Prediction of Quantitative Traits Using Common Genetic Variants: Application to Body Mass Index
Sunghwan Bae, Sungkyoung Choi, Sung Min Kim, Taesung Park
Genomics Inform. 2016;14(4):149-159.   Published online 2016 Dec 30     DOI: https://doi.org/10.5808/GI.2016.14.4.149
Citations to this article as recorded by Crossref logo
Weighting approaches for a genetic risk score and an oxidative stress score for predicting the incidence of obesity
Seonmin Park, Hye Jin Yoo, Sun Ha Jee, Jong Ho Lee, Minjoo Kim
Diabetes/Metabolism Research and Reviews.2020;[Epub]     CrossRef
Investigation of prediction accuracy and the impact of sample size, ancestry, and tissue in transcriptome-wide association studies
James J. Fryett, Andrew P. Morris, Heather J. Cordell
Genetic Epidemiology.2020; 44(5): 425.     CrossRef
Signatures of selection analysis using whole-genome sequence data reveals novel candidate genes for pony and light horse types
Siavash Salek Ardestani, Mehdi Aminafshar, Mohammad Bagher Zandi Baghche Maryam, Mohammad Hossein Banabazi, Mehdi Sargolzaei, Younes Miar
Genome.2020; 63(8): 387.     CrossRef
Newly identified set of obesity-related genotypes and abdominal fat influence the risk of insulin resistance in a Korean population
Minjoo Kim, Sarang Jeong, Hye Jin Yoo, Hyoeun An, Sun Ha Jee, Jong Ho Lee
Clinical Genetics.2019; 95(4): 488.     CrossRef
Pure additive contribution of genetic variants to a risk prediction model using propensity score matching: application to type 2 diabetes
Chanwoo Park, Nan Jiang, Taesung Park
Genomics & Informatics.2019; 17(4): e47.     CrossRef
BMI prediction within a Korean population
Jin Sol Lee, Hyun Sub Cheong, Hyoung-Doo Shin
PeerJ.2017; 5: e3510.     CrossRef