Statistics and Probability Commons^™

Trans-Ancestry Fine Mapping And Molecular Assays Identify Regulatory Variants At The Angptl8 Hdl-C Gwas Locus, Maren E. Cannon, Qing Duan, Ying Wu, Monica Zeynalzadeh, Zheng Xu, Antti J. Kangas, Pasi Soininen, Mika Ala-Korpela, Mete Civelek, Aldons J. Lusis, Johanna Kuusisto, Francis S. Collins, Michael Boehnke, Hua Tang, Markku Laakso, Yun Li, Karen L. Mohlke

Department of Statistics: Faculty Publications

Recent genome-wide association studies (GWAS) have identified variants associated with highdensity lipoprotein cholesterol (HDL-C) located in or near the ANGPTL8 gene. Given the extensive sharing of GWAS loci across populations, we hypothesized that at least one shared variant at this locus affects HDL-C. The HDL-C–associated variants are coincident with expression quantitative trait loci for ANGPTL8 and DOCK6 in subcutaneous adipose tissue; however, only ANGPTL8 expression levels are associated with HDL-C levels. We identified a 400-bp promoter region of ANGPTL8 and enhancer regions within 5 kb that contribute to regulating expression in liver and adipose. To identify variants functionally responsible for …

A Bayes Interpretation Of Stacking For M-Complete And M-Open Settings, Tri Le, Bertrand S. Clarke

Department of Statistics: Faculty Publications

In M-open problems where no true model can be conceptualized, it is common to back off from modeling and merely seek good prediction. Even in M-complete problems, taking a predictive approach can be very useful. Stacking is a model averaging procedure that gives a composite predictor by combining individual predictors from a list of models using weights that optimize a cross validation criterion. We show that the stacking weights also asymptotically minimize a posterior expected loss. Hence we formally provide a Bayesian justification for cross-validation. Often the weights are constrained to be positive and sum to one. For greater generality, …

Optimal Design Of Low-Density Snp Arrays For Genomic Prediction: Algorithm And Applications, Xiao-Lin Wu, Jiaqi Xu, Guofei Feng, George R. Wiggans, Jeremy F. Taylor, Jun He, Changsong Qian, Jiansheng Qiu, Barry Simpson, Jeremy Walker, Stewart Bauck

Department of Statistics: Faculty Publications

Low-density (LD) single nucleotide polymorphism (SNP) arrays provide a cost-effective solution for genomic prediction and selection, but algorithms and computational tools are needed for the optimal design of LD SNP chips. A multiple-objective, local optimization (MOLO) algorithm was developed for design of optimal LD SNP chips that can be imputed accurately to medium-density (MD) or high-density (HD) SNP genotypes for genomic prediction. The objective function facilitates maximization of non-gap map length and system information for the SNP chip, and the latter is computed either as locus-averaged (LASE) or haplotype-averaged Shannon entropy (HASE) and adjusted for uniformity of the SNP distribution. …

Methods To Account For Breed Composition In A Bayesian Gwas Method Which Utilizes Haplotype Clusters, Danielle F. Wilson-Wells

Department of Statistics: Dissertations, Theses, and Student Research

In livestock, prediction of an animal’s genetic merit using genomic information is becoming increasingly common. The models used to make these predictions typically assume that we are sampling from a homogeneous population. However, in both commercial and experimental populations the sire and dam of an individual may be a mixture of different breeds. Haplotype models can capture this population structure.

Two models based on breed specific haplotype clusters where developed to account for differences across multiple breeds. The first model utilizes the breed composition of the individual, while the second utilizes the breed composition from the sire and dam. Haplotype …

Converting Heterogeneous Statistical Tables On The Web To Searchable Databases, David W. Embley, Mukkai S. Krishnamoorthy, George Nagy, Sharad C. Seth

School of Computing: Faculty Publications

Much of the world’s quantitative data reside in scattered web tables. For a meaningful role in Big Data analytics, the facts reported in these tables must be brought into a uniform framework. Based on a formalization of header-indexed tables, we proffer an algorithmic solution to end-to-end table processing for a large class of human-readable tables. The proposed algorithms transform header-indexed tables to a category table format that maps easily to a variety of industry-standard data stores for query processing. The algorithms segment table regions based on the unique indexing of the data region by header paths, classify table cells, and …

How Often Are Antibiotic-Resistant Bacteria Said To “Evolve” In The News?, Nina Singh, Matthew T. Sit, Deanna M. Chung, Ana A. Lopez, Ranil Weerackoon, Pamela J. Yeh

Department of Statistics: Faculty Publications

Media plays an important role in informing the general public about scientific ideas.We examine whether the word “evolve,” sometimes considered controversial by the general public, is frequently used in the popular press. Specifically, we ask how often articles discussing antibiotic resistance use the word “evolve” (or its lexemes) as opposed to alternative terms such as “emerge” or “develop.” We chose the topic of antibiotic resistance because it is a medically important issue; bacterial evolution is a central player in human morbidity and mortality. We focused on the most widely-distributed newspapers written in English in the United States, United Kingdom, Canada, …

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. …

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 …

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 …

Simulations Of A New Response-Adaptive Biased Coin Design, Aleksandra Stein

Department of Statistics: Dissertations, Theses, and Student Research

Modern medical experiments accrue and treat patients--hence obtain treatment response data--throughout a trial. Designs which prospectively plan to modify patient allocation by leveraging accumulating data are response-adaptive randomization (RAR) designs. Many such designs attempt to balance the desire to bias assignment proportions towards a treatment which is performing better against the need to maintain randomization in the face of continued equipoise.

This dissertation consists of simulated investigations into frequentist and ethical properties of an new RAR biased coin design. Chapter 2 proposes a new adaptive design for phase III clinical trials, a modification of the 2001 Bandyopadhyay and Biswas biased …

Beta-Binomial Kriging: A New Approach To Modeling Spatially Correlated Proportions, Aimee Schwab

Department of Statistics: Dissertations, Theses, and Student Research

Spatially correlated count data sets appear often in applied data analysis problems, but there is little consensus in the literature about how best to analyze the data. The two prevailing approaches provide accurate parameter estimates and predictions, at the cost of model interpretability and simplicity. This dissertation will present a new approach to modeling spatially correlated binomial observations: beta-binomial kriging. The model proposed here is a modified form of spatial kriging which assumes the data are generated from a correlated beta-binomial distribution. Given this assumption, the spatial parameters and predicted values can be estimated using simple matrix algebra. Beta-binomial kriging …

A Comparison Of Population-Averaged And Cluster-Specific Approaches In The Context Of Unequal Probabilities Of Selection, Natalie A. Koziol

College of Education and Human Sciences: Dissertations, Theses, and Student Research

Sampling designs of large-scale, federally funded studies are typically complex, involving multiple design features (e.g., clustering, unequal probabilities of selection). Researchers must account for these features in order to obtain unbiased point estimators and make valid inferences about population parameters. Single-level (i.e., population-averaged) and multilevel (i.e., cluster-specific) methods provide two alternatives for modeling clustered data. Single-level methods rely on the use of adjusted variance estimators to account for dependency due to clustering, whereas multilevel methods incorporate the dependency into the specification of the model.

Although the literature comparing single-level and multilevel approaches is vast, comparisons have been limited to the …

A New Approach To Modeling Multivariate Time Series On Multiple Temporal Scales, Tucker Zeleny

Department of Statistics: Dissertations, Theses, and Student Research

In certain situations, observations are collected on a multivariate time series at a certain temporal scale. However, there may also exist underlying time series behavior on a larger temporal scale that is of interest. Often times, identifying the behavior of the data over the course of the larger scale is the key objective. Because this large scale trend is not being directly observed, describing the trends of the data on this scale can be more difficult. To further complicate matters, the observed data on the smaller time scale may be unevenly spaced from one larger scale time point to the …

Global Network Inference From Ego Network Samples: Testing A Simulation Approach, Jeffrey A. Smith

Department of Sociology: Faculty Publications

Network sampling poses a radical idea: that it is possible to measure global network structure without the full population coverage assumed in most network studies. Network sampling is only useful, however, if a researcher can produce accurate global network estimates. This article explores the practicality of making network inference, focusing on the approach introduced in Smith (2012). The method uses sampled ego network data and simulation techniques to make inference about the global features of the true, unknown network. The validity check here includes more difficult scenarios than previous tests, including those that go beyond the initial scope conditions of …

Best Practice Recommendations For Data Screening, Justin A. Desimone, Peter D. Harms, Alice J. Desimone

Department of Management: Faculty Publications

Survey respondents differ in their levels of attention and effort when responding to items. There are a number of methods researchers may use to identify respondents who fail to exert sufficient effort in order to increase the rigor of analysis and enhance the trustworthiness of study results. Screening techniques are organized into three general categories, which differ in impact on survey design and potential respondent awareness. Assumptions and considerations regarding appropriate use of screening techniques are discussed along with descriptions of each technique. The utility of each screening technique is a function of survey design and administration. Each technique has …

Spin Glass Reflection Of The Decoding Transition For Quantum Error Correcting Codes, Alexey Kovalev, Leonid P. Pryadko

Department of Physics and Astronomy: Faculty Publications

We study the decoding transition for quantum error correcting codes with the help of a mapping to random-bond Wegner spin models. Families of quantum low density parity-check (LDPC) codes with a finite decoding threshold lead to both known models (e.g., random bond Ising and random plaquette Z₂ gauge models) as well as unexplored earlier generally non-local disordered spin models with non-trivial phase diagrams. The decoding transition corresponds to a transition from the ordered phase by proliferation of "post-topological" extended defects which generalize the notion of domain walls to non-local spin models. In recently discovered quantum LDPC code families with …

Genomic-Enabled Prediction Of Ordinal Data With Bayesian Logistic Ordinal Regression, Osval A. Montesinos-López, Abelardo Montesinos-López, José Crossa, Juan Burgueño, Kent M. Eskridge

Department of Statistics: Faculty Publications

Most genomic-enabled prediction models developed so far assume that the response variable is continuous and normally distributed. The exception is the probit model, developed for ordered categorical phenotypes. In statistical applications, because of the easy implementation of the Bayesian probit ordinal regression (BPOR) model, Bayesian logistic ordinal regression (BLOR) is implemented rarely in the context of genomic-enabled prediction [sample size (n) is much smaller than the number of parameters (p)]. For this reason, in this paper we propose a BLOR model using the Pólya-Gamma data augmentation approach that produces a Gibbs sampler with similar full conditional distributions of the BPORmodel …

Establishment And Persistence Of Yellow-Flowered Alfalfa No-Till Interseeded Into Crested Wheatgrass Stands, Christopher G. Misar, Lan Xu, Roger N. Gates, Arvid Boe, Patricia S. Johnson, Christopher S. Schauer, John R. Rickertsen, Walter Stroup

Department of Statistics: Faculty Publications

Crested wheatgrass [Agropyron cristatum (L.) Gaertn., A. desertorum

(Fisch. ex Link) Schult., and related taxa] often exists

in near monoculture stands in the northern Great Plains.

Introducing locally adapted yellow-flowered alfalfa [Medicago

sativa L. subsp. falcata (L.) Arcang.] would complement crested

wheatgrass. Our objective was to evaluate effects of seeding

date, clethodim {(E) -2-[1-[[(3-chloro-2-propenyl)oxy]imino]

propyl]-5-[2-(ethylthio)propyl]-3-hydroxy-2-cyclohexen-1-one}

sod suppression, and seeding rate on initial establishment and

stand persistence of Falcata, a predominantly yellow-flowered

alfalfa, no-till interseeded into crested wheatgrass. Research was

initiated in August 2008 at Newcastle, WY; Hettinger, ND;

Fruitdale, SD; and Buffalo, SD. Effects of treatment …

Effect Of Dexamethasone Prodrug On Inflamed Temporomandibular Joints In Juvenile Rats, Mitchell Knudsen, Matthew Bury, Callie Holwegner, Adam L. Reinhardt, Fang Yuan, Yijia Zhang, Peter Giannini, D. B. Marx, Dong Wang, Richard A. Reinhardt

Department of Statistics: Faculty Publications

Introduction: Juvenile idiopathic arthritis (JIA) often causes inflammation of the temporomandibular joint (TMJ) and has been treated with both systemic and intra-articular steroids, with concerns about effects on growing bones. In this study, we evaluated the impact of a macromolecular prodrug of dexamethasone (P-DEX) with inflammation-targeting potential applied systemically or directly to the TMJ.

Methods: Joint inflammation was initiated by injecting two doses of complete Freund’s adjuvant (CFA) at 1-month intervals into the right TMJs of 24 growing Sprague–Dawley male rats (controls on left side). Four additional rats were not manipulated. With the second CFA injection, animals received (1) 5 …

Threshold Models For Genome-Enabled Prediction Of Ordinal Categorical Traits In Plant Breeding, Osval A. Montesinos-López, Abelardo Montesinos-López, Paulino Pérez-Rodríguez, Gustavo De Los Campos, Kent M. Eskridge, José Crossa

Department of Statistics: Faculty Publications

Categorical scores for disease susceptibility or resistance often are recorded in plant breeding. The aim of this study was to introduce genomic models for analyzing ordinal characters and to assess the predictive ability of genomic predictions for ordered categorical phenotypes using a threshold model counterpart of the Genomic Best Linear Unbiased Predictor (i.e., TGBLUP). The threshold model was used to relate a hypothetical underlying scale to the outward categorical response. We present an empirical application where a total of nine models, five without interaction and four with genomic x environment interaction (G·E) and genomic additive x additive x environment interaction …

Measuring Peer Socialization For Adolescent Substance Use:A Comparison Of Perceived And Actual Friends’ Substance Use Effects, Arielle R. Deutsch, Pavel Chernyavskiy, Douglas Steinley, Wendy S. Slutske

Department of Statistics: Faculty Publications

Objective: There has been an increase in the use of social network analysis in studies of peer socialization effects on adolescent substance use. Some researchers argue that social network analyses provide more accurate measures of peer substance use, that the alternate strategy of assessing perceptions of friends’ drug use is biased, and that perceptions of peer use and actual peer use represent different constructs. However, there has been little research directly comparing the two effects, and little is known about the extent to which the measures differ in the magnitude of their influence on adolescent substance use, as well as …

A Copula Based Approach For Design Of Multivariate Random Forests For Drug Sensitivity Prediction, Saad Haider, Raziur Rahman, Souparno Ghosh, Ranadip Pal

Department of Statistics: Faculty Publications

Modeling sensitivity to drugs based on genetic characterizations is a significant challenge in the area of systems medicine. Ensemble based approaches such as Random Forests have been shown to perform well in both individual sensitivity prediction studies and team science based prediction challenges. However, Random Forests generate a deterministic predictive model for each drug based on the genetic characterization of the cell lines and ignores the relationship between different drug sensitivities during model generation. This application motivates the need for generation of multivariate ensemble learning techniques that can increase prediction accuracy and improve variable importance ranking by incorporating the relationships …