ProbABEL 软件包可用于分析基于孟德尔随机化的全基因组关联研究数据。
ProbABEL package for genome-wide association analysis of imputed data.
机构信息
Department of Epidemiology, Erasmus MC, Postbus 2040, 3000 CA Rotterdam, The Netherlands.
出版信息
BMC Bioinformatics. 2010 Mar 16;11:134. doi: 10.1186/1471-2105-11-134.
BACKGROUND
Over the last few years, genome-wide association (GWA) studies became a tool of choice for the identification of loci associated with complex traits. Currently, imputed single nucleotide polymorphisms (SNP) data are frequently used in GWA analyzes. Correct analysis of imputed data calls for the implementation of specific methods which take genotype imputation uncertainty into account.
RESULTS
We developed the ProbABEL software package for the analysis of genome-wide imputed SNP data and quantitative, binary, and time-till-event outcomes under linear, logistic, and Cox proportional hazards models, respectively. For quantitative traits, the package also implements a fast two-step mixed model-based score test for association in samples with differential relationships, facilitating analysis in family-based studies, studies performed in human genetically isolated populations and outbred animal populations.
CONCLUSIONS
ProbABEL package provides fast efficient way to analyze imputed data in genome-wide context and will facilitate future identification of complex trait loci.
背景
在过去的几年中，全基因组关联（GWA）研究已成为鉴定与复杂性状相关基因座的首选工具。目前，常染色体 SNP 数据的导入在 GWA 分析中经常被使用。正确的导入数据分析需要采用特定的方法，以考虑基因型导入的不确定性。
结果
我们开发了 ProbABEL 软件包，用于分析全基因组导入的 SNP 数据，以及线性、逻辑和 Cox 比例风险模型下的定量、二项式和直至事件时间的结果。对于定量性状，该软件包还实现了一种快速两步混合模型基于评分的关联检验方法，用于具有不同关系的样本中，促进了基于家族的研究、在人类遗传隔离群体和杂种动物群体中进行的研究的分析。
结论
ProbABEL 软件包为全基因组范围内导入数据分析提供了快速高效的方法，并将有助于未来鉴定复杂性状基因座。
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