What does CWAS mean in ASSOCIATIONS
CWAS stands for Candidate Wide Association Study. It is an approach to genetic epidemiology used to identify genetic variants associated with a phenotype or trait of interest. In this type of study, researchers use data from large-scale genome-wide association studies (GWAS) to look at the association between a single candidate gene and a trait of interest such as disease risk or drug response.
CWAS meaning in Associations in Community
CWAS mostly used in an acronym Associations in Category Community that means candidate wide association study
Shorthand: CWAS,
Full Form: candidate wide association study
For more information of "candidate wide association study", see the section below.
Essential Questions and Answers on candidate wide association study in "COMMUNITY»ASSOCIATIONS"
What does CWAS stand for?
CWAS stands for Candidate Wide Association Study.
How is a CWAS different from other types of genetic epidemiology studies?
A CWAS focuses on the association between a single candidate gene and the trait of interest, whereas other types of genetic epidemiology studies take a broader view and examine associations across multiple genes or genomic regions.
What kinds of traits can be studied in a CWAS?
Examples of traits that can be studied include disease risk, drug response, or any other measurable trait that has been linked to genotypes within GWAS data sets.
What kind of data is used in a CWAS?
The primary source of data used in a CWAS is high-throughput genotyping data from large-scale GWAS studies. This allows researchers to examine associations between the genotypes present within each individual sample and various traits or phenotypes.
What are the benefits of using CWAS?
The main benefit of using this approach is that it allows for more precise analyses than those possible with traditional methods as well as greater efficiency when examining small numbers of candidate genes compared to larger GWAS. Additionally, by narrowing down the focus on specific candidate genes, findings can be replicated more easily due to their localized nature compared to larger population based samples from GWAs which may produce false positive findings due to population stratification issues.
Final Words:
In conclusion, Candidate Wide Association Studies (CWAS) provide an effective way to explore potential gene-trait associations by leveraging large scale GWAs datasets while allowing for more targeted and efficient analysis than traditional methodologies would allow.
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