Using BioPAX-Parser (BiP) to Annotate Lists of Biological Entities with Pathway Data

Abstract

Proteins and genes are widely involved in activation or inhibition of the communication flow between a receptor and a transcription factor within a biological pathway. The key to fully understand proteins’ functional roles is the deduction of the relationship between pathways and proteins. To facilitate the understanding of the complex flow of interactions characterizing biological pathways, in the last years, several public and private databases have been built to store, represent, visualize, and share pathways information. Pathway Enrichment Analysis (PEA) makes it possible to take advantage of the pathway databases information to discover connections with biological mechanisms. PEA methods help researchers to overcome the problem of interpreting gene lists, or other biological entity lists of interest, disconnected from the biological context, facilitating and validating their findings. Here, we introduce the BioPAX-Parser (BiP), an automatic and graphics-based tool aimed at performing PEA by using pathways data encoded in BioPAX format. BiP is fully developed using Java 8, and it helps the researcher to perform pathways enrichment analysis, merely loading a list of proteins/genes of interest. Enrichment in BiP has been performed by implementing Hypergeometric test, along with False Discovery Rate (FDR) and Bonferroni multiple-test statistical correctors. A case study of using BiP to annotate endometrial cancer gene list is also presented.