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Yung-Hsiang Huang

Publications and source records attributed to Yung-Hsiang Huang.

2 recordsLinked to original sources

A Bayes regression approach to array-CGH data.

This paper develops a Bayes regression model having change points for the analysis of array-CGH data by utilizing not only the underlying spatial structure of the genomic alterations but also the observation that the noise associated with the ratio of the fluorescence intensities is bigger when the intensities get smaller. We show that this Bayes regression approach is particularly suitable for the analysis of cDNA microarray-CGH data, which are generally noisier than those using genomic clones. A simulation study and a real data analysis are included to illustrate this approach.

Bayes Theorem↗

Directly measured insulin resistance and the assessment of clustered cardiovascular risks in hypertension.

BACKGROUND: The purpose of the study was to use factor analysis to investigate the contribution of a directly measured insulin sensitivity index, steady-state plasma glucose (SSPG) from insulin suppression test (IST), to a clustering of cardiovascular risk factors in hypertensive subjects. METHODS: A total of 204 nondiabetic hypertensive patients who received IST for SSPG were included for current analysis. Factor analysis was performed to explore the contribution of SSPG as additional information to a clustering of risk factors in these subjects. RESULTS: In factor analysis, SSPG aggregated with metabolic variables in an obesity-hyperinsulinemia domain that included two factors: one with positive loadings for SSPG, 2-h glucose, and Log 2-h insulin; and the other with positive loadings for body mass index, waist circumference, and fasting glucose. Fasting insulin linked the two factors together and explained 38.3% of the total variance. Systolic and diastolic blood pressures were loaded on a blood pressure domain separately. The third domain consisted of two factors: one with positive loadings for Log triglycerides and negative loading for high-density lipoprotein cholesterol; and the other with positive loadings for Log triglycerides and non-high-density lipoprotein cholesterol. The model loaded without SSPG explained a proportion of the total variance (78.5%) similar to that achieved with the model loaded with SSPG (77.1%). CONCLUSIONS: Directly measured insulin sensitivity index SSPG clustered with 2-h glucose and Log 2-h insulin in factor analysis in a cohort consisting entirely of hypertensive subjects. However, the contribution of SSPG as additional information to explain the total variance seems to be insignificant.

Adult↗