What is genetic fine-mapping?

What is genetic fine-mapping?

Fine-mapping is the process by which a trait-associated region from a genome-wide association study (GWAS) is analysed to identify the particular genetic variants that are likely to causally influence the examined trait.

What is Bayesian fine-mapping analysis?

Bayesian genetic fine-mapping studies aim to identify the specific causal variants within GWAS loci responsible for each association, reporting credible sets of plausible causal variants, which are interpreted as containing the causal variant with some “coverage probability”.

What is GWAS data?

A genome-wide association study (GWAS) is an approach used in genetics research to associate specific genetic variations with particular diseases. The method involves scanning the genomes from many different people and looking for genetic markers that can be used to predict the presence of a disease.

What is the unit of genetic map?

In genetics, a centimorgan (abbreviated cM) or map unit (m.u.) is a unit for measuring genetic linkage. It is defined as the distance between chromosome positions (also termed loci or markers) for which the expected average number of intervening chromosomal crossovers in a single generation is 0.01.

How do you interpret Bayesian credible intervals?

Interpretation of the Bayesian 95% confidence interval (which is known as credible interval): there is a 95% probability that the true (unknown) estimate would lie within the interval, given the evidence provided by the observed data.

What is the meaning of haplotype?

A haplotype is a group of genes within an organism that was inherited together from a single parent. The word “haplotype” is derived from the word “haploid,” which describes cells with only one set of chromosomes, and from the word “genotype,” which refers to the genetic makeup of an organism.

What is the goal of association mapping?

Association mapping seeks to identify specific functional variants (loci, alleles) linked to phenotypic differences in a trait to facilitate detection of trait causing DNA sequence polymorphisms and selection of genotypes that closely resemble the phenotype (Oraguzie et al., 2007).

Why are SNPs used in GWAS?

GWAS are used to identify whether common SNPs in the population are associated with disease. This can be done by undertaking a case:control study to see whether a specific SNP is more common in people with a specific condition, compared to those without the condition. Take our position 5 SNP above.

Where is Gene mapping used?

Genetic mapping – also called linkage mapping – can offer firm evidence that a disease transmitted from parent to child is linked to one or more genes. Mapping also provides clues about which chromosome contains the gene and precisely where the gene lies on that chromosome.

What can fine mapping of genes be used for?

Once a gene is mapped, that information may be used to compare abnormal genes with normal ones. Molecular biological techniques may then be used to search for methods of treating and preventing conditions resulting from genetic abnormality. Want to thank TFD for its existence?

What’s the difference between gene mapping and genetic mapping?

Gene mapping is the sequential allocation of loci to a relative position on a chromosome. Genetic maps are species-specific and comprised of genomic markers and/or genes and the genetic distance between each marker.

How is fine mapping of genetic variants becoming more sophisticated?

Fine-mapping of genetic variants has become increasingly sophisticated: initially, variants were simply overlapped with functional elements, but now the impact of variants on regulatory activity and direct variant-gene 3D interactions can be identified.

Which is the best definition of Fine mapping?

ABSTRACT : A fine-mapping method exploiting linkage disequilibrium was used to detect quantitative trait loci (QTL) on the X chromosome affecting milk production, body conformation and productivity traits. Evaluation of a fine-mapping method exploiting linkage disequilibrium in livestock populations: simulation study.