Statistics and Probability Commons^™

Systematic Evaluation Of The Impact Of Chip-Seq Read Designs On Genome Coverage, Peak Identification, And Allele-Specific Binding Detection, Qi Zhang, Xin Zeng, Sam Younkin, Trupti Kawli, Michael P. Snyder, Sündüz Kele

Department of Statistics: Faculty Publications

Background: Chromatin immunoprecipitation followed by sequencing (ChIP-seq) experiments revolutionized genome-wide profiling of transcription factors and histone modifications. Although maturing sequencing technologies allow these experiments to be carried out with short (36–50 bps), long (75–100 bps), single-end, or paired-end reads, the impact of these read parameters on the downstream data analysis are not well understood. In this paper, we evaluate the effects of different read parameters on genome sequence alignment, coverage of different classes of genomic features, peak identification, and allele-specific binding detection.

Results: We generated 101 bps paired-end ChIP-seq data for many transcription factors from human GM12878 and MCF7 cell …

The Impact Of Hair Coat Color On Longevity Of Holstein Cows In The Tropics, C. N. Lee, K. S. Baek, A. Parkhurst

Department of Statistics: Faculty Publications

Background: Over two decades of observations in the field in South East Asia and Hawai‘i suggest that majority of the commercial dairy herds are of black hair coat. Hence a simple study to determine the accuracy of the observation was conducted with two large dairy herds in Hawaii in the mid-1990s.

Methods: A retrospective study on longevity of Holstein cattle in the tropics was conducted using DairyComp-305 lactation information coupled with phenotypic evaluation of hair coat color in two large dairy farms. Cows were classified into 3 groups: a) black (B, >90%); b) black/white (BW, 50:50) and c) white (W, …

Sex-Specific Hippocampal 5-Hydroxymethylcytosine Is Disrupted In Response To Acute Stress, Ligia A. Papale, Sisi Li, Andy Madrid, Qi Zhang, Li Chen, Pankaj Chopra, Peng Jin, Sunduz Keles, Reid S. Alisch

Department of Statistics: Faculty Publications

Environmental stress is among the most important contributors to increased susceptibility to develop psychiatric disorders. While it is well known that acute environmental stress alters gene expression, the molecular mechanisms underlying these changes remain largely unknown. 5-hydroxymethylcytosine (5hmC) is a novel environmentally sensitive epigenetic modification that is highly enriched in neurons and is associated with active neuronal transcription. Recently,we reported a genome-wide disruption of hippocampal 5hmCin male mice following acute stress that was correlated to altered transcript levels of genes in known stress related pathways. Since sex-specific endocrine mechanisms respond to environmental stimulus by altering the neuronal epigenome, we examined …

A Compendium Of Chromatin Contact Maps Reveals Spatially Active Regions In The Human Genome, Anthony D. Schmitt, Ming Hu, Inkyung Jung, Zheng Xu, Yunjiang Qiu, Catherine L. Tan, Yun Li, Shin Lin, Yiing Lin, Cathy L. Barr, Bing Ren

Department of Statistics: Faculty Publications

The three-dimensional configuration of DNA is integral to all nuclear processes in eukaryotes, yet our knowledge of the chromosome architecture is still limited. Genome-wide chromosome conformation capture studies have uncovered features of chromatin organization in cultured cells, but genome architecture in human tissues has yet to be explored. Here, we report the most comprehensive survey to date of chromatin organization in human tissues. Through integrative analysis of chromatin contact maps in 21 primary human tissues and cell types, we find topologically associating domains highly conserved in different tissues. We also discover genomic regions that exhibit unusually high levels of local …

Hiview: An Integrative Genome Browser To Leverage Hi‑C Results For The Interpretation Of Gwas Variants, Zheng Xu, Guosheng Zhang, Qing Duan, Shengjie Chai, Baqun Zhang, Cong Wu, Fulai Jin, Feng Yue, Yun Li, Ming Hu

Department of Statistics: Faculty Publications

Genome-wide association studies (GWAS) have identified thousands of genetic variants associated with complex traits and diseases. However, most of them are located in the non-protein coding regions, and therefore it is challenging to hypothesize the functions of these non-coding GWAS variants. Recent large efforts such as the ENCODE and Roadmap Epigenomics projects have predicted a large number of regulatory elements. However, the target genes of these regulatory elements remain largely unknown. Chromatin conformation capture based technologies such as Hi-C can directly measure the chromatin interactions and have generated an increasingly comprehensive catalog of the interactome between the distal regulatory elements …

A Bayesian Gwas Method Utilizing Haplotype Clusters For A Composite Breed Population, Danielle F. Wilson-Wells, Stephen D. Kachman

Department of Statistics: Faculty Publications

Commercial beef cattle are often composites of multiple breeds. Current methods used to produce genomic predictors are based on the underlying assumption of animals being sampled from a homogeneous population. As a result, the predictors can perform poorly when used to predict the relative genetic merit of animals whose breed composition are different. In part, this is due to the changes in linkage disequilibrium between the markers and the quantitative trait loci as we move from one breed to the next. An alternative model based on breed specific haplotype clusters was developed to allow for differences in linkage disequilibrium across …

Design Of Probabilistic Random Forests With Applications To Anticancer Drug Sensitivity Prediction- 2016, Raziur Rahman, Saad Haider, Souparno Ghosh, Ranadip Pal

Department of Statistics: Faculty Publications

Random forests consisting of an ensemble of regression trees with equal weights are frequently used for design of predictive models. In this article, we consider an extension of the methodology by representing the regression trees in the form of probabilistic trees and analyzing the nature of heteroscedasticity. The probabilistic tree representation allows for analytical computation of confidence intervals (CIs), and the tree weight optimization is expected to provide stricter CIs with comparable performance in mean error. We approached the ensemble of probabilistic trees’ prediction from the perspectives of a mixture distribution and as a weighted sum of correlated random variables. …

A Descriptive Study Of The Effect Of Payer Source On Multiple Longitudinal Outcome Measures Within The Tbi Model Systems National Database Using Longitudinal Hlm Analyses, Melissa Carole Hofmann

Electronic Theses and Dissertations

Using longitudinal data from the TBIMS ND, this study utilized a longitudinal hierarchical linear modeling approach to describe the effect of primary payer source on individual level change in outcomes including the FIM and DRS. To facilitate the use of parametric statistics, Rasch-transformed FIM and DRS scores were utilized; thus approaching an interval level of measurement. The FIM was separated into 3 separate cognitive, mobility, and self-care subscales. In this way, rehabilitation professionals including speech, physical, and occupational therapists for this TBI sample could reference results to inform current clinical practice.

Results indicated that FIM and DRS trajectories were best …

A Comparison Between Propensity Score Matching, Weighting, And Stratification In Multiple Treatment Groups: A Simulation Study, Priyalatha Govindasamy

Electronic Theses and Dissertations

The application of propensity score techniques (matching, stratification, and weighting) with multiple treatment levels are similar to those used in binary groups. However, given that the application of propensity scores in multiple treatment groups is new, factors affecting the performance of matching, stratification, and weighting in multiple treatment groups are less explored. Therefore, this study was conducted to determine the performance of different propensity score techniques with multiple treatment groups under various circumstances. Specifically, the study focused on examining how the three propensity score corrective techniques perform in estimating treatment effects under (1) overt and (2) hidden types of selection …

Clme: An R Package For Linear Mixed Effects Models Under Inequality Constraints, Casey M. Jelsema, Shyamal D. Peddada

Faculty & Staff Scholarship

In many applications researchers are typically interested in testing for inequality constraints in the context of linear fixed effects and mixed effects models. Although there exists a large body of literature for performing statistical inference under inequality constraints, user friendly statistical software implementing such methods is lacking, especially in the context of linear fixed and mixed effects models. In this article we introduce CLME, a package in the R language that can be used for testing a broad collection of inequality constraints. It uses residual bootstrap based methodology which is reasonably robust to non-normality as well as heteroscedasticity. The package …

Enscat: Clustering Of Categorical Data Via Ensembling, Bertrand S. Clarke, Saeid Amiri, Jennifer L. Clarke

Department of Statistics: Faculty Publications

Background: Clustering is a widely used collection of unsupervised learning techniques for identifying natural classes within a data set. It is often used in bioinformatics to infer population substructure. Genomic data are often categorical and high dimensional, e.g., long sequences of nucleotides. This makes inference challenging: The distance metric is often not well-defined on categorical data; running time for computations using high dimensional data can be considerable; and the Curse of Dimensionality often impedes the interpretation of the results. Up to the present, however, the literature and software addressing clustering for categorical data has not yet led to a standard …

Genomic Bayesian Prediction Model For Count Data With Genotype X Environment Interaction, Abelardo Montesinos-López, Osval A. Montesinos-López, José Crossa, Juan Burgueño, Kent M. Eskridge, Esteban Falconi-Castillo, Xinyao He, Pawan Singh, Karen Cichy

Department of Statistics: Faculty Publications

Genomic tools allow the study of the whole genome, and facilitate the study of genotype-environment combinations and their relationship with phenotype. However, most genomic prediction models developed so far are appropriate for Gaussian phenotypes. For this reason, appropriate genomic prediction models are needed for count data, since the conventional regression models used on count data with a large sample size (n_T ) and a small number of parameters (p) cannot be used for genomic-enabled prediction where the number of parameters (p) is larger than the sample size (n_T ). Here, we propose a Bayesian mixed-negative binomial (BMNB) genomic …

A Genomic Bayesian Multi-Trait And Multi-Environment Model, Osval A. Montesinos-López, Abelardo Montesinos-López, José Crossa, Fernando Toledo, Oscar Pérez-Hernández, Kent M. Eskridge, Jessica Rutkoski

Department of Statistics: Faculty Publications

When information on multiple genotypes evaluated in multiple environments is recorded, a multi-environment single trait model for assessing genotype × environment interaction (G×E) is usually employed. Comprehensive models that simultaneously take into account the correlated traits and trait × genotype × environment interaction (T×G×E) are lacking. In this research, we propose a Bayesian model for analyzing multiple traits and multiple environments for whole-genome prediction (WGP) model. For this model, we used Half-𝑡 priors on each standard deviation term and uniform priors on each correlation of the covariance matrix. These priors were not informative and led to posterior inferences that were …

Student Fact Book, Fall 2016 - Fortieth Annual Edition, Office Of Student Information Systems, Wright State University

Wright State University Student Fact Books

The student fact book has general demographic information on all students enrolled at Wright State University for Fall Semester, 2016.

A Comparison Of Latent Class Analysis And The Mixture Rasch Model: A Cross-Cultural Comparison Of 8th Grade Mathematics Achievement In The Fourth International Mathematics And Science Study (Timss-2011), Turker Toker

Electronic Theses and Dissertations

This study provides a comparison of the results of latent class analysis (LCA) and mixture Rasch model (MRM) analysis using data from the Trends in International Mathematics and Science Study - 2011 (TIMSS-2011) with a focus on the 8th-grade mathematics section. The research study focuses on the comparison of LCA with Mplus version 7.31 and MRM with WinMira 2011 to determine if results obtained differ when the assumed psychometric model differs. Also, a log-linear analysis was conducted to understand the interactions between latent classes identified by LCA and MRM. The data set used in the study was from four diverse …

Socioecological Factors Influencing Women's Hiv Risk In The United States: Qualitative Findings From The Women's Hiv Seroincidence Study (Hptn 064)., Paula M Frew, Kimberly Parker, Linda Vo, Danielle Haley, Ann O'Leary, Dazon Dixon Diallo, Carol E Golin, Irene Kuo, Lydia Soto-Torres, Jing Wang, Adaora A Adimora, Laura A Randall, Carlos Del Rio, Sally Hodder, Hiv Prevention Trials Network 064 (Htpn) Study Team.

Epidemiology Faculty Publications

BACKGROUND: We sought to understand the multilevel syndemic factors that are concurrently contributing to the HIV epidemic among women living in the US. We specifically examined community, network, dyadic, and individual factors to explain HIV vulnerability within a socioecological framework.

METHODS: We gathered qualitative data (120 interviews and 31 focus groups) from a subset of women ages 18-44 years (N = 2,099) enrolled in the HPTN 064 HIV seroincidence estimation study across 10 US communities. We analyzed data from 4 diverse locations: Atlanta, New York City (the Bronx), Raleigh, and Washington, DC. Data were thematically coded using grounded theory methodology. …

What's In A Name? A Critical Review Of Definitions Of Quantitative Literacy, Numeracy, And Quantitative Reasoning, Gizem Karaali, Edwin H Villafane Hernandez '18, Jeremy Alexander Taylor '18

Pomona Faculty Publications and Research

This article aims to bring together various threads in the eclectic literature that make up the scholarship around the theme of Quantitative Literacy. In investigating the meanings of terms like "quantitative literacy," "quantitative reasoning," and "numeracy," we seek common ground, common themes, common goals and aspirations of a community of practitioners. A decade ago, these terms were relatively new in the public sphere; today policy makers and accrediting agencies are routinely inserting them into general education conversations. Having good, representative, and perhaps even compact and easily digestible definitions of these terms might come in handy in public relations contexts as …

Species Discovery And Diversity In Lobocriconema (Criconematidae: Nematoda) And Related Plant-Parasitic Nematodes From North American Ecoregions, Tom Powers, Ernest C. Bernard, T. Harris, Robert Higgins, M. Olson, S. Olson, M. Lodema, Julianne N. Matczyszyn, P. Mullin, L. Sutton, K.S Powers

Department of Statistics: Faculty Publications

There are many nematode species that, following formal description, are seldom mentioned again in the scientific literature. Lobocriconema thornei and L. incrassatum are two such species, described from North American forests, respectively 37 and 49 years ago. In the course of a 3-year nematode biodiversity survey of North American ecoregions, specimens resembling Lobocriconema species appeared in soil samples from both grassland and forested sites. Using a combination of molecular and morphological analyses, together with a set of species delimitation approaches, we have expanded the known range of these species, added to the species descriptions, and discovered a related group of …

Improving Hiv Surveillance Data For Public Health Action In Washington, Dc: A Novel Multiorganizational Data-Sharing Method, Joanne Ocampo, J. C. Smart, Adam Allston, Reshma Bhattacharjee, Sahithi Boggavarapu, Amanda D. Castel, +13 More

GW Biostatistics Center

Background: The National HIV/AIDS Strategy calls for active surveillance programs for human immunodeficiency virus (HIV) to more accurately measure access to and retention in care across the HIV care continuum for persons living with HIV within their jurisdictions and to identify persons who may need public health services. However, traditional public health surveillance methods face substantial technological and privacy-related barriers to data sharing.

Objective: This study developed a novel data-sharing approach to improve the timeliness and quality of HIV surveillance data in three jurisdictions where persons may often travel across the borders of the District of Columbia, Maryland, and Virginia. …

Skin Collagen Fluorophore Lw-1 Versus Skin Fluorescence As Markers For The Long-Term Progression Of Subclinical Macrovascular Disease In Type 1 Diabetes., David R Sell, Wanjie Sun, Xiaoyu Gao, Christopher Strauch, John M. Lachin, Patricia A Cleary, Saul Genuth, Ddit/Edic Research Group, Vincent M Monnier

GW Biostatistics Center

BACKGROUND: Skin collagen Long Wavelength Fluorescence (LWF) is widely used as a surrogate marker for accumulation of advanced glycation end-products. Here we determined the relationship of LWF with glycemia, skin fluorescence, and the progression of complications during EDIC in 216 participants from the DCCT.

METHODS: LW-1 and collagen-linked fluorescence (CLF) were measured by either High Performance Liquid Chromatography (HPLC) with fluorescence detection (LW-1) or total fluorescence of collagenase digests (CLF) in insoluble skin collagen extracted from skin biopsies obtained at the end of the DCCT (1993). Skin intrinsic fluorescence (SIF) was noninvasively measured on volar forearm skin at EDIC year …