P0204(w)Hol(e)Istic Gene Ontology and Pathway Analysis Using Open Source Web Tools
Downstream analysis of high throughput and next generation sequencing experiments (NGS) can often provide researchers with a means of deciphering their results. These downstream analyses often elucidate clusters of genes or networks of biological processes that have an interaction under the condition being studied. One convention for examining gene interactions is to conduct downstream investigations based upon gene ontology (GO), pathway, and network analyses of statistically significant genes of interest. Unfortunately, the software available for these types of analyses is too often expensive, not species specific, and subject to gaps in annotation. These difficulties can cause studies to omit this downstream step, limiting the utility of the data. In order to facilitate pathway and network analyses of candidate gene lists from high-throughput studies, a workflow was constructed based on the use of open sourced freely available software and genomic databases.
Results:
Downstream analysis using the “(w)HOL(e)ISTIC gene ontology enrichment” approach, which is centered around the overlap of multiple open source software to annotate, analyze, and visualize biological networks. It is a 3 stage process in which stage 1 (Annotation) is the generation of alias identifiers. Stage 2 (Analysis) is a two-part process generating ontologies and networks with statistical inferences. Stage 2 relies on info from databases such as Reactome, KEGG, and InterPro. Stage 3 (Visualization) allows for figure creation.
Conclusion:
The use of open source web-based tools can facilitate the conversion of gene list data from various studies into explorable networks of biological interest, allowing researchers a usable protocol for downstream analysis.