title: Measuring the spatial correlations of protein binding sites.
abstract: Understanding the interactions of different DNA binding proteins is a crucial first step toward deciphering gene regulatory mechanism. With advances of high-throughput sequencing technology such as ChIP-seq, the genome-wide binding sites of many proteins have been profiled under different biological contexts. It is of great interest to quantify the spatial correlations of the binding sites, such as their overlaps, to provide information for the interactions of proteins. Analyses of the overlapping patterns of binding sites have been widely performed, mostly based on ad hoc methods. Due to the heterogeneity and the tremendous size of the genome, such methods often lead to biased even erroneous results.
  
  
  
  In this work, we discover a Simpson's paradox phenomenon in assessing the genome-wide spatial correlation of protein binding sites. Leveraging information from publicly available data, we propose a testing procedure for evaluating the significance of overlapping from a pair of proteins, which accounts for background artifacts and genome heterogeneity. Real data analyses demonstrate that the proposed method provide more biologically meaningful results.
  
  
  
  An R package is available at http://www.sta.cuhk.edu.hk/YWei/ChIPCor.html
  
  
  
  ywei@sta.cuhk.edu.hk or hao.wu@emory.edu
  
  
  
  Supplementary data are available at Bioinformatics online.
authors: Department of Statistics, The Chinese University of Hong Kong, Shatin, NT, Hong Kong and.
authors: Yingying
authors: Y
authors: Wei
authors: Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA 30322, USA.
authors: Hao
authors: H
authors: Wu
mesh_terms: D001665:Binding Sites; D004268:DNA-Binding Proteins; D055786:Gene Knockout Techniques; D016678:Genome; D023281:Genomics; D057166:High-Throughput Screening Assays; D016014:Linear Models; D011485:Protein Binding
chemical_list: D004268:DNA-Binding Proteins