TY - CHAP
T1 - Computational disease-risk prediction
T2 - Tools and statistical approaches
AU - Chimusa, Emile R.
PY - 2024/11/15
Y1 - 2024/11/15
N2 - It has become clear that a mixture between diverged populations (admixture) has been a recurrent feature in human evolution. Whole or genome-wide association studies (GWAS) have become a fundamental method for dissecting genetic variations and architecture of human conditions based on common polymorphisms. It is hoped that there will be several opportunities to use identified associated variants to comprehend the pathogenesis of human conditions, discover novel biomarkers, and protein targets, as well as predict clinical drugs and treatments for worldwide global health. Technological, statistical, and computational advances keep fostering the development of genomics tools ranging from GWAS to post-GWAS including polygenic risk scores and functional GWAS. We summarize the concepts of several computational genetic ancestries, polygenic risk scores, and GWAS approaches. In addition, we outline the implications, challenges, and opportunities, these approaches present and summarize with brief discussions of future research directions.
AB - It has become clear that a mixture between diverged populations (admixture) has been a recurrent feature in human evolution. Whole or genome-wide association studies (GWAS) have become a fundamental method for dissecting genetic variations and architecture of human conditions based on common polymorphisms. It is hoped that there will be several opportunities to use identified associated variants to comprehend the pathogenesis of human conditions, discover novel biomarkers, and protein targets, as well as predict clinical drugs and treatments for worldwide global health. Technological, statistical, and computational advances keep fostering the development of genomics tools ranging from GWAS to post-GWAS including polygenic risk scores and functional GWAS. We summarize the concepts of several computational genetic ancestries, polygenic risk scores, and GWAS approaches. In addition, we outline the implications, challenges, and opportunities, these approaches present and summarize with brief discussions of future research directions.
KW - Genome-wide association studies
KW - Genomics
KW - Human genetics
KW - Missing heritability
KW - Polygenic risk scores
KW - Risk prediction
KW - Statistical computing
UR - http://www.scopus.com/inward/record.url?scp=85214155225&partnerID=8YFLogxK
U2 - 10.1016/B978-0-443-18546-5.00006-1
DO - 10.1016/B978-0-443-18546-5.00006-1
M3 - Chapter
AN - SCOPUS:85214155225
SN - 9780443185472
T3 - Translational and Applied Genomics
SP - 91
EP - 106
BT - Population Genomics in the Developing World
A2 - Möller, Marlo
A2 - Uren, Caitlin
PB - Academic Press
CY - London, United Kingdom
ER -