A multilevel model to address batch effects in copy number estimation using SNP arrays
A multilevel model to address batch effects in copy number estimation using SNP arrays
复制标题
DOI：
10.1093/biostatistics/kxq043
复制
发表时间：
2011-01-01
期刊：
影响因子：
2.1
通讯作者：
Irizarry, Rafael A.
中科院分区：
文献类型：
--
作者：
Scharpf, Robert B.;Ruczinski, Ingo;Irizarry, Rafael A.
染色体DNA拷贝数剂量的亚显微变化是常见的，并与许多遗传性疾病和癌症有关。最近的高通量技术具有允许检测基因组中跨越数千个碱基对的DNA拷贝数的片段变化的分辨率。全基因组关联研究（GWAS）可以同时筛选拷贝数表型和单核苷酸多态性（SNP）表型关联作为分析策略的一部分。然而，全基因组阵列分析特别容易受到批量效应的影响，因为制备DNA和处理数千个阵列的后勤工作通常涉及多个实验室和技术人员，或者随着时间的推移而改变试剂和实验室设备。未能调整批次效应可能导致不正确的推断，并需要低效的事后质量控制程序来排除与批次相关的区域。我们的工作扩展了以前的基于模型的方法，通过显式建模批处理和使用收缩，以提高基因座特定的拷贝数不确定性的估计拷贝数估计。该方法的主要特征包括使用来自实验数据的双等位基因基因型调用来估计背景和信号的批次特异性和基因座特异性参数，而不需要训练数据。我们用双相情感障碍和21号染色体三体的研究来说明这些观点。前者具有批次效应，其在分位数归一化强度中占主导地位，而后者说明了我们的方法对其中约27%的样品具有改变的拷贝数的数据集的鲁棒性。拷贝数的基因座特异性估计值可以绘制在拷贝数标度上，以研究嵌合现象并指导选择适当的下游方法来平滑拷贝数作为物理位置的函数。该软件是开源的，并在Bioconductor（http：www.bioconductor.org）的R包crlmm中实现。
Submicroscopic changes in chromosomal DNA copy number dosage are common and have been implicated in many heritable diseases and cancers. Recent high-throughput technologies have a resolution that permits the detection of segmental changes in DNA copy number that span thousands of base pairs in the genome. Genomewide association studies (GWAS) may simultaneously screen for copy number phenotype and single nucleotide polymorphism (SNP) phenotype associations as part of the analytic strategy. However, genomewide array analyses are particularly susceptible to batch effects as the logistics of preparing DNA and processing thousands of arrays often involves multiple laboratories and technicians, or changes over calendar time to the reagents and laboratory equipment. Failure to adjust for batch effects can lead to incorrect inference and requires inefficient post hoc quality control procedures to exclude regions that are associated with batch. Our work extends previous model-based approaches for copy number estimation by explicitly modeling batch and using shrinkage to improve locus-specific estimates of copy number uncertainty. Key features of this approach include the use of biallelic genotype calls from experimental data to estimate batch-specific and locus-specific parameters of background and signal without the requirement of training data. We illustrate these ideas using a study of bipolar disease and a study of chromosome 21 trisomy. The former has batch effects that dominate much of the observed variation in the quantile-normalized intensities, while the latter illustrates the robustness of our approach to a data set in which approximately 27% of the samples have altered copy number. Locus-specific estimates of copy number can be plotted on the copy number scale to investigate mosaicism and guide the choice of appropriate downstream approaches for smoothing the copy number as a function of physical position. The software is open source and implemented in the R package crlmm at Bioconductor (http:www.bioconductor.org).