Exploratory Gene Ontology Analysis with Interactive Visualization.

Journal: Scientific reports
Published Date:

Abstract

The Gene Ontology (GO) is a central resource for functional-genomics research. Scientists rely on the functional annotations in the GO for hypothesis generation and couple it with high-throughput biological data to enhance interpretation of results. At the same time, the sheer number of concepts (>30,000) and relationships (>70,000) presents a challenge: it can be difficult to draw a comprehensive picture of how certain concepts of interest might relate with the rest of the ontology structure. Here we present new visualization strategies to facilitate the exploration and use of the information in the GO. We rely on novel graphical display and software architecture that allow significant interaction. To illustrate the potential of our strategies, we provide examples from high-throughput genomic analyses, including chromatin immunoprecipitation experiments and genome-wide association studies. The scientist can also use our visualizations to identify gene sets that likely experience coordinated changes in their expression and use them to simulate biologically-grounded single cell RNA sequencing data, or conduct power studies for differential gene expression studies using our built-in pipeline. Our software and documentation are available at http://aegis.stanford.edu .

Authors

  • Junjie Zhu
    Hunan University; zhujunjie@hnu.edu.cn.
  • Qian Zhao
    Key Lab of Cell Differentiation and Apoptosis of Ministry of Education, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Eugene Katsevich
    Department of Statistics and Data Science, Wharton School of the University of Pennsylvania, 265 South 37th Street, Philadelphia, Pennsylvania 19104, U.S.A.
  • Chiara Sabatti
    Department of Statistics, Stanford University, Stanford, CA, USA. sabatti@stanford.edu.