A brief survey on GWAS and ML algorithms

Nowadays, we can see an increasing number of studies in genomics that try to find out ways to detect diseases and also better prevention methods. The public would gain a lot of benefits from the studies. With the rapid development of genotyping technology, it creates opportunity to the researchers to go depth to the genetic and look into the variants. Most of the time, researchers would found different set of variants that increase the risk to the different diseases. Moreover, it is found that different populations would have same or would have different set of variants. The association of the variants to the disease is still in mystery but could be discovered by thorough studies. The studies about the variants are also known as genome wide association studies (GWAS). Key roles in GWAS are not limited to the bioinformaticians or pure scientists only, but also computer scientists could contribute to the studies by developing algorithms and tools. Therefore, this paper would like to briefly introduce GWAS and facilitate researchers with several studies that have applied machine learning (ML) algorithms in GWAS.