R PheWAS: data analysis and plotting tools for phenome-wide association studies in the R environment
R PheWAS: data analysis and plotting tools for phenome-wide association studies in the R environment
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DOI：
10.1093/bioinformatics/btu197
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发表时间：
2014-08-15
期刊：
影响因子：
5.8
通讯作者：
Denny, Joshua C.
中科院分区：
文献类型：
--
作者：
Carroll, Robert J.;Bastarache, Lisa;Denny, Joshua C.
全表型关联研究（PheWAS）已被用于复制已知的遗传关联，并发现遗传变异的新表型关联。这种PheWAS实现允许用户将ICD-9代码翻译为PheWAS病例和对照组，使用这些和/或其他表型进行协变量调整并绘制结果。我们通过在rs3135388（靠近HLA-DRB，与多发性硬化症相关）上复制PheWAS，并使用个体最大白细胞计数（WBC）作为连续测量来执行新的PheWAS，从而证明了这些方法。我们对rs3135388的研究结果与在相同数据集上的原始研究相比，重复了已知的关联，结果更加显著。我们的WBC PheWAS发现了预期的结果，包括与感染、骨髓增生性疾病和相关疾病（如贫血）的关联。实验结果证明了改进后的分类方案的性能和封装在该包中的PheWAS的灵活性。
Phenome-wide association studies (PheWAS) have been used to replicate known genetic associations and discover new phenotype associations for genetic variants. This PheWAS implementation allows users to translate ICD-9 codes to PheWAS case and control groups, perform analyses using these and/or other phenotypes with covariate adjustments and plot the results. We demonstrate the methods by replicating a PheWAS on rs3135388 (near HLA-DRB, associated with multiple sclerosis) and performing a novel PheWAS using an individual's maximum white blood cell count (WBC) as a continuous measure. Our results for rs3135388 replicate known associations with more significant results than the original study on the same dataset. Our PheWAS of WBC found expected results, including associations with infections, myeloproliferative diseases and associated conditions, such as anemia. These results demonstrate the performance of the improved classification scheme and the flexibility of PheWAS encapsulated in this package.