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One of the main contributions of SNPs in clinical research is genome-wide association study (GWAS). [38] Genome-wide genetic data can be generated by multiple technologies, including SNP array and whole genome sequencing. GWAS has been commonly used in identifying SNPs associated with diseases or clinical phenotypes or traits.
It identified two SNPs with significantly altered allele frequency between the two groups. These SNPs were located in the gene encoding complement factor H, which was an unexpected finding in the research of ARMD. The findings from these first GWA studies have subsequently prompted further functional research towards therapeutical manipulation ...
The first study of PheWAS was done on 6000 European-American population with 5 SNPs of interest picked for validation: rs1333049, rs2200733, rs3135388, rs6457620, and rs1333049. [9] Quality control was done by examining marker and sample genotyping efficiency, allele frequency calculations, and Hardy-Weinberg equilibrium tests. [9]
A SNP array can also be used to generate a virtual karyotype using software to determine the copy number of each SNP on the array and then align the SNPs in chromosomal order. [10] SNPs can also be used to study genetic abnormalities in cancer. For example, SNP arrays can be used to study loss of heterozygosity (LOH). LOH occurs when one allele ...
A quantitative trait locus (QTL) is a locus (section of DNA) that correlates with variation of a quantitative trait in the phenotype of a population of organisms. [1] QTLs are mapped by identifying which molecular markers (such as SNPs or AFLPs) correlate with an observed trait.
The use of SNPs is being extended in the HapMap project, which aims to provide the minimal set of SNPs needed to genotype the human genome. SNPs can also provide a genetic fingerprint for use in identity testing. [1] The increase of interest in SNPs has been reflected by the furious development of a diverse range of SNP genotyping methods.
For example, in a genetic association case-control study, such as Genome-wide association study, a point in a volcano plot represents a single-nucleotide polymorphism. Its x value can be the logarithm of the odds ratio and its y value can be -log 10 of the p value from a Chi-square test or a Chi-square test statistic. [4]
Nucleotide sequence analyses identify functional elements like protein binding sites, uncover genetic variations like SNPs, study gene expression patterns, and understand the genetic basis of traits. It helps to understand mechanisms that contribute to processes like replication and transcription. Some of the tasks involved are outlined below.