Genome-wide association study of colorectal cancer using evolutionary computing

Abstract

The heritability of complex diseases is usually ascribed to interacting genetic alterations. Many diseases have been found that are influenced by genetic factors. Colorectal cancer (CRC) is a type of cancer starting from the colon or rectum that seriously threatens human health, and it has the chance to spread to other parts of the human body. The cause of CRC is multifactorial, including age, sex, intake of fat, etc. In addition, it has been suggested that genetic factors also play an essential role. Several genetic variations have been identified as associated with CRC. However, they only explain a small portion of the heritability. More advanced computational techniques are required to identify combinations of genetic factors. Recently, artificial intelligence algorithms have became a powerful tool for biomedical data analyses. In this thesis, I design an evolutionary algorithm for the identification of combinations of genetic factors, i.e., single nucleotide polymorphisms (SNPs), that can best explain the susceptibility to CRC.