Tree-structured supervised learning and the genetics of hypertension

Proceedings of the National Academy of Sciences of the United States of America
Jing HuangRichard A Olshen

Abstract

This paper is about an algorithm, FlexTree, for general supervised learning. It extends the binary tree-structured approach (Classification and Regression Trees, CART) although it differs greatly in its selection and combination of predictors. It is particularly applicable to assessing interactions: gene by gene and gene by environment as they bear on complex disease. One model for predisposition to complex disease involves many genes. Of them, most are pure noise; each of the values that is not the prevalent genotype for the minority of genes that contribute to the signal carries a "score." Scores add. Individuals with scores above an unknown threshold are predisposed to the disease. For the additive score problem and simulated data, FlexTree has cross-validated risk better than many cutting-edge technologies to which it was compared when small fractions of candidate genes carry the signal. For the model where only a precise list of aberrant genotypes is predisposing, there is not a systematic pattern of absolute superiority; however, overall, FlexTree seems better than the other technologies. We tried the algorithm on data from 563 Chinese women, 206 hypotensive, 357 hypertensive, with information on ethnicity, menopausal sta...Continue Reading

References

Dec 7, 2000·Genetic Epidemiology·H Zhang, G Bonney
Feb 22, 2001·Annual Review of Physiology·J P Morello, D G Bichet
Feb 22, 2002·European Journal of Biochemistry·Stephanie BechtelRita Bernhardt
Aug 13, 2003·Current Atherosclerosis Reports·Gerald M Reaven

❮ Previous
Next ❯

Citations

Jul 26, 2011·Journal of Autism and Developmental Disorders·Yun JiaoEdward H Herskovits
Jan 17, 2008·European Journal of Human Genetics : EJHG·Yan V Sun, Sharon Lr Kardia
Apr 13, 2007·Biostatistics·Mee Young Park, Trevor Hastie
Sep 22, 2011·Human Heredity·Annette M MolinaroNilanjan Chatterjee
Jun 3, 2014·PloS One·Sangho YoonRichard A Olshen
Dec 26, 2006·Pharmacogenomics·Eugene LinEllson Y Chen
Oct 11, 2007·Pharmacogenomics·Alison A MotsingerDavid M Reif
Oct 26, 2016·Journal of Human Genetics·Dong-Hao JinJoobae Park
Jan 30, 2019·Archives of Toxicology·Tobias TietzHolger Schwender
Aug 12, 2009·European Journal of Epidemiology·Ronja Foraita
Jan 27, 2006·Genetic Epidemiology·Wen-Harn PanHsing-Yi Chang
Jan 1, 2009·Statistical Science : a Review Journal of the Institute of Mathematical Statistics·Charles KooperbergIndika Rajapakse

❮ Previous
Next ❯

Related Concepts

Related Feeds

CZI Human Cell Atlas Seed Network

The aim of the Human Cell Atlas (HCA) is to build reference maps of all human cells in order to enhance our understanding of health and disease. The Seed Networks for the HCA project aims to bring together collaborators with different areas of expertise in order to facilitate the development of the HCA. Find the latest research from members of the HCA Seed Networks here.