Statistical Methodology Commons^™

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 …

Comparative Gene Expression Profiles Between Heterotic And Non-Heterotic Hybrids Of Tetraploid Medicago Sativa, Xuehui Li, Yanling Wei, Dan Nettleton, E. Charles Brummer

Dan Nettleton

Background: Heterosis, the superior performance of hybrids relative to parents, has clear agricultural value, but its genetic control is unknown. Our objective was to test the hypotheses that hybrids expressing heterosis for biomass yield would show more gene expression levels that were different from midparental values and outside the range of parental values than hybrids that do not exhibit heterosis.

Results: We tested these hypotheses in three Medicago sativa (alfalfa) genotypes and their three hybrids, two of which expressed heterosis for biomass yield and a third that did not, using Affymetrix M. truncatula GeneChip arrays. Alfalfa hybridized to approximately 47% …

Extreme‐Phenotype Genome‐Wide Association Study (Xp‐Gwas): A Method For Identifying Trait‐Associated Variants By Sequencing Pools Of Individuals Selected From A Diversity Panel, Jinliang Yang, Haiying Jiang, Cheng-Ting Yeh, Jianming Yu, Jeffrey A. Jeddeloh, Dan Nettleton, Patrick S. Schnable

Dan Nettleton

Although approaches for performing genome‐wide association studies (GWAS) are well developed, conventional GWAS requires high‐density genotyping of large numbers of individuals from a diversity panel. Here we report a method for performing GWAS that does not require genotyping of large numbers of individuals. Instead XP‐GWAS (extreme‐phenotype GWAS) relies on genotyping pools of individuals from a diversity panel that have extreme phenotypes. This analysis measures allele frequencies in the extreme pools, enabling discovery of associations between genetic variants and traits of interest. This method was evaluated in maize (Zea mays) using the well‐characterized kernel row number trait, which was …

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. …

Parallel Genome-Wide Expression Profiling Of Host And Pathogen During Soybean Cyst Nematode Infection Of Soybean, Nagabhushana Ithal, Justin Recknor, Dan Nettleton, Leonard Hearne, Tom Maier, Thomas J. Baum, Melissa G. Mitchum

Dan Nettleton

Global analysis of gene expression changes in soybean (Glycine max) and Heterodera glycines (soybean cyst nematode [SCN]) during the course of infection in a compatible interaction was performed using the Affymetrix GeneChip soybean genome array. Among 35,611 soybean transcripts monitored, we identified 429 genes that showed statistically significant differential expression between uninfected and nematode-infected root tissues. These included genes encoding enzymes involved in primary metabolism; biosynthesis of phenolic compounds, lignin, and flavonoids; genes related to stress and defense responses; cell wall modification; cellular signaling; and transcriptional regulation. Among 7,431 SCN transcripts monitored, 1,850 genes showed statistically significant differential …

Sequence Mining And Transcript Profiling To Explore Cyst Nematode Parasitism, Axel A. Elling, Makedonka Mitreva, Xiaowu Gai, John Martin, Justin Recknor, Eric L. Davis, Richard S. Hussey, Dan Nettleton, James P. Mccarter, Thomas J. Baum

Dan Nettleton

Background: Cyst nematodes are devastating plant parasites that become sedentary within plant roots and induce the transformation of normal plant cells into elaborate feeding cells with the help of secreted effectors, the parasitism proteins. These proteins are the translation products of parasitism genes and are secreted molecular tools that allow cyst nematodes to infect plants.

Results: We present here the expression patterns of all previously described parasitism genes of the soybean cyst nematode, Heterodera glycines, in all major life stages except the adult male. These insights were gained by analyzing our gene expression dataset from experiments using the Affymetrix Soybean …

Developmental Transcript Profiling Of Cyst Nematode Feeding Cells In Soybean Roots, Nagabhushana Ithal, Justin Recknor, Dan Nettleton, Tom Maier, Thomas J. Baum, Melissa G. Mitchum

Dan Nettleton

Cyst nematodes of the genus Heterodera are obligate, sedentary endoparasites that have developed highly evolved relationships with specific host plant species. Successful parasitism involves significant physiological and morphological changes to plant root cells for the formation of specialized feeding cells called syncytia. To better understand the molecular mechanisms that lead to the development of nematode feeding cells, transcript profiling was conducted on developing syncytia induced by the soybean cyst nematode Heterodera glycines in soybean roots by coupling laser capture microdissection with high-density oligonucleotide microarray analysis. This approach has identified pathways that may play intrinsic roles in syncytium induction, formation, and …

Comparison Of Transcript Profiles In Wild-Type And O2 Maize Endosperm In Different Genetic Backgrounds, Hongwu Jia, Dan Nettleton, Joan M. Peterson, Gricelda Vasquez-Carrillo, Jean-Luc Jannink, M. Paul Scott

Dan Nettleton

Mutations in the Opaque2 (O2) gene of maize (Zea mays L.) improve the nutritional value of maize by reducing the level of zeins in the kernel. The phenotype of o2 grain is controlled by many modifier genes and is therefore strongly dependent on genetic background. We propose two hypotheses to explain differences in phenotypic severity in different genetic backgrounds: (i) Specific genes are differentially (o2 vs. wild-type) expressed only in certain genotypes, and (ii) A set of genes are differentially expressed in all backgrounds, but the degree of differential expression differs in different backgrounds. To determine …

Arca Controls Metabolism, Chemotaxis, And Motility Contributing To The Pathogenicity Of Avian Pathogenic Escherichia Coli, Fengwei Jiang, Chunxia An, Yinli Bao, Xuefeng Zhao, Robert L. Jernigan, Andrew Lithio, Dan Nettleton, Ling Li, Eve S. Wurtele, Lisa K. Nolan, Chengping Lu, Ganwu Li

Dan Nettleton

Avian pathogenic Escherichia coli (APEC) strains cause one of the three most significant infectious diseases in the poultry industry and are also potential food-borne pathogens threating human health. In this study, we showed that ArcA (aerobic respiratory control), a global regulator important for E. coli's adaptation from anaerobic to aerobic conditions and control of that bacterium's enzymatic defenses against reactive oxygen species (ROS), is involved in the virulence of APEC. Deletion of arcA significantly attenuates the virulence of APEC in the duck model. Transcriptome sequencing (RNA-Seq) analyses comparing the APEC wild type and the arcA mutant indicate that ArcA regulates …

A Clade-Specific Arabidopsis Gene Connects Primary Metabolism And Senescence, Dallas C. Jones, Wenguang Zheng, Sheng Huang, Chuanlong Du, Xuefeng Zhao, Ragothaman M. Yennamalli, Taner Z. Sen, Dan Nettleton, Eve S. Wurtele, Ling Li

Dan Nettleton

Nearly immobile, plants have evolved new components to be able to respond to changing environments. One example is Qua Quine Starch (QQS, AT3G30720), an Arabidopsis thaliana-specific orphan gene that integrates primary metabolism with adaptation to environment changes. SAQR (Senescence-Associated and QQS-Related, AT1G64360), is unique to a clade within the family Brassicaceae; as such, the gene may have arisen about 20 million years ago. SAQR is up-regulated in QQS RNAi mutant and in the apx1 mutant under light-induced oxidative stress. SAQR plays a role in carbon allocation: overexpression lines of SAQR have significantly decreased starch content; …

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

Michael Stanley Smith

Multivariate Spectral Analysis Of Crism Data To Characterize The Composition Of Mawrth Vallis, Melissa Luna

Melissa Luna

No abstract provided.

Time Series Copulas For Heteroskedastic Data, Ruben Loaiza-Maya, Michael S. Smith, Worapree Maneesoonthorn

Michael Stanley Smith

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

Methods For Scalar-On-Function Regression, Philip T. Reiss, Jeff Goldsmith, Han Lin Shang, R. Todd Ogden

Philip T. Reiss

Propensity Score Analysis With Matching Weights, Liang Li

Liang Li

The propensity score analysis is one of the most widely used methods for studying the causal treatment effect in observational studies. This paper studies treatment effect estimation with the method of matching weights. This method resembles propensity score matching but offers a number of new features including efficient estimation, rigorous variance calculation, simple asymptotics, statistical tests of balance, clearly identified target population with optimal sampling property, and no need for choosing matching algorithm and caliper size. In addition, we propose the mirror histogram as a useful tool for graphically displaying balance. The method also shares some features of the inverse …

Evaluation Of Progress Towards The Unaids 90-90-90 Hiv Care Cascade: A Description Of Statistical Methods Used In An Interim Analysis Of The Intervention Communities In The Search Study, Laura Balzer, Joshua Schwab, Mark J. Van Der Laan, Maya L. Petersen

Laura B. Balzer

WHO guidelines call for universal antiretroviral treatment, and UNAIDS has set a global target to virally suppress most HIV-positive individuals. Accurate estimates of population-level coverage at each step of the HIV care cascade (testing, treatment, and viral suppression) are needed to assess the effectiveness of "test and treat" strategies implemented to achieve this goal. The data available to inform such estimates, however, are susceptible to informative missingness: the number of HIV-positive individuals in a population is unknown; individuals tested for HIV may not be representative of those whom a testing intervention fails to reach, and HIV-positive individuals with a viral …

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

Philip T. Reiss

Auxiliary Likelihood-Based Approximate Bayesian Computation In State Space Models, Worapree Ole Maneesoonthorn

Worapree Ole Maneesoonthorn

Shrinkage Estimation For Multivariate Hidden Markov Mixture Models, Mark Fiecas, Jürgen Franke, Rainer Von Sachs, Joseph Tadjuidje

Mark Fiecas

Modeling The Evolution Of Dynamic Brain Processes During An Associative Learning Experiment, Mark Fiecas, Hernando Ombao

Mark Fiecas

Flexible Penalized Regression For Functional Data...And Other Complex Data Objects, Philip T. Reiss

Philip T. Reiss

No abstract provided.

An Omnibus Nonparametric Test Of Equality In Distribution For Unknown Functions, Alexander Luedtke, Marco Carone, Mark Van Der Laan

Alex Luedtke

We present a novel family of nonparametric omnibus tests of the hypothesis that two unknown but estimable functions are equal in distribution when applied to the observed data structure. We developed these tests, which represent a generalization of the maximum mean discrepancy tests described in Gretton et al. [2006], using recent developments from the higher-order pathwise differentiability literature. Despite their complex derivation, the associated test statistics can be expressed rather simply as U-statistics. We study the asymptotic behavior of the proposed tests under the null hypothesis and under both fixed and local alternatives. We provide examples to which our tests …

Nonparametric Methods For Doubly Robust Estimation Of Continuous Treatment Effects, Edward Kennedy, Zongming Ma, Matthew Mchugh, Dylan Small

Edward H. Kennedy

Continuous treatments (e.g., doses) arise often in practice, but available causal effect estimators require either parametric models for the effect curve or else consistent estimation of a single nuisance function. We propose a novel doubly robust kernel smoothing approach, which requires only mild smoothness assumptions on the effect curve and allows for misspecification of either the treatment density or outcome regression. We derive asymptotic properties and also discuss an approach for data-driven bandwidth selection. The methods are illustrated via simulation and in a study of the effect of nurse staffing on hospital readmissions penalties.

公的統計における欠測値補定の研究：多重代入法と単一代入法(高橋将宜), Masayoshi Takahashi

Masayoshi Takahashi

No abstract provided.

Set-Based Tests For Genetic Association In Longitudinal Studies, Zihuai He, Min Zhang, Seunggeun Lee, Jennifer A. Smith, Xiuqing Guo, Walter Palmas, Sharon L.R. Kardia, Ana V. Diez Roux, Bhramar Mukherjee

Jennifer McMahon

Genetic association studies with longitudinal markers of chronic diseases (e.g., blood pressure, body mass index) provide a valuable opportunity to explore how genetic variants affect traits over time by utilizing the full trajectory of longitudinal outcomes. Since these traits are likely influenced by the joint eff#11;ect of multiple variants in a gene, a joint analysis of these variants considering linkage disequilibrium (LD) may help to explain additional phenotypic variation. In this article, we propose a longitudinal genetic random field model (LGRF), to test the association between a phenotype measured repeatedly during the course of an observational study and a set …

Surrogate Markers For Time-Varying Treatments And Outcomes, Jesse Hsu, Edward Kennedy, Jason Roy, Alisa Stephens-Shields, Dylan Small, Marshall Joffe

Edward H. Kennedy

A surrogate marker is a variable commonly used in clinical trials to guide treatment decisions when the outcome of ultimate interest is not available. A good surrogate marker is one where the treatment effect on the surrogate is a strong predictor of the effect of treatment on the outcome. We review the situation when there is one treatment delivered at baseline, one surrogate measured at one later time point, and one ultimate outcome of interest and discuss new issues arising when variables are time-varying. Most of the literature on surrogate markers has only considered simple settings with one treatment, one …

Promoting Similarity Of Model Sparsity Structures In Integrative Analysis Of Cancer Genetic Data, Shuangge Ma

Shuangge Ma

In profiling studies, the analysis of a single dataset often leads to unsatisfactory results because of the small sample size. Multi-dataset analysis utilizes information across multiple independent datasets and outperforms single-dataset analysis. Among the available multi-dataset analysis methods, integrative analysis methods aggregate and analyze raw data and outperform meta-analysis methods, which analyze multiple datasets separately and then pool summary statistics. In this study, we conduct integrative analysis and marker selection under the heterogeneity structure, which allows different datasets to have overlapping but not necessarily identical sets of markers. Under certain scenarios, it is reasonable to expect some similarity of identified …

Matching Methods For Biomarker Evaluation: A Mapping With Causal Inference, Debashis Ghosh, Michael Sabel

Debashis Ghosh

In many medical settings, there is interest in evaluating the predictive ability of a candidate biomarker while adjusting appropriately for confounding factors. Recently, Janes and Pepe (2008, {\it Biometrics} 64: 1 -- 9) evaluated the effects of matching on classification accuracy for biomarkers. In this article, we note an analogy between the use of matching in causal inference with its role in the biomarker evaluation problem. This leads us to be able to import much of the literature on matching from causal inferential settings to the biomarker evaluation problem. This leads to a theoretical characterization of the bias properties of …