The Nuances Of Statistically Analyzing Next-Generation Sequencing Data,
2012
Kansas State University Libraries
The Nuances Of Statistically Analyzing Next-Generation Sequencing Data, Sanvesh Srivastava, R. W. Doerge
Conference on Applied Statistics in Agriculture
High-throughput sequencing technologies, in particular next-generation sequencing (NGS) technologies, have emerged as the preferred approach for exploring both gene function and pathway organization. Data from NGS technologies pose new computational and statistical challenges because of their massive size, limited replicate information, large number of genes (high-dimensionality), and discrete form. They are more complex than data from previous high-throughput technologies such as microarrays. In this work we focus on the statistical issues in analyzing and modeling NGS data for selecting genes suitable for further exploration and present a brief review of the relevant statistical methods. We discuss visualization methods to assess …
Treatment Heterogeneity And Potential Outcomes In Linear Mixed Effects Models,
2012
Kansas State University Libraries
Treatment Heterogeneity And Potential Outcomes In Linear Mixed Effects Models, Troy E. Richardson, Gary L. Gadbury
Conference on Applied Statistics in Agriculture
Studies commonly focus on estimating a mean treatment effect in a population. However, in some applications the variability of treatment effects across individual units may help to characterize the overall effect of a treatment across the population. Consider a set of treatments, {T,C}, where T denotes some treatment that might be applied to an experimental unit and C denotes a control. For each of N experimental units, the duplet {rTᵢ,rCᵢ}, i = 1,2, … , N, represents the potential response of the i th experimental unit if treatment were applied and the response …
Identifying Spectra Important For Prediction Of Senescent Grassland Canopy Structure,
2012
Kansas State University Libraries
Identifying Spectra Important For Prediction Of Senescent Grassland Canopy Structure, Rebecca Phillips, Nicanor Saliendra, Mark West
Conference on Applied Statistics in Agriculture
Managers of the nearly 0.5 million ha of public lands in North and South Dakota, USA rely heavily on manual measurements of vegetation properties to ensure conservation of grassland structure for wildlife and forage for livestock. Spectral imaging data may be useful in assessment of large (>100,000 ha) landscapes, as in the Grand River National Grassland (GRNG), South Dakota. Here, we examined the predictive potential for the Advanced High Resolution Spectrometer (AVIRIS) to estimate mixed-grass prairie canopy structural attributes (photosynthetically active vegetation (kg PV ha-1), non-photosynthetically active vegetation (kg NPV ha-1), total standing crop (kg …
Exploration Of Reactant-Product Lipid Pairs In Mutant-Wild Type Lipidomics Experiments,
2012
Kansas State University Libraries
Exploration Of Reactant-Product Lipid Pairs In Mutant-Wild Type Lipidomics Experiments, Lianqing Zheng, Gary L. Gadbury, Jyoti Shah, Ruth Welti
Conference on Applied Statistics in Agriculture
High-throughput metabolite analysis is very important for biologists to identify the functions of genes. A mutation in a gene encoding an enzyme is expected to alter the level of the metabolites which serve as the enzyme’s reactant(s) (also known as substrate) and product(s). To find the function of a mutated gene, metabolite data from a wild-type organism and a mutant are compared and candidate reactants and products are identified. The screening principle is that the concentration of reactants will be higher and the concentration of products will be lower in the mutant than in wild type. This is because the …
Variance Inflation Factors In Regression Models With Dummy Variables,
2012
Kansas State University Libraries
Variance Inflation Factors In Regression Models With Dummy Variables, Leigh Murray, Hien Nguyen, Yu-Feng Lee, Marta D. Remmenga, David W. Smith
Conference on Applied Statistics in Agriculture
Variance Inflation Factors (VIFs) are used to detect collinearity among predictors in regression models. Textbook explanation of collinearity and diagnostics such as VIFs have focused on numeric predictors as being "co-linear" or "co-planar", with little attention paid to VIFs when a dummy variable is included in the model. This work was motivated by two regression models with high VIFs, where "standard' interpretations of causes of collinearity made no sense. The first was an alfalfa-breeding model with two numeric predictors and two dummy variables. The second was an economic model with one numeric predictor, one dummy and the numeric x dummy …
Stability Analysis For Yield And Seed Quality Of Soybean [Glycine Max (L.) Merril] Across Different Environments In Eastern South Dakota,
2012
Kansas State University Libraries
Stability Analysis For Yield And Seed Quality Of Soybean [Glycine Max (L.) Merril] Across Different Environments In Eastern South Dakota, Kaushal Raj Chaudhary, Jixiang Wu
Conference on Applied Statistics in Agriculture
Genotype-environment interaction has always been an important and challenging issue for plant breeders in developing desirable varieties. Determination of genotype and environment is common in breeding program as it helps to find out the genotypes that have wide or specific adaptability across various environmental conditions. In this study, fifteen varieties of soybean were evaluated for stability of grain yield (ton/ha), protein content (%), and oil content (%) at six different locations of Eastern South Dakota in 2011. Mixed linear model and Additive main effects and multiplicative interactions (AMMI) were applied to detect genotype-by-environment (G*E) interactions and stability of each variety …
Gene Set Testing To Characterize Multivariately Differentially Expressed Genes,
2012
Kansas State University Libraries
Gene Set Testing To Characterize Multivariately Differentially Expressed Genes, John R. Stevens, S. Clay Isom
Conference on Applied Statistics in Agriculture
In a gene expression experiment (using oligo array, RNA-Seq, or other platform), researchers typically seek to characterize di erentially expressed genes based on common gene function or pathway involve-ment. The eld of gene set testing provides numerous characterization methods, some of which have proven to be more valid and powerful than others. These existing gene set testing methods focus on experimental designs where there is a single null hypothesis (usually involving association with a continuous or categorical phenotype) for each gene. Increasingly common experimental designs lead to multiple null hypotheses for each gene, and the characterization of these multivariately di …
Determining The Effectivesness Of Including Spatial Information Into A Nematode/Nutsedge Pest Complex Model,
2012
Kansas State University Libraries
Determining The Effectivesness Of Including Spatial Information Into A Nematode/Nutsedge Pest Complex Model, Joel Vetter, Zhining Ou, Leigh Murray, Stephen H. Thomas, Jill Schroeder
Conference on Applied Statistics in Agriculture
An experiment was performed in 2005-2006 to determine if a nematode-resistant variety of alfalfa (Medicago sativa L.) can effectively reduce the pest complex consisting of yellow and purple nutsedge (YNS, Cyperus esculentus L. and PNS, C. rotundus L.) and the southern rootknot nematode (SRKN, Meloidogyne incognita (Kofoid & White) Chitwood). The alfalfa field, which had a history of severe infestation from both species of nutsedge and SRKN, was divided into 1m x 2m quadrats. In May, July and September of each year, eighty quadrats were randomly selected and counts of PNS, YNS and a soil sample (analyzed for the count …
Statistical Tests For Stability Analysis With Resampling Techniques,
2012
Kansas State University Libraries
Statistical Tests For Stability Analysis With Resampling Techniques, Jixiang Wu, Karl Glover, William Berzonsky
Conference on Applied Statistics in Agriculture
Crop trials or crop performance trials (CPT), which are among the most important activities associated with plant breeding programs, are commonly used to measure the performance stability of genotypes. Several methods which include variation, regression, and cluster analyses for determination of crop stability have been proposed and are commonly used. However, many of these approaches require the use of normally distributed data. Thus, commonly used statistical tests, like the t- or F-test may not be appropriate when the assumptions of data are violated. In this study, two resampling techniques (jackknife and bootstrapping) were integrated into several crop stability analyses. An …
Bayesian Mcmc Analyses For Regulatory Assessments Of Food Composition,
2012
Kansas State University Libraries
Bayesian Mcmc Analyses For Regulatory Assessments Of Food Composition, Jay M. Harrison, Derek Culp, George G. Harrigan
Conference on Applied Statistics in Agriculture
In order to gain regulatory approval to market a new seed product derived with biotechnology, grain and forage composition data must be collected from field trials, and summaries must be reported to various government agencies. Currently, both tests of differences in composition between a genetically modified organism (GMO) and its control and tests of equivalence of the GMO to conventional genotypes are required by regulatory agencies. Bayesian analyses offer an attractive option for regulatory assessments by expressing results that can be interpreted more easily by a wide audience and by providing more ways to examine various hypotheses of interest. In …
A Comparison Of Analytic And Bayesian Approaches For Characterizing Thermal Hysteresis In Cattle Using Algebraic And Geometric Distances,
2012
Kansas State University Libraries
A Comparison Of Analytic And Bayesian Approaches For Characterizing Thermal Hysteresis In Cattle Using Algebraic And Geometric Distances, F. Yang, A. M. Parkhurst, S. Zhang, C. N. Lee, T. M. Brown-Brandl, K. G. Gebremedhin, P. E. Hillman
Conference on Applied Statistics in Agriculture
A high ambient temperature poses a serious threat to cattle. Above a certain threshold, an animal’s body temperature (Tb) appears to be driven by the hot cyclic air temperature (Ta) and hysteresis occurs. Elliptical hysteresis describes the output of a process in response to a simple harmonic input, and the trajectory forms a closed loop. The hysteresis loop shows a rotated elliptical pattern which depends on the lag between Tb and Ta. The objectives of this study are 1) to characterize hysteresis using bootstrapped ellipse specific nonlinear least squares 2) to reformulate models using the Bayesian method, and 3) to …
Armedand Dangerous: The Consequences Of Not Randomizing The First Block,
2012
Kansas State University Libraries
Armedand Dangerous: The Consequences Of Not Randomizing The First Block, Edzard Van Santen, Mark West
Conference on Applied Statistics in Agriculture
Replication and randomization and are the keys for statistically valid experiments. Both are necessary components for statistically valid experimentation. Yet it is an industry wide practicein weed science research to assign treatment in the first block of a randomized complete block design in a systematic order for reasons of convenience. We investigated this practice by comparing four randomization/analysis scenarios: (i) complete randomization in all blocks, (ii) systematic assignment of treatmentsin block 1, where the best treatment was assigned to the best plot, (iii) systematic assignment of treatmentsin block 1, where the best treatment was assigned to the worst plot,and (iv) …
Correcting For Amplification Bias In Next-Generation Sequencing Data,
2012
Kansas State University Libraries
Correcting For Amplification Bias In Next-Generation Sequencing Data, Douglas Baumann, R. W. Doerge
Conference on Applied Statistics in Agriculture
Next-generation sequencing (NGS) technologies have opened the door to a wealth of knowledge and information about biological systems, particularly in genomics and epigenomics. These tools, although useful, carry with them additional technological and statistical challenges that need to be understood and addressed. One such issue is ampli cation bias. Specifically, the majority of NGS technologies effectively sample small amounts of DNA or RNA that are amplified (i.e., copied) prior to sequencing. The amplification process is not perfect, and thus sequenced read counts can be extremely biased. Unfortunately, current amplification bias controlling procedures introduce a dependence of gene expression on gene …
Multivariate Statistical Analysis Of Avian Index Of Biotic Integrity,
2012
Kansas State University Libraries
Multivariate Statistical Analysis Of Avian Index Of Biotic Integrity, Bahman Shafii, William J. Price, Norm Merz, Dwight Bergeron
Conference on Applied Statistics in Agriculture
The Index of Biotic Integrity (IBI) is a multi-metric index designed to measure the changes in ecological and environmental conditions as affected by human disturbances. Hence, IBI is used in practice to detect divergence from biological integrity attributable to human actions. The incorporation of biological attributes is often done at both the individual and higher level assemblages. The objective of this paper is to demonstrate the construction and statistical evaluation of a multi-metric Avian Index of Biotic Integrity (A-IBI). Canonical correlation analyses are utilized to select pertinent avian metrics as impacted by vegetation and hydrology variables. The resulting avian metrics …
Evaluation Of Genotype By Environment Interactions From Unreplicated Multi-Environmental Trials Of Hybrid Maize,
2012
Kansas State University Libraries
Evaluation Of Genotype By Environment Interactions From Unreplicated Multi-Environmental Trials Of Hybrid Maize, Ani A. Elias, Kelly R. Robbins, Dev Niyogi, James J. Camberato, R. W. Doerge, Mitchell R. Tuinstra
Conference on Applied Statistics in Agriculture
Diverse soils and varying weather conditions not only affect overall performance of hybrid maize in multi-environment field studies, but can also cause strong genotype by environment interactions (GEI). Modern maize breeding experiments utilize multilocation trials with augmented field designs to evaluate the performance of unreplicated test hybrids. Augmented designs are resource efficient; however, these designs do not efficiently quantify or test GEI variation in the test hybrids. New methods are being developed that use random regression models to incorporate multiple environmental effects into GEI models to increase their accuracy and predictive ability. Incorporation of varying weather and soil physical variables …
Editor's Preface And Table Of Contents,
2012
Kansas State University Libraries
Editor's Preface And Table Of Contents, Weixing Song
Conference on Applied Statistics in Agriculture
These proceedings contain papers presented in the twenty-fourth annual Kansas State University Conference on Applied Statistics in Agriculture, held in Manhattan, Kansas, April 29 - May 1, 2012.
A Failure Index For High Performance Computing Applications,
2012
Louisiana Tech University
A Failure Index For High Performance Computing Applications, Clayton F. Chandler
Doctoral Dissertations
This dissertation introduces a new metric in the area of High Performance Computing (HPC) application reliability and performance modeling. Derived via the time-dependent implementation of an existing inequality measure, the Failure index (FI) generates a coefficient representing the level of volatility for the failures incurred by an application running on a given HPC system in a given time interval. This coefficient presents a normalized cross-system representation of the failure volatility of applications running on failure-rich HPC platforms. Further, the origin and ramifications of application failures are investigated, from which certain mathematical conclusions yield greater insight into the behavior of these …
Using Multiattribute Utility Copulas In Support Of Uav Search And Destroy Operations,
2012
Air Force Institute of Technology
Using Multiattribute Utility Copulas In Support Of Uav Search And Destroy Operations, Beau A. Nunnally
Theses and Dissertations
The multiattribute utility copula is an emerging form of utility function used by decision analysts to study decisions with dependent attributes. Failure to properly address attribute dependence may cause errors in selecting the optimal policy. This research examines two scenarios of interest to the modern warfighter. The first scenario employs a utility copula to determine the type, quantity, and altitude of UAVs to be sent to strike a stationary target. The second scenario employs a utility copula to examine the impact of attribute dependence on the optimal routing of UAVs in a contested operational environment when performing a search and …
On The Order Statistics Of Standard Normal-Based Power Method Distributions,
2012
Southern Illinois University Carbondale
On The Order Statistics Of Standard Normal-Based Power Method Distributions, Todd C. Headrick, Mohan D. Pant
Mohan Dev Pant
This paper derives a procedure for determining the expectations of order statistics associated with the standard normal distribution (Z) and its powers of order three and five (Z^3 and Z^5). The procedure is demonstrated for sample sizes of n ≤ 9. It is shown that Z^3 and Z^5 have expectations of order statistics that are functions of the expectations for Z and can be expressed in terms of explicit elementary functions for sample sizes of n ≤ 5. For sample sizes of n = 6, 7 the expectations of the order statistics for Z, Z^3, and Z^5 only require a …
A Doubling Method For The Generalized Lambda Distribution,
2012
Southern Illinois University Carbondale
A Doubling Method For The Generalized Lambda Distribution, Todd C. Headrick, Mohan D. Pant
Mohan Dev Pant
This paper introduces a new family of generalized lambda distributions (GLDs) based on a method of doubling symmetric GLDs. The focus of the development is in the context of L-moments and L-correlation theory. As such, included is the development of a procedure for specifying double GLDs with controlled degrees of L-skew, L-kurtosis, and L-correlations. The procedure can be applied in a variety of settings such as modeling events and Monte Carlo or simulation studies. Further, it is demonstrated that estimates of L-skew, L-kurtosis, and L-correlation are substantially superior to conventional product-moment estimates of skew, kurtosis, and Pearson correlation in terms …
