Visualization of Functional Assignment of Disease Genes and Mutations

Abstract

Visualization is one of the important components of data science. This paper presents a method that utilizes the functional annotations of human genes for identifying, analysing, and visualizing the most important and highly represented biological process functions in disease mutations. The analysis and visualization of human gene functions are important for understanding disease progression, gene-disease associations, and disease-gene-mutation relationships. In the past two decades, a number of research projects have been proposed for the analysis and discovery of gene functions and gene functional annotations. However, little work has been done for the functional analysis and annotation of mutations and genetic variants. Effectively identifying significant genetic functions of disease mutations can benefit medical applications related to genetic treatment of hard diseases like some cancer types. We present experiments and results involving more than 25,000 human genes with more than 220,000 genetic mutations from two of the most commonly used mutation databases. We used heat maps for visualization of the clustered biological process functions from the Gene Ontology among the disease mutations.