GO-2D: identifying 2-dimensional cellular-localized functional modules in Gene Ontology

Jing Zhu,Zheng Guo,Min Zhang,Da Yang,Dong Wang,Jing Wang,Yanhui Li,Guohua Xiao

doi:10.1186/1471-2164-8-30

Abstract

BackgroundRapid progress in high-throughput biotechnologies (e.g. microarrays) and exponential accumulation of gene functional knowledge make it promising for systematic understanding of complex human diseases at functional modules level. Based on Gene Ontology, a large number of automatic tools have been developed for the functional analysis and biological interpretation of the high-throughput microarray data.ResultsDifferent from the existing tools such as Onto-Express and FatiGO, we develop a tool named GO-2D for identifying 2-dimensional functional modules based on combined GO categories. For example, it refines biological process categories by sorting their genes into different cellular component categories, and then extracts those combined categories enriched with the interesting genes (e.g., the differentially expressed genes) for identifying the cellular-localized functional modules. Applications of GO-2D to the analyses of two human cancer datasets show that very specific disease-relevant processes can be identified by using cellular location information.ConclusionFor studying complex human diseases, GO-2D can extract functionally compact and detailed modules such as the cellular-localized ones, characterizing disease-relevant modules in terms of both biological processes and cellular locations. The application results clearly demonstrate that 2-dimensional approach complementary to current 1-dimensional approach is powerful for finding modules highly relevant to diseases.

Highlights

Rapid progress in high-throughput biotechnologies and exponential accumulation of gene functional knowledge make it promising for systematic understanding of complex human diseases at functional modules level
Most existing approaches interpret the interesting genes using categories from three ontologies "biological process" (BP), "molecular function" (MF) and "cellular component" (CC) separately, which may be inefficient for mapping some specific modular activities in cells
The tabular results collect the following information of a combined category: Gene Ontology (GO) IDs, names and depths of categories, numbers of genes and interesting genes annotated in it, the observed p values, and the corrected p values for multiple tests of the combined categories

Summary

Introduction

Rapid progress in high-throughput biotechnologies (e.g. microarrays) and exponential accumulation of gene functional knowledge make it promising for systematic understanding of complex human diseases at functional modules level. Based on Gene Ontology, a large number of automatic tools have been developed for the functional analysis and biological interpretation of the high-throughput microarray data. For high-throughput microarray data analysis, translating lists of interesting genes (e.g., DEGs) into functional modules for understanding the biological phenomena has become an important routine task. Based on Gene Ontology, a large number of tools such as Onto-Express [8], FatiGO [9], GoMiner [10] and GOstat [11] have been developed for this purpose. In this paper, by combining categories from BP, CC, and MF, we propose GO-2D as a tool for finding 2-dimensional functional modules (e.g., the cellular-localized modules) for studying complex human diseases

Results

Discussion

Conclusion