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典型文献
A novel genomic prediction method combining randomized Haseman-Elston regression with a modified algorithm for Proven and Young for large genomic data
文献摘要:
Computational efficiency has become a key issue in genomic prediction(GP)owing to the massive his-torical datasets accumulated.We developed hereby a new super-fast GP approach(SHEAPY)combining randomized Haseman-Elston regression(RHE-reg)with a modified Algorithm for Proven and Young(APY)in an additive-effect model,using the former to estimate heritability and then the latter to invert a large genomic relationship matrix for best linear prediction.In simulation results with varied sizes of training population,GBLUP,HEAPY|A and SHEAPY showed similar predictive performance when the size of a core population was half that of a large training population and the heritability was a fixed value,and the computational speed of SHEAPY was faster than that of GBLUP and HEAPY|A.In simulation results with varied heritability,SHEAPY showed better predictive ability than GBLUP in all cases and than HEAPY|A in most cases when the size of a core population was 4/5 that of a small training population and the training population size was a fixed value.As a proof of concept,SHEAPY was applied to the anal-ysis of two real datasets.In an Arabidopsis thaliana F2 population,the predictive performance of SHEAPY was similar to or better than that of GBLUP and HEAPY|A in most cases when the size of a core population(200)was 2/3 of that of a small training population(300).In a sorghum multiparental population,SHEAPY showed higher predictive accuracy than HEAPY|A for all of three traits,and than GBLUP for two traits.SHEAPY may become the GP method of choice for large-scale genomic data.
文献关键词:
作者姓名:
Hailan Liu;Guo-Bo Chen
作者机构:
Maize Research Institute,Sichuan Agricultural University,Chengdu 611130,Sichuan,China;Phase Ⅰ Clinical Research Institute,Zhejiang Provincial People's Hospital,Affiliated People's Hospital,Hangzhou Medical College,Hangzhou 310014,Zhejiang,China;Key Laboratory of Endocrine Gland Diseases of Zhejiang Province,Hangzhou 310014,Zhejiang,China
引用格式:
[1]Hailan Liu;Guo-Bo Chen-.A novel genomic prediction method combining randomized Haseman-Elston regression with a modified algorithm for Proven and Young for large genomic data)[J].作物学报(英文版),2022(02):550-554
A类:
Haseman,Elston,SHEAPY,APY,HEAPY,multiparental
B类:
novel,genomic,prediction,method,combining,randomized,regression,modified,algorithm,Proven,Young,large,Computational,efficiency,has,become,key,issue,GP,owing,massive,his,torical,datasets,accumulated,We,developed,hereby,new,super,approach,RHE,Algorithm,additive,effect,model,using,former,estimate,heritability,then,latter,invert,relationship,matrix,best,linear,In,simulation,results,varied,sizes,training,population,GBLUP,showed,similar,predictive,performance,when,core,was,half,that,fixed,value,computational,speed,faster,than,better,cases,most,small,proof,concept,applied,anal,ysis,two,real,Arabidopsis,thaliana,F2,sorghum,higher,accuracy,three,traits,may,choice,scale
AB值:
0.368051
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