Genome-wide complex trait analysis: Difference between revisions

Revision as of 14:32, 3 April 2019

Revision as of 09:02, 4 April 2019

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=== GWAS power ===

GCTA estimates can be used to resolve the [[missing heritability problem]] and [[Design of experiments|design]] GWASes which will yield genome-wide statistically-significant hits. This is done by comparing the GCTA estimate with the results of smaller GWASes. If a GWAS of n=10k using SNP data fails to turn up any hits, but the GCTA indicates a high heritability accounted for by SNPs, then that implies that there are a large number of variants are involved ([[polygenic|polygenicity]] variants) and thus that much larger GWASes will be required to accurately estimate each SNP's effectseffect and directly account for a fraction of the GCTA heritability.

== Disadvantages ==