This medium throughput SNP Genotyping system is ideal in clinical facilities for all sorts of genotyping applications, including pharmacogenomics [12], [13], [14] and medical genetic applications [15], [16] as well as population genetics [17], [18].
These genetic applications for the mouse genome will dramatically advance in vivo gene function studies.
Next-generation Sequencing (NGS) is a rapidly evolving technology with demonstrated benefits for forensic genetic applications, and the strategies to analyze and manage the massive NGS datasets are currently in development.
It is well suited for genetic applications since it is both computationally efficient and models genetic causal mechanisms well.
Progressively more numbers of microsatellites are being linked to genes associated with adaptive and functional variations, therefore making their utility broader in genetic applications.
The enormous potential for genetic applications has created an equally large challenge when it comes to processing, sharing, and analyzing the petabytes of data being generated by cheaper and more efficient machines.
Single nucleotide polymorphisms (SNP) have proven to be powerful genetic markers for genetic applications in medicine, life science and agriculture.
Several fields of research (population, medical, and forensic genetic) are interested in the analysis of mtSNPs for several genetic applications.
Self-identified race is a common method used to track and control for population stratification; however, social constructs of race are not necessarily informative for genetic applications.
The results from simulation studies suggest that the model displays favorable statistical properties and can be robust in practical genetic applications.
We suggest, on the basis of the evidence presented in this paper, that supervised learning methods have a useful role to play in genetic applications where we are interested in differences between pre defined groups of individuals.
