KOBAS 2.0: a web server for annotation and identification of enriched pathways and diseases

TLDR

High‑throughput experiments frequently identify large gene sets associated with biological or pathological processes. The aim is to determine which pathways and diseases are implicated by these gene sets. KOBAS 2.0 is a web server that maps input genes to known annotations, performs enrichment tests, and draws on 1327 species across five pathway and five disease databases to annotate pathways and diseases. The server is available at http://kobas.cbi.pku.edu.cn.

Abstract

High-throughput experimental technologies often identify dozens to hundreds of genes related to, or changed in, a biological or pathological process. From these genes one wants to identify biological pathways that may be involved and diseases that may be implicated. Here, we report a web server, KOBAS 2.0, which annotates an input set of genes with putative pathways and disease relationships based on mapping to genes with known annotations. It allows for both ID mapping and cross-species sequence similarity mapping. It then performs statistical tests to identify statistically significantly enriched pathways and diseases. KOBAS 2.0 incorporates knowledge across 1327 species from 5 pathway databases (KEGG PATHWAY, PID, BioCyc, Reactome and Panther) and 5 human disease databases (OMIM, KEGG DISEASE, FunDO, GAD and NHGRI GWAS Catalog). KOBAS 2.0 can be accessed at http://kobas.cbi.pku.edu.cn .