Journal
BRIEFINGS IN BIOINFORMATICS
Volume 23, Issue 3, Pages -Publisher
OXFORD UNIV PRESS
DOI: 10.1093/bib/bbac067
Keywords
SNP heritability; missing heritability; complex phenotypes; genomic prediction
Ask authors/readers for more resources
This article reviews the recently developed and commonly used SNP heritability estimation methods for continuous and binary phenotypes, focusing on their model assumptions, parameter optimization, ability to handle multiple phenotypes and longitudinal measurements, as well as their use of individual-level data versus summary statistics.
Over the past decade, statistical methods have been developed to estimate single nucleotide polymorphism (SNP) heritability, which measures the proportion of phenotypic variance explained by all measured SNPs in the data. Estimates of SNP heritability measure the degree to which the available genetic variants influence phenotypes and improve our understanding of the genetic architecture of complex phenotypes. In this article, we review the recently developed and commonly used SNP heritability estimation methods for continuous and binary phenotypes from the perspective of model assumptions and parameter optimization. We primarily focus on their capacity to handle multiple phenotypes and longitudinal measurements, their ability for SNP heritability partition and their use of individual-level data versus summary statistics. State-of-the-art statistical methods that are scalable to the UK Biobank dataset are also elucidated in detail.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available