A Flexible Gene-Based Test for Genome-Wide Association Studies

Genetic-based related tests are increasingly being viewed as a useful complement to the genome-wide association study (GWAS) [1]. The gene-based approach takes into account the association between traits within genes and all markers (usually SNPs), not each marker alone. Based on the underlying genetic makeup, the gene-based approach may be more powerful than the traditional GWAS based on a single SNP. For example, if a gene contains multiple pathogenic manifolds, some SNPs in the gene may show slight significance, which is usually indistinguishable from random noise in the first GWAS result .

Theoretical literature on gene - cultural interactions is increasingly important in the genome era. The whole genome related research (GWAS) showed an association between multiple genomes and multiple complex phenotypes, making it possible to detect genetically adaptive signals (54). However, the GWA should be interpreted carefully to study behavioral phenotypes such as IQ, education, and life history (55). The authors of such research stated as follows. "Genetic analysis of behavioral phenotypes is prone to misunderstandings, such as characterizing identified related mutants as" educational genes ". Educational level is mainly dependent on environmental factors (55). Statistical relationships between genetic variation and behavior are not necessarily cause-and-effect (55, 59), because mating mating, spatial autocorrelation, and shared environment may affect this relationship (55, 59) .

Approximately 20,000 subjects have been adjusted and implemented for genome-wide association analysis in order to investigate more than 50 candidate genes by 2011. This research needs to investigate the genetic variation of factors that lead to phenotypic fluctuations between co-identified individuals and stratified subjects based on behavior, cognition, and clinical features. Progress: With the funding of several GWAS and sequence projects, progress has been made on this goal. Although the current number of 6,000 GWAS targets is less than 20,000, the number of all exosome sequences far exceeds 1,200, which may reach 6,000 next year. Sequencing of all exosomes has identified 7 to 10 candidate genes and is expected to approach 50 targets in the future. CNV research is progressing. Generally, this work is subject.

With the advent of next-generation sequencing, we acquired enough sequence data to map genes of complex diseases such as diabetes, infertility, breast cancer, Alzheimer's disease. Genome-wide association studies are a useful way to identify mutations that cause such complicated diseases. Through these studies thousands of DNA variants associated with similar diseases and traits were identified. In addition, the possibility that genes are used for prognosis, diagnosis or treatment is one of the most important uses. Many studies discuss gene selection and promising methods for the use of genes to predict problems and prognostic problems and pitfalls in the disease.