NaviGO: interactive tool for visualization and functional similarity and coherence analysis with gene ontology

Qing Wei,Ishita K Khan,Satwica Yerneni,Ziyun Ding,Daisuke Kihara

doi:10.1186/s12859-017-1600-5

Qing Wei, Ishita K Khan + Show 3 more

Open Access

https://doi.org/10.1186/s12859-017-1600-5

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Journal: BMC Bioinformatics	Publication Date: Mar 20, 2017
Citations: 55	License type: open-access

Affiliation: Purdue University West Lafayette, Mayo Clinic

Abstract

BackgroundThe number of genomics and proteomics experiments is growing rapidly, producing an ever-increasing amount of data that are awaiting functional interpretation. A number of function prediction algorithms were developed and improved to enable fast and automatic function annotation. With the well-defined structure and manual curation, Gene Ontology (GO) is the most frequently used vocabulary for representing gene functions. To understand relationship and similarity between GO annotations of genes, it is important to have a convenient pipeline that quantifies and visualizes the GO function analyses in a systematic fashion.ResultsNaviGO is a web-based tool for interactive visualization, retrieval, and computation of functional similarity and associations of GO terms and genes. Similarity of GO terms and gene functions is quantified with six different scores including protein-protein interaction and context based association scores we have developed in our previous works. Interactive navigation of the GO function space provides intuitive and effective real-time visualization of functional groupings of GO terms and genes as well as statistical analysis of enriched functions.ConclusionsWe developed NaviGO, which visualizes and analyses functional similarity and associations of GO terms and genes. The NaviGO webserver is freely available at: http://kiharalab.org/web/navigo.

Highlights

The number of genomics and proteomics experiments is growing rapidly, producing an ever-increasing amount of data that are awaiting functional interpretation
The directed acyclic graph (DAG) structure is divided into three different Gene Ontology (GO) categories, namely, Biological Process (BP), Molecular Function (MF), and Cellular Component (CC)
Real-time and interactive rendering of GO terms Retrieving and mapping parental GO terms on the GO hierarchy for query GO terms is implemented as a basic functionality

Summary

Introduction

The number of genomics and proteomics experiments is growing rapidly, producing an ever-increasing amount of data that are awaiting functional interpretation. A number of function prediction algorithms were developed and improved to enable fast and automatic function annotation. With the well-defined structure and manual curation, Gene Ontology (GO) is the most frequently used vocabulary for representing gene functions. To understand relationship and similarity between GO annotations of genes, it is important to have a convenient pipeline that quantifies and visualizes the GO function analyses in a systematic fashion. GO is widely used as the vocabulary of gene functions [1]. GO terms are arranged in a hierarchical directed acyclic graph (DAG), where parental relationships between terms are represented. GO is updated periodically by the Gene Ontology Consortium [2], and currently holds over 44,000 terms.

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Conclusion