When Does Choice of Accuracy Measure Alter Imputation Accuracy Assessments?
When Does Choice of Accuracy Measure Alter Imputation Accuracy Assessments?
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DOI：
10.1371/journal.pone.0137601
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发表时间：
2015
期刊：
影响因子：
3.7
通讯作者：
Saccone NL
中科院分区：
文献类型：
--
作者：
Ramnarine S;Zhang J;Chen LS;Culverhouse R;Duan W;Hancock DB;Hartz SM;Johnson EO;Olfson E;Schwantes-An TH;Saccone NL
插补是推断未分型变异的基因型的过程，用于识别和改进遗传关联结果。插补数据的不准确性可能会扭曲变异与疾病之间观察到的关联。许多统计数据被用来评估准确性;一些比较插补到基因型数据和其他计算没有参考真正的基因型。先前的工作表明，插补质量评分（IQS），这是基于科恩的kappa统计和比较插补基因型概率的真实基因型，适当调整的机会协议，但是，它并不常用。为了确定准确性评估的差异，我们比较了IQS与一致率，平方相关性和插补程序中内置的准确性指标。对来自1000个基因组参考人群（AFR N = 246和EUR N = 379）的基因型进行掩蔽，以匹配几个SNP阵列的分型单核苷酸多态性（SNP）覆盖率，并在与吸烟行为相关的区域用BEAGLE 3.3.2和IMPUTE 2进行插补。对尼古丁依赖协作遗传研究和非裔美国人尼古丁依赖遗传研究的测序受试者进行了额外的设盲和插补（N = 1，481名非裔美国人和N = 1，480名欧洲裔美国人）。我们的研究结果提供了进一步的证据，一致率膨胀的准确性估计，特别是对于罕见和低频的变异。对于常见变异，平方相关、BEAGLE R2、IMPUTE 2 INFO和IQS对插补准确度的评估结果相似。然而，对于罕见和低频变异，与IQS相比，其他统计量在准确性评估方面往往更自由。在评估插补准确性时，IQS是重要的考虑因素，特别是对于罕见和低频变异。
Imputation, the process of inferring genotypes for untyped variants, is used to identify and refine genetic association findings. Inaccuracies in imputed data can distort the observed association between variants and a disease. Many statistics are used to assess accuracy; some compare imputed to genotyped data and others are calculated without reference to true genotypes. Prior work has shown that the Imputation Quality Score (IQS), which is based on Cohen’s kappa statistic and compares imputed genotype probabilities to true genotypes, appropriately adjusts for chance agreement; however, it is not commonly used. To identify differences in accuracy assessment, we compared IQS with concordance rate, squared correlation, and accuracy measures built into imputation programs. Genotypes from the 1000 Genomes reference populations (AFR N = 246 and EUR N = 379) were masked to match the typed single nucleotide polymorphism (SNP) coverage of several SNP arrays and were imputed with BEAGLE 3.3.2 and IMPUTE2 in regions associated with smoking behaviors. Additional masking and imputation was conducted for sequenced subjects from the Collaborative Genetic Study of Nicotine Dependence and the Genetic Study of Nicotine Dependence in African Americans (N = 1,481 African Americans and N = 1,480 European Americans). Our results offer further evidence that concordance rate inflates accuracy estimates, particularly for rare and low frequency variants. For common variants, squared correlation, BEAGLE R2, IMPUTE2 INFO, and IQS produce similar assessments of imputation accuracy. However, for rare and low frequency variants, compared to IQS, the other statistics tend to be more liberal in their assessment of accuracy. IQS is important to consider when evaluating imputation accuracy, particularly for rare and low frequency variants.