{"title":"Bpop:一种在单群和多群结构群体中估计基础群体等位基因频率的有效程序","authors":"I. Strandén, E. Mäntysaari","doi":"10.23986/afsci.90955","DOIUrl":null,"url":null,"abstract":"Base population allele frequencies (AF) should be used in genomic evaluations. A program named Bpop was implemented to estimate base population AF using a generalized least squares (GLS) method when the base population individuals can be assigned to groups. The required dense matrix products involving (A22 ) -1v were implemented efficiently using sparse submatrices of A-1, where A and A22 are pedigree relationship matrices for all and genotyped animals, respectively. Three approaches were implemented: iteration on pedigree (IOP), iteration in memory (IM), and direct inversion by sparsity preserving Cholesky decomposition (CHM). The test data had 1.5 million animals genotyped using 50240 markers. Total computing time (the product (A22) -11) was 53 min (1.2 min) by IOP, 51 min (0.3 min) by IM, and 56 min (4.6 min) by CHM. Peak computer core memory use was 0.67 GB by IOP, 0.80 GB by IM, and 7.53 GB by CHM. Thus, the IOP and IM approaches can be recommended for large data sets because of their low memory use and computing time.","PeriodicalId":7393,"journal":{"name":"Agricultural and Food Science","volume":"31 1","pages":""},"PeriodicalIF":1.0000,"publicationDate":"2020-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Bpop: an efficient program for estimating base population allele frequencies in single and multiple group structured populations\",\"authors\":\"I. Strandén, E. Mäntysaari\",\"doi\":\"10.23986/afsci.90955\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Base population allele frequencies (AF) should be used in genomic evaluations. A program named Bpop was implemented to estimate base population AF using a generalized least squares (GLS) method when the base population individuals can be assigned to groups. The required dense matrix products involving (A22 ) -1v were implemented efficiently using sparse submatrices of A-1, where A and A22 are pedigree relationship matrices for all and genotyped animals, respectively. Three approaches were implemented: iteration on pedigree (IOP), iteration in memory (IM), and direct inversion by sparsity preserving Cholesky decomposition (CHM). The test data had 1.5 million animals genotyped using 50240 markers. Total computing time (the product (A22) -11) was 53 min (1.2 min) by IOP, 51 min (0.3 min) by IM, and 56 min (4.6 min) by CHM. Peak computer core memory use was 0.67 GB by IOP, 0.80 GB by IM, and 7.53 GB by CHM. Thus, the IOP and IM approaches can be recommended for large data sets because of their low memory use and computing time.\",\"PeriodicalId\":7393,\"journal\":{\"name\":\"Agricultural and Food Science\",\"volume\":\"31 1\",\"pages\":\"\"},\"PeriodicalIF\":1.0000,\"publicationDate\":\"2020-06-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Agricultural and Food Science\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://doi.org/10.23986/afsci.90955\",\"RegionNum\":4,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"AGRICULTURE, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Agricultural and Food Science","FirstCategoryId":"97","ListUrlMain":"https://doi.org/10.23986/afsci.90955","RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"AGRICULTURE, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 7
摘要
基础群体等位基因频率(AF)应用于基因组评估。利用广义最小二乘(GLS)方法,在基本种群个体可以被分配到群体的情况下,实现了一个名为Bpop的程序来估计基本种群的AF。所需的包含(A22) -1v的密集矩阵乘积使用A-1的稀疏子矩阵有效地实现,其中A和A22分别是所有和基因型动物的家系关系矩阵。实现了三种方法:谱系迭代(IOP)、内存迭代(IM)和保持稀疏度的Cholesky分解(CHM)直接反演。测试数据使用50240个标记对150万只动物进行基因分型。总计算时间(乘积(A22) -11) IOP为53 min (1.2 min), IM为51 min (0.3 min), CHM为56 min (4.6 min)。IOP、IM和CHM的计算机核心内存使用峰值分别为0.67 GB、0.80 GB和7.53 GB。因此,IOP和IM方法可以推荐用于大型数据集,因为它们的内存使用和计算时间较低。
Bpop: an efficient program for estimating base population allele frequencies in single and multiple group structured populations
Base population allele frequencies (AF) should be used in genomic evaluations. A program named Bpop was implemented to estimate base population AF using a generalized least squares (GLS) method when the base population individuals can be assigned to groups. The required dense matrix products involving (A22 ) -1v were implemented efficiently using sparse submatrices of A-1, where A and A22 are pedigree relationship matrices for all and genotyped animals, respectively. Three approaches were implemented: iteration on pedigree (IOP), iteration in memory (IM), and direct inversion by sparsity preserving Cholesky decomposition (CHM). The test data had 1.5 million animals genotyped using 50240 markers. Total computing time (the product (A22) -11) was 53 min (1.2 min) by IOP, 51 min (0.3 min) by IM, and 56 min (4.6 min) by CHM. Peak computer core memory use was 0.67 GB by IOP, 0.80 GB by IM, and 7.53 GB by CHM. Thus, the IOP and IM approaches can be recommended for large data sets because of their low memory use and computing time.
期刊介绍:
Agricultural and Food Science (AFSci) publishes original research reports on agriculture and food research related to primary production and which have a northern dimension. The fields within the scope of the journal include agricultural economics, agricultural engineering, animal science, environmental science, horticulture, plant and soil science and primary production-related food science. Papers covering both basic and applied research are welcome.
AFSci is published by the Scientific Agricultural Society of Finland. AFSci, former The Journal of the Scientific Agricultural Society of Finland, has been published regularly since 1928. Alongside the printed version, online publishing began in 2000. Since the year 2010 Agricultural and Food Science has only been available online as an Open Access journal, provided to the user free of charge. Full texts are available online from 1945 on.