Genome-Wide Association Study - Term Paper Example

This belief later changed when some other complex diseases came into existence and many people were worried since they could not identify the causes of these dangerous diseases. They suggested another study called genetic association. This study focused on the genetic variations in the individuals who tested to be suffering from the diseases. This study was showed more improvements from the first one that linked the diseases with family inheritance. More projects were intensified which led to the genome-wide association study, well known as GWAS.

GWAS is a study which is used to examine variations in genetics belonging to many individuals to identify how the variants have an association with a particular trait. However, GWAS has been identified as the best tool to be used in finding out the major causes of human mortality. One of the fields where GWAS has been used is the studies on the breast cancer (Huang, 2009). History of GWAS Genome-wide association studies have been in taking place for the last five years. It has led to very many discoveries in the science fields despite the fact it is associated with many problems that make some people to criticize it.

GWAS has been criticized by many journalists and scientist more especially on the way of study and the results achieved. Nevertheless, this study is improving in the way of research as high technology is applied in the most of its areas of concern (Visscher, Peter, Matthew Brown, Mark, McCarthy & Yang, 2012). Various studies have improved the development of GWAS in the scientific field. The uses of linkage analysis to associate the genetic variants with a certain disease of traits have made scientists to give wrong conclusions for the last 20 years.

This is because linkage mapping could not when the number of recombination is very large. It only worked with small recombination number. GWAS, at population level, used linkage disequilibrium (LD). Linkage disequilibrium deals with how alleles at some different loci are associated non-randomly. This LD was weakened by the large population that was used. HapMap project investigated the LD structure and a list of SNPs was found. These SNPs had captured common genomic variations of the human population.

Technology together control samples of population cohorts accelerated the possibility of conducting GWASs. The linkage disequilibrium between un-genotyped variants and the genotyped SNPs determines the GWAS (Visscher, Peter, Matthew Brown, Mark, McCarthy & Yang, 2012). The first GWAS was known in 2005. The first to be taken as the starting point paper was the Wellcome Trust Case Control Consortium (WTCCC) in 2007. This is because this paper covered GWAS for the most complex diseases by using a SNP chip that covered genome correctly.

There many discoveries of GWAS that have been done in the last five years. This study has emphasized more on biology rather than discoveries as compared to the past studies. Currently, more than 2000 loci can be associated to a particular trait that is more complex. Before 2007, loci association to a disease was not known (Visscher, Peter, Matthew Brown, Mark, McCarthy & Yang, 2012). GWAS has investigated more complex traits and many loci have been identified but not all of them have been completed.

This is because of inadequate statistical significance caused by false negatives. Many findings have been