Statistical Models Commons^™

Statistical And Machine Learning Methods Evaluated For Incorporating Soil And Weather Into Corn Nitrogen Recommendations, Curtis J. Ransom, Newell R. Kitchen, James J. Camberato, Paul R. Carter, Richard B. Ferguson, Fabián G. Fernández, David W. Franzen, Carrie A. M. Laboski, D. Brenton Myers, Emerson D. Nafziger, John E. Sawyer, John F. Shanahan

John E. Sawyer

Nitrogen (N) fertilizer recommendation tools could be improved for estimating corn (Zea mays L.) N needs by incorporating site-specific soil and weather information. However, an evaluation of analytical methods is needed to determine the success of incorporating this information. The objectives of this research were to evaluate statistical and machine learning (ML) algorithms for utilizing soil and weather information for improving corn N recommendation tools. Eight algorithms [stepwise, ridge regression, least absolute shrinkage and selection operator (Lasso), elastic net regression, principal component regression (PCR), partial least squares regression (PLSR), decision tree, and random forest] were evaluated using a dataset …

Hierarchical Modeling And Differential Expression Analysis For Rna-Seq Experiments With Inbred And Hybrid Genotypes, Andrew Lithio, Dan Nettleton

Dan Nettleton

The performance of inbred and hybrid genotypes is of interest in plant breeding and genetics. High-throughput sequencing of RNA (RNA-seq) has proven to be a useful tool in the study of the molecular genetic responses of inbreds and hybrids to environmental stresses. Commonly used experimental designs and sequencing methods lead to complex data structures that require careful attention in data analysis. We demonstrate an analysis of RNA-seq data from a split-plot design involving drought stress applied to two inbred genotypes and two hybrids formed by crosses between the inbreds. Our generalized linear modeling strategy incorporates random effects for whole-plot experimental …

Nested Hierarchical Functional Data Modeling And Inference For The Analysis Of Functional Plant Phenotypes, Yuhang Xu, Yehua Li, Dan Nettleton

Dan Nettleton

In a plant science Root Image Study, the process of seedling roots bending in response to gravity is recorded using digital cameras, and the bending rates are modeled as functional plant phenotype data. The functional phenotypes are collected from seeds representing a large variety of genotypes and have a three-level nested hierarchical structure, with seeds nested in groups nested in genotypes. The seeds are imaged on different days of the lunar cycle, and an important scientific question is whether there are lunar effects on root bending. We allow the mean function of the bending rate to depend on the lunar …

Root Type-Specific Reprogramming Of Maize Pericycle Transcriptomes By Local High Nitrate Results In Disparate Lateral Root Branching Patterns, Peng Yu, Jutta A. Baldauf, Andrew Lithio, Caroline Marcon, Dan Nettleton, Chunjian Li, Frank Hochholdinger

Dan Nettleton

The adaptability of root system architecture to unevenly distributed mineral nutrients in soil is a key determinant of plant performance. The molecular mechanisms underlying nitrate dependent plasticity of lateral root branching across the different root types of maize are only poorly understood. In this study, detailed morphological and anatomical analyses together with cell type-specific transcriptome profiling experiments combining laser capture microdissection with RNA-seq were performed to unravel the molecular signatures of lateral root formation in primary, seminal, crown, and brace roots of maize (Zea mays) upon local high nitrate stimulation. The four maize root types displayed divergent branching …

Using Random Forests To Estimate Win Probability Before Each Play Of An Nfl Game, Dennis Lock, Dan Nettleton

Dan Nettleton

Before any play of a National Football League (NFL) game, the probability that a given team will win depends on many situational variables (such as time remaining, yards to go for a first down, field position and current score) as well as the relative quality of the two teams as quantified by the Las Vegas point spread. We use a random forest method to combine pre-play variables to estimate Win Probability (WP) before any play of an NFL game. When a subset of NFL play-by-play data for the 12 seasons from 2001 to 2012 is used as a training dataset, …

Stability Of Single-Parent Gene Expression Complementation In Maize Hybrids Upon Water Deficit Stress, Caroline Marcon, Anja Paschold, Waqas Ahmed Malik, Andrew Lithio, Jutta A. Baldauf, Lena Altrogge, Nina Opitz, Christa Lanz, Heiko Schoof, Dan Nettleton, Hans-Peter Piepho, Frank Hochholdinger

Dan Nettleton

Heterosis is the superior performance of F1 hybrids compared with their homozygous, genetically distinct parents. In this study, we monitored the transcriptomic divergence of the maize (Zea mays) inbred lines B73 and Mo17 and their reciprocal F1 hybrid progeny in primary roots under control and water deficit conditions simulated by polyethylene glycol treatment. Single-parent expression (SPE) of genes is an extreme instance of gene expression complementation, in which genes are active in only one of two parents but are expressed in both reciprocal hybrids. In this study, 1,997 genes only expressed in B73 and 2,024 genes …

Genomic Neighborhoods For Arabidopsisretrotransposons: A Role For Targeted Integration In The Distribution Of The Metaviridae, Brooke D. Peterson-Burch, Dan Nettleton, Daniel F. Voytas

Dan Nettleton

Background: Retrotransposons are an abundant component of eukaryotic genomes. The high quality of the Arabidopsis thaliana genome sequence makes it possible to comprehensively characterize retroelement populations and explore factors that contribute to their genomic distribution.

Results: We identified the full complement of A. thaliana long terminal repeat (LTR) retroelements using RetroMap, a software tool that iteratively searches genome sequences for reverse transcriptases and then defines retroelement insertions. Relative ages of full-length elements were estimated by assessing sequence divergence between LTRs: the Pseudoviridae were significantly younger than the Metaviridae. All retroelement insertions were mapped onto the genome sequence and their distribution …

Complementation Contributes To Transcriptome Complexity In Maize (Zea Mays L.) Hybrids Relative To Their Inbred Parents, Anja Paschold, Yi Jia, Caroline Marcon, Steve Lund, Nick B. Larson, Cheng-Ting Yeh, Stephan Ossowski, Christa Lanz, Dan Nettleton, Patrick S. Schnable, Frank Hochholdinger

Dan Nettleton

Typically, F₁-hybrids are more vigorous than their homozygous, genetically distinct parents, a phenomenon known as heterosis. In the present study, the transcriptomes of the reciprocal maize (Zea mays L.) hybrids B73×Mo17 and Mo17×B73 and their parental inbred lines B73 and Mo17 were surveyed in primary roots, early in the developmental manifestation of heterotic root traits. The application of statistical methods and a suitable experimental design established that 34,233 (i.e., 86%) of all high-confidence maize genes were expressed in at least one genotype. Nearly 70% of all expressed genes were differentially expressed between the two parents and 42%–55% …

Estimation And Testing Of Gene Expression Heterosis, Tieming Ji, Peng Liu, Dan Nettleton

Dan Nettleton

Heterosis, also known as the hybrid vigor, occurs when the mean phenotype of hybrid offspring is superior to that of its two inbred parents. The heterosis phenomenon is extensively utilized in agriculture though the molecular basis is still unknown. In an effort to understand phenotypic heterosis at the molecular level, researchers have begun to compare expression levels of thousands of genes between parental inbred lines and their hybrid offspring to search for evidence of gene expression heterosis. Standard statistical approaches for separately analyzing expression data for each gene can produce biased and highly variable estimates and unreliable tests of heterosis. …

Non-Syntenic Genes Drive Rtcs-Dependent Regulation Of The Embryo Transcriptome During Formation Of Seminal Root Primordia In Maize (Zea Mays L.), Huanhuan Tai, Nina Opitz, Andrew Lithio, Xin Lu, Dan Nettleton, Frank Hochholdinger

Dan Nettleton

Seminal roots of maize are pivotal for early seedling establishment. The maize mutant rootless concerning crown and seminal roots (rtcs) is defective in seminal root initiation during embryogenesis. In this study, the transcriptomes of wild-type and rtcs embryos were analyzed by RNA-Seq based on histological results at three stages of seminal root primordia formation. Hierarchical clustering highlighted that samples of each genotype grouped together along development. Determination of their gene activity status revealed hundreds of genes specifically transcribed in wild-type or rtcs embryos, while K-mean clustering revealed changes in gene expression dynamics between wild-type and rtcs during embryo …

Post-Weaning Blood Transcriptomic Differences Between Yorkshire Pigs Divergently Selected For Residual Feed Intake, Haibo Liu, Yet T. Nguyen, Dan Nettleton, Jack C. M. Dekkers, Christopher K. Tuggle

Dan Nettleton

Background: Improving feed efficiency (FE) of pigs by genetic selection is of economic and environmental significance. An increasingly accepted measure of feed efficiency is residual feed intake (RFI). Currently, the molecular mechanisms underlying RFI are largely unknown. Additionally, to incorporate RFI into animal breeding programs, feed intake must be recorded on individual pigs, which is costly and time-consuming. Thus, convenient and predictive biomarkers for RFI that can be measured at an early age are greatly desired. In this study, we aimed to explore whether differences exist in the global gene expression profiles of peripheral blood of 35 to 42 day-old …

Substantial Contribution Of Genetic Variation In The Expression Of Transcription Factors To Phenotypic Variation Revealed By Erd-Gwas, Hung-Ying Lin, Qiang Liu, Xiao Li, Jinliang Yang, Sanzhen Liu, Yinlian Huang, Michael J. Scanlon, Dan Nettleton, Patrick S. Schnable

Dan Nettleton

Background: There are significant limitations in existing methods for the genome-wide identification of genes whose expression patterns affect traits.

Results: The transcriptomes of five tissues from 27 genetically diverse maize inbred lines were deeply sequenced to identify genes exhibiting high and low levels of expression variation across tissues or genotypes. Transcription factors are enriched among genes with the most variation in expression across tissues, as well as among genes with higher-than-median levels of variation in expression across genotypes. In contrast, transcription factors are depleted among genes whose expression is either highly stable or highly variable across genotypes. We developed a …

Empirical Bayes Analysis Of Rna-Seq Data For Detection Of Gene Expression Heterosis, Jarad Niemi, Eric Mittman, Will Landau, Dan Nettleton

Dan Nettleton

An important type of heterosis, known as hybrid vigor, refers to the enhancements in the phenotype of hybrid progeny relative to their inbred parents. Although hybrid vigor is extensively utilized in agriculture, its molecular basis is still largely unknown. In an effort to understand phenotypic heterosis at the molecular level, researchers are measuring transcript abundance levels of thousands of genes in parental inbred lines and their hybrid offspring using RNA sequencing (RNA-seq) technology. The resulting data allow researchers to search for evidence of gene expression heterosis as one potential molecular mechanism underlying heterosis of agriculturally important traits. The null hypotheses …

A Diallel Analysis Of A Maize Donor Population Response To In Vivo Maternal Haploid Induction I: Inducibility, Gerald N. De La Fuente, Ursula K. Frei, Benjamin Trampe, Daniel Nettleton, Wei Zhang, Thomas Lubberstedt

Dan Nettleton

The maize in vivo maternal doubled haploid (DH) system is an important tool used by maize breeders and geneticists around the world. The ability to rapidly produce DH lines of maize for breeding allows breeders to quickly respond to new selection criteria based on the ever changing biotic and abiotic stresses that maize is subjected to across its growing area. There are two important steps in the generation of DH lines using the in vivo maternal DH system: 1) the production and identification of haploid progeny, and 2) the doubling of genomes to create fertile, diploid inbred lines that can …

Combining Survey And Non-Survey Data For Improved Sub-Area Prediction Using A Multi-Level Model, Jae Kwang Kim, Zhonglei Wang, Zhengyuan Zhu, Nathan B. Cruze

Zhengyuan Zhu

Combining information from different sources is an important practical problem in survey sampling. Using a hierarchical area-level model, we establish a framework to integrate auxiliary information to improve state-level area estimates. The best predictors are obtained by the conditional expectations of latent variables given observations, and an estimate of the mean squared prediction error is discussed. Sponsored by the National Agricultural Statistics Service of the US Department of Agriculture, the proposed model is applied to the planted crop acreage estimation problem by combining information from three sources, including the June Area Survey obtained by a probability-based sampling of lands, administrative …

Inferring Processes Of Coevolutionary Diversification In A Community Of Panamanian Strangler Figs And Associated Pollinating Wasps, Jordan D. Satler, Edward Allen Herre, K. Charlotte Jandér, Deren A. R. Eaton, Carlos A. Machado, Tracy A. Heath, John D. Nason

Tracy Heath

The fig and pollinator wasp obligate mutualism is diverse (~750 described species), ecologically important, and ancient (~80-90 Ma), providing model systems for generating and testing many questions in evolution and ecology. Once thought to be a prime example of strict one-to-one cospeciation, current thinking suggests that genera of pollinator wasps coevolve with corresponding subsections of figs, but the degree to which cospeciation or other processes contributes to the association at finer scales is unclear. Here we use genome-wide sequence data from a community of Panamanian strangler figs (Ficus subgenus Urostigma, section Americana) and associated fig wasp pollinators …

Inversion Copulas From Nonlinear State Space Models With An Application To Inflation Forecasting, Michael S. Smith, Worapree Ole Maneesoonthorn

Michael Stanley Smith

The Fossilized Birth-Death Model For The Analysis Of Stratigraphic Range Data Under Different Speciation Modes, Tanja Stadler, Alexandra Gavryushkina, Rachel C. M. Warnock, Alexei J. Drummond, Tracy A. Heath

Tracy Heath

A birth-death-sampling model gives rise to phylogenetic trees with samples from the past and the present. Interpreting “birth” as branching speciation, “death” as extinction, and “sampling” as fossil preservation and recovery, this model – also referred to as the fossilized birth-death (FBD) model – gives rise to phylogenetic trees on extant and fossil samples. The model has been mathematically analyzed and successfully applied to a range of datasets on different taxonomic levels, such as penguins, plants, and insects. However, the current mathematical treatment of this model does not allow for a group of temporally distinct fossil specimens to be assigned …

Implicit Copulas From Bayesian Regularized Regression Smoothers, Nadja Klein, Michael S. Smith

Michael Stanley Smith

Variational Bayes Estimation Of Discrete-Margined Copula Models With Application To Ime Series, Ruben Loaiza-Maya, Michael S. Smith

Michael Stanley Smith

Implementing Propensity Score Matching With Network Data: The Effect Of Gatt On Bilateral Trade, Luca De Benedictis, Bruno Arpino, Alessandra Mattei

Luca De Benedictis

Shining A Light On A University Special Collection With Data Visualization, Lisa Deluca, Katie M. Wissel

Kathryn Wissel, MBA, MI

Penalized Nonparametric Scalar-On-Function Regression Via Principal Coordinates, Philip T. Reiss, David L. Miller, Pei-Shien Wu, Wen-Yu Hua

Philip T. Reiss

Addition To Pglr Chap 6, Joseph M. Hilbe

Joseph M Hilbe

Addition to Chapter 6 in Practical Guide to Logistic Regression. Added section on Bayesian logistic regression using Stata.

A Gene-Based Association Method For Mapping Traits Using Reference Transcriptome Data, Eric R. Gamazon, Heather Wheeler, Kaanan P. Shah, Sahar V. Mozaffari, Keston Aquino-Michaels, Robert J. Carroll, Anne E. Eyler, Joshua C. Denny, Dan L. Nicolae, Nancy J. Cox, Hae Kyung Im

Heather Wheeler

Genome-wide association studies (GWAS) have identified thousands of variants robustly associated with complex traits. However, the biological mechanisms underlying these associations are, in general, not well understood. We propose a gene-based association method called PrediXcan that directly tests the molecular mechanisms through which genetic variation affects phenotype. The approach estimates the component of gene expression determined by an individual’s genetic profile and correlates ‘imputed’ gene expression with the phenotype under investigation to identify genes involved in the etiology of the phenotype. Genetically regulated gene expression is estimated using whole-genome tissue-dependent prediction models trained with reference transcriptome data sets. PrediXcan enjoys …

Social Learning And Adoption Of New Behavior In A Virtual Agent Society, Benjamin D. Nye, Barry G. Silverman

Barry G Silverman

Social learning and adoption of new behavior govern the rise of a variety of behaviors: from actions as mundane as dance steps to those as dangerous as new ways to make IED detonators. However, agents in immersive virtual environments lack the ability to realistically simulate the spread of new behavior. To address this gap, a cognitive model was designed that represents the well-known socio-cognitive factors of attention, social influence, and motivation that influence learning and the adoption of a new behavior. To explore the effectiveness of this model, simulations modeled the spread of two competing memes in Hamariyah, an archetypal …

Social Learning And Adoption Of New Behavior In A Virtual Agent Society, Benjamin D. Nye, Barry G. Silverman

Barry G Silverman

Social learning and adoption of new behavior govern the rise of a variety of behaviors: from actions as mundane as dance steps to those as dangerous as new ways to make IED detonators. However, agents in immersive virtual environments lack the ability to realistically simulate the spread of new behavior. To address this gap, a cognitive model was designed that represents the well-known socio-cognitive factors of attention, social influence, and motivation that influence learning and the adoption of a new behavior. To explore the effectiveness of this model, simulations modeled the spread of two competing memes in Hamariyah, an archetypal …

Predicting Financial Distress: A Comparison Of Survival Analysis And Decision Tree Techniques, Adrian Gepp, Kuldeep Kumar

Adrian Gepp

Financial distress and then the consequent failure of a business is usually an extremely costly and disruptive event. Statistical financial distress prediction models attempt to predict whether a business will experience financial distress in the future. Discriminant analysis and logistic regression have been the most popular approaches, but there is also a large number of alternative cutting - edge data mining techniques that can be used. In this paper, a semi-parametric Cox survival analysis model and non-parametric CART decision trees have been applied to financial distress prediction and compared with each other as well as the most popular approaches. This …

Online Variational Bayes Inference For High-Dimensional Correlated Data, Sylvie T. Kabisa, Jeffrey S. Morris, David Dunson

Jeffrey S. Morris

High-dimensional data with hundreds of thousands of observations are becoming commonplace in many disciplines. The analysis of such data poses many computational challenges, especially when the observations are correlated over time and/or across space. In this paper we propose exible hierarchical regression models for analyzing such data that accommodate serial and/or spatial correlation. We address the computational challenges involved in fitting these models by adopting an approximate inference framework. We develop an online variational Bayes algorithm that works by incrementally reading the data into memory one portion at a time. The performance of the method is assessed through simulation studies. …

Functional Car Models For Spatially Correlated Functional Datasets, Lin Zhang, Veerabhadran Baladandayuthapani, Hongxiao Zhu, Keith A. Baggerly, Tadeusz Majewski, Bogdan Czerniak, Jeffrey S. Morris

Jeffrey S. Morris

We develop a functional conditional autoregressive (CAR) model for spatially correlated data for which functions are collected on areal units of a lattice. Our model performs functional response regression while accounting for spatial correlations with potentially nonseparable and nonstationary covariance structure, in both the space and functional domains. We show theoretically that our construction leads to a CAR model at each functional location, with spatial covariance parameters varying and borrowing strength across the functional domain. Using basis transformation strategies, the nonseparable spatial-functional model is computationally scalable to enormous functional datasets, generalizable to different basis functions, and can be used on …