Department of Statistics, Iowa State University, Ames, IA, USA.
Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, IA, USA.
Bioinformatics. 2018 Sep 1;34(17):2909-2917. doi: 10.1093/bioinformatics/bty227.
ChIP-seq experiments that are aimed at detecting DNA-protein interactions require biological replication to draw inferential conclusions, however there is no current consensus on how to analyze ChIP-seq data with biological replicates. Very few methodologies exist for the joint analysis of replicated ChIP-seq data, with approaches ranging from combining the results of analyzing replicates individually to joint modeling of all replicates. Combining the results of individual replicates analyzed separately can lead to reduced peak classification performance compared to joint modeling. Currently available methods for joint analysis may fail to control the false discovery rate at the nominal level.
We propose BinQuasi, a peak caller for replicated ChIP-seq data, that jointly models biological replicates using a generalized linear model framework and employs a one-sided quasi-likelihood ratio test to detect peaks. When applied to simulated data and real datasets, BinQuasi performs favorably compared to existing methods, including better control of false discovery rate than existing joint modeling approaches. BinQuasi offers a flexible approach to joint modeling of replicated ChIP-seq data which is preferable to combining the results of replicates analyzed individually.
Source code is freely available for download at https://cran.r-project.org/package=BinQuasi, implemented in R.
Supplementary data are available at Bioinformatics online.
旨在检测 DNA-蛋白质相互作用的 ChIP-seq 实验需要进行生物学复制以得出推论结论，但是目前对于如何使用生物学重复分析 ChIP-seq 数据还没有共识。很少有方法可用于复制的 ChIP-seq 数据的联合分析，方法范围从单独分析重复的结果组合到所有重复的联合建模。与联合建模相比，组合单独分析的重复结果可能会导致峰分类性能降低。目前用于联合分析的方法可能无法在名义水平上控制假发现率。
我们提出了 BinQuasi，这是一种用于复制 ChIP-seq 数据的峰调用程序，它使用广义线性模型框架联合建模生物学重复，并采用单边拟似然比检验来检测峰。当应用于模拟数据和真实数据集时，BinQuasi 的性能优于现有方法，包括比现有联合建模方法更好地控制假发现率。BinQuasi 提供了一种灵活的方法来联合建模复制的 ChIP-seq 数据，优于组合单独分析的重复结果。
源代码可在 https://cran.r-project.org/package=BinQuasi 上免费下载，它是用 R 语言实现的。
补充数据可在生物信息学在线获得。
