利用Mendel进行全基因组QTL快速分析
Fast Genome-Wide QTL Analysis Using Mendel
摘要：
孟德尔软件当前版本中的系谱GWAS（选项29）是用于进行大规模全基因组QTL分析的优化子程序。该分析（a）适用于随机样本数据、谱系数据或两者的混合，（b）在运行时间和记忆要求方面都是高效的，（c）适应单变量和多变量性状，（d）适用于常染色体和X连锁基因座，（e）正确处理性状、协变量和基因型中的缺失数据，（f）允许参数之间的协变量调整和约束，（g）使用理论或基于SNP的经验亲缘关系矩阵用于加性多基因效应，（h）允许额外的方差分量，例如显性多基因效应和家庭效应，（i）检测和报告离群个体和谱系，以及（j）允许通过$t$分布进行稳健估计。目前的论文评估了这些能力的遗传分析研讨会19（GAW19）测序数据。我们分析了家庭和随机样本数据集的模拟和真实表型。例如，当联合测试8个纵向测量的收缩压（SBP）和舒张压（DBP）性状时，孟德尔需要在标准笔记本电脑上花费78分钟来读取，质量检查和分析849个个体和830万个SNP的数据集。对641个个体的20，643个表达性状进行全基因组eQTL分析，其中830万个SNP需要30个小时，在一个集群上使用20个平行运行。孟德尔可在\url{http://www.genetics.ucla.edu/software}上免费获得。
英文摘要：
Pedigree GWAS (Option 29) in the current version of the Mendel software is an optimized subroutine for performing large scale genome-wide QTL analysis. This analysis (a) works for random sample data, pedigree data, or a mix of both, (b) is highly efficient in both run time and memory requirement, (c) accommodates both univariate and multivariate traits, (d) works for autosomal and x-linked loci, (e) correctly deals with missing data in traits, covariates, and genotypes, (f) allows for covariate adjustment and constraints among parameters, (g) uses either theoretical or SNP-based empirical kinship matrix for additive polygenic effects, (h) allows extra variance components such as dominant polygenic effects and household effects, (i) detects and reports outlier individuals and pedigrees, and (j) allows for robust estimation via the $t$-distribution. The current paper assesses these capabilities on the genetics analysis workshop 19 (GAW19) sequencing data. We analyzed simulated and real phenotypes for both family and random sample data sets. For instance, when jointly testing the 8 longitudinally measured systolic blood pressure (SBP) and diastolic blood pressure (DBP) traits, it takes Mendel 78 minutes on a standard laptop computer to read, quality check, and analyze a data set with 849 individuals and 8.3 million SNPs. Genome-wide eQTL analysis of 20,643 expression traits on 641 individuals with 8.3 million SNPs takes 30 hours using 20 parallel runs on a cluster. Mendel is freely available at \url{http://www.genetics.ucla.edu/software}.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
