Physical Sciences and Mathematics Commons^™

A Support Vector Machine Based Test For Incongruence Between Sets Of Trees In Tree Space, David C. Haws, Peter Huggins, Eric M. O'Neill, David W. Weisrock, Ruriko Yoshida

Statistics Faculty Publications

BACKGROUND: The increased use of multi-locus data sets for phylogenetic reconstruction has increased the need to determine whether a set of gene trees significantly deviate from the phylogenetic patterns of other genes. Such unusual gene trees may have been influenced by other evolutionary processes such as selection, gene duplication, or horizontal gene transfer.

RESULTS: Motivated by this problem we propose a nonparametric goodness-of-fit test for two empirical distributions of gene trees, and we developed the software GeneOut to estimate a p-value for the test. Our approach maps trees into a multi-dimensional vector space and then applies support vector machines (SVMs) …

A Proposed Methodology For Pairwise Comparison Of Treatment Levels In A Functional Data Setting, Olga A. Vsevolozhskaya, Mark C. Greenwood, Dmitri B. Holodov

Olga A. Vsevolozhskaya

An effect of procaine (novocaine) on the structural and functional properties of somatic cell membranes was studied based on erythrocyte acidity resistance. To study the effect of different levels of procaine (novocaine) in the bloodstream, the dynamics of the red blood cells rupture was measured after the addition of hydrochloric acid to the red blood cell suspension. The measurements were taken every 15 seconds for 12 minutes. Since the response was sampled at a high frequency, it can be regarded as functional data. One of the research questions was to compare rates of hemolysis under different procaine (novocaine) dosages. We …

Families Or Unrelated: The Evolving Debate In Genetic Association Studies, David W. Fardo, Richard Charnigo, Michael P. Epstein

Biostatistics Faculty Publications

To help uncover the genetic determinants of complex disease, a scientist often designs an association study using either unrelated subjects or family members within pedigrees. But which of these two subject recruitment paradigms is preferable? This editorial addresses the debate over the relative merits of family- and population-based genetic association studies. We begin by briefly recounting the evolution of genetic epidemiology and the rich crossroads of statistics and genetics. We then detail the arguments for the two aforementioned paradigms in recent and current applications. Finally, we speculate on how the debate may progress with the emergence of next-generation sequencing technologies.

A Proposed Methodology For Performing Follow-Up Tests To Compare Pairs Of Treatment Levels In Functional Linear Models, Olga A. Vsevolozhskaya, Mark C. Greenwood, Dmitri B. Holodov

Olga A. Vsevolozhskaya

No abstract provided.

Genetic Association Studies Of Copy-Number Variation: Should Assignment Of Copy Number States Precede Testing?, Patrick Breheny, Prabhakar Chalise, Anthony Batzler, Liewei Wang, Brooke L. Fridley

Biostatistics Faculty Publications

Recently, structural variation in the genome has been implicated in many complex diseases. Using genomewide single nucleotide polymorphism (SNP) arrays, researchers are able to investigate the impact not only of SNP variation, but also of copy-number variants (CNVs) on the phenotype. The most common analytic approach involves estimating, at the level of the individual genome, the underlying number of copies present at each location. Once this is completed, tests are performed to determine the association between copy number state and phenotype. An alternative approach is to carry out association testing first, between phenotype and raw intensities from the SNP array …

The Analysis Of Image Feature Robustness Using Cometcloud, Xin Qi, Hyunjoo Kim, Fuyong Xing, Manish Parashar, David J. Foran, Lin Yang

Biostatistics Faculty Publications

The robustness of image features is a very important consideration in quantitative image analysis. The objective of this paper is to investigate the robustness of a range of image texture features using hematoxylin stained breast tissue microarray slides which are assessed while simulating different imaging challenges including out of focus, changes in magnification and variations in illumination, noise, compression, distortion, and rotation. We employed five texture analysis methods and tested them while introducing all of the challenges listed above. The texture features that were evaluated include co-occurrence matrix, center-symmetric auto-correlation, texture feature coding method, local binary pattern, and texton. Due …

Evaluating Retention In Medical Care And Its Impact On The Health Outcomes Of Individuals Living With Human Inmmunodeficiency Virus, Timothy N. Crawford

Theses and Dissertations--Epidemiology and Biostatistics

In the last few years, engagement in medical care among individuals living with HIV has become a major priority among HIV medical providers and public health researchers. Engagement in medical care is an important concept as it involves the process of linking newly diagnosed individuals into medical care and retaining those individuals in care throughout the course of their infection. Although there have been major advances in the management of HIV, like the advent of Highly Active Antiretroviral Therapy, morbidity and mortality due to HIV cannot be fully reduced if the individual does not optimally retain in care. Retention in …

Analysis Of Binary Data Via Spatial-Temporal Autologistic Regression Models, Zilong Wang

Theses and Dissertations--Statistics

Spatial-temporal autologistic models are useful models for binary data that are measured repeatedly over time on a spatial lattice. They can account for effects of potential covariates and spatial-temporal statistical dependence among the data. However, the traditional parametrization of spatial-temporal autologistic model presents difficulties in interpreting model parameters across varying levels of statistical dependence, where its non-negative autocovariates could bias the realizations toward 1. In order to achieve interpretable parameters, a centered spatial-temporal autologistic regression model has been developed. Two efficient statistical inference approaches, expectation-maximization pseudo-likelihood approach (EMPL) and Monte Carlo expectation-maximization likelihood approach (MCEML), have been proposed. Also, Bayesian …