after encryption (D). The column number for the random matrix is k = 500 and the number of SNPs is m = 100.
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sharing summary statisticsmany merits comparingimproved statistical powerfinely devised multicommon statistical analysesmasked genotype matriceslevel genotype datarelatives estimated usingencrypted genomic datawidely used softwarevarious degrees basedstudy clearly demonstratesrandom matrix theorycovering 9 cohorts092 gwas samplesencrypted genotype data> b >,div >< pgenotype datarandom matrixb ><> bsearching relativesdetect relativescohort relativesuk biobankstrict qcssearching acrossrespective centersrequired precisionrelative identificationregression approachreg genotypic qualitiesgenomics studiesfalse positiveethical constraintsequivalently accurateencryption propertiescomputationally efficientcomplex application
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