What is the difference between GWAS and Association mapping?

  

Aspect	Genome-Wide Association Studies (GWAS)	Association Mapping
Scope	Analyzes genetic variants across the entire genome	Analyzes genetic variants within candidate genes or genomic regions of interest
Marker Density	High marker density, typically covering the entire genome	Marker density may vary, often focused on specific genomic regions or candidate genes
Sample Size	Large sample sizes are often required to detect significant associations due to stringent statistical thresholds	Smaller sample sizes may be sufficient due to more targeted analysis
Statistical Power	Generally higher statistical power to detect associations due to genome-wide coverage	Statistical power may vary depending on marker density and effect size
Discovery of Novel Loci	GWAS can identify novel loci and genetic variants associated with traits	Association mapping may focus on known candidate genes or genomic regions, potentially missing novel associations
Multiple Testing Correction	Requires stringent correction for multiple testing due to testing numerous markers across the genome	Correction for multiple testing may be less stringent due to fewer markers tested
Population Structure	Important to account for population structure to avoid spurious associations	Population structure may have less impact due to more targeted analysis
Candidate Gene Studies	Less focused on specific candidate genes initially, but candidate genes may be identified post hoc	Often focused on specific candidate genes or genomic regions from the outset

 

GWAS offers a comprehensive approach to identify genetic variants associated with traits across the entire genome, whereas association mapping typically involves a more targeted analysis of specific candidate genes or genomic regions. Each approach has its strengths and limitations, and the choice between them depends on the research objectives, available resources, and characteristics of the traits being studied.