Statistics and Probability Commons^™

Identification Of Gene Expression Patterns Using Planned Linear Contrasts, Hao Li, Constance L. Wood, Yushu Liu, Thomas V. Getchell, Marilyn L. Getchell, Arnold J. Stromberg

Statistics Faculty Publications

BACKGROUND: In gene networks, the timing of significant changes in the expression level of each gene may be the most critical information in time course expression profiles. With the same timing of the initial change, genes which share similar patterns of expression for any number of sampling intervals from the beginning should be considered co-expressed at certain level(s) in the gene networks. In addition, multiple testing problems are complicated in experiments with multi-level treatments when thousands of genes are involved.

RESULTS: To address these issues, we first performed an ANOVA F test to identify significantly regulated genes. The Benjamini and …

Nonparametric Control Chart For The Range, Arnold J. Stromberg

Statistics Faculty Patents

A method is provided for detecting or predicting an undesired deviation in variability of at least one parameter being monitored, wherein the variation in the parameter is incrementally recorded. The method comprises establishing the number of subsets of a dataset that have a range of the difference between any two datapoints within the dataset, and computing a control chart for the range based thereon. The method accurately detects changes in variability in real time. The true distribution of the data is reflected, and the desired result is achieved without requiring an inordinate number of computations.

Quadratic Regression Analysis For Gene Discovery And Pattern Recognition For Non-Cyclic Short Time-Course Microarray Experiments, Hua Liu, Sergey Tarima, Aaron S. Borders, Thomas V. Getchell, Marilyn L. Getchell, Arnold J. Stromberg

Statistics Faculty Publications

BACKGROUND: Cluster analyses are used to analyze microarray time-course data for gene discovery and pattern recognition. However, in general, these methods do not take advantage of the fact that time is a continuous variable, and existing clustering methods often group biologically unrelated genes together.

RESULTS: We propose a quadratic regression method for identification of differentially expressed genes and classification of genes based on their temporal expression profiles for non-cyclic short time-course microarray data. This method treats time as a continuous variable, therefore preserves actual time information. We applied this method to a microarray time-course study of gene expression at short …

Analysis Of Oligonucleotide Array Experiments With Repeated Measures Using Mixed Models, Hao Li, Constance L. Wood, Thomas V. Getchell, Marilyn L. Getchell, Arnold J. Stromberg

Statistics Faculty Publications

BACKGROUND: Two or more factor mixed factorial experiments are becoming increasingly common in microarray data analysis. In this case study, the two factors are presence (Patients with Alzheimer's disease) or absence (Control) of the disease, and brain regions including olfactory bulb (OB) or cerebellum (CER). In the design considered in this manuscript, OB and CER are repeated measurements from the same subject and, hence, are correlated. It is critical to identify sources of variability in the analysis of oligonucleotide array experiments with repeated measures and correlations among data points have to be considered. In addition, multiple testing problems are more …

Nonparametric Control Chart For The Range, Arnold J. Stromberg

Statistics Faculty Patents

The method comprises establishing the number of subsets of a dataset that have a range of the difference between any two datapoints within the dataset, and computing a control chart for the range based thereon. In another aspect, a software program for accomplishing the method of the present invention is provided. The method of the invention allows monitoring variability of a product being produced by a particular piece of machinery, of a process conducted by the machinery, or of a product stream generated thereby, accurately detecting changes in variability in real time. The true distribution of the data is reflected, …

Statistical Implications Of Pooling Rna Samples For Microarray Experiments, Xuejun Peng, Constance L. Wood, Eric M. Blalock, Kuey Chu Chen, Philip W. Landfield, Arnold J. Stromberg

Statistics Faculty Publications

BACKGROUND: Microarray technology has become a very important tool for studying gene expression profiles under various conditions. Biologists often pool RNA samples extracted from different subjects onto a single microarray chip to help defray the cost of microarray experiments as well as to correct for the technical difficulty in getting sufficient RNA from a single subject. However, the statistical, technical and financial implications of pooling have not been explicitly investigated.

RESULTS: Modeling the resulting gene expression from sample pooling as a mixture of individual responses, we derived expressions for the experimental error and provided both upper and lower bounds for …

Modeling Mass Transport In Aquifers: The Distributed Source Problem, Sergio E. Serrano

KWRRI Research Reports

This report presents a new methodology to model the time and space evolution of groundwater variables in a system of aquifers when certain components of the model, such as the geohydrologic information, the boundary conditions, the magnitude and variability of the sources or physical parameters are uncertain and defined in stochastic terms. This facilitates a more realistic statistical representation of groundwater flow and groundwater pollution forecasting for either the saturated or the unsaturated zone. The method is based on applications of modern mathematics to the solution of the resulting stochastic transport equations. This procedure exhibits considerable advantages over the existing …

Regionalization Of Flood Data Using Probability Distributions And Their Parameters, Nageshwar Rao Bhaskar, Carol Alf O'Connor, Harold Andrew Myers, William Paul Puckett

KWRRI Research Reports

The U. S. Geological survey recently used the method of residuals to delineate seven flood regions for the State of Kentucky. As an alternative approach, the FASTCLUS clustering procedure of the Statistical Analysis system (SAS) is used in this study to delineate five to six cluster regions in conjunction with statistical properties of the AMF series, like the coefficient of variation as estimated using method of L-moments, LCV, the parameters of the EVl and GEV flood frequency distributions, and the specific mean annual flood, QSP. For both cluster and USGS flood regions, regionalized flood frequency growth curves are developed and …

Improved Methods And Guidelines For Modeling Stormwater Runoff From Surface Coal Mined Lands, Michael E. Meadows, George E. Blandford

KWRRI Research Reports

The investgations, developments and guidelines for several hydrologic modeling strategies are presented. Investigations were conducted to determine appropriate event curve numbers for surface mined disturbed watersheds; and performance of four synthetic unit hydrograph models (SCS curvilinear, SCS single triangle, Williams and TVA double triangle) on 38 USDA experimental watersheds in 14 physiographic provinces using in excess of 270 events. A second test using only the SCS curvilinear unit hydrograph on 11 small watersheds and 48 events was conducted to investigate the excess rainfall pattern simulated with the curve number model. A procedure for developing a unit hydrograph using the time …

Modeling Surface And Subsurface Stormflow On Steeply-Sloping Forested Watersheds, Patrick G. Sloan, Ian D. Moore, George B. Coltharp, Joseph D. Eigel

KWRRI Research Reports

A simple conceptual rainfall-runoff model, based on the variable source area concept, was developed for predicting runoff from small, steep-sloped, forested Appalachian watersheds. Tests of the model showed that the predicted and observed daily discharges were in good agreement. The results demonstrate the ability of the model to simulate the "flashy" hydrologic behavior of these watersheds.

Five subsurface flow models were evaluated by application to existing data measured at Coweeta on a reconstructed homogeneous forest soil. The five models were: Nieber 's 2-D and 1-D finite element models (based on Richards' equation), the kinematic wave equation, and two simple storage …

Opset Program For Computerized Selection Of Watershed Parameter Values For The Stanford Watershed Model, Earnest Yuan-Shang Liou, L. Douglas James

KWRRI Research Reports

The advent of high-speed electronic computer made it possible to model complex hydrologic processes by mathematical expressions and thereby simulate streamflows from climatological data. The most widely used program is the Stanford Watershed Model, a digital parametric model of the land phase of the hydrologic cycle based on moisture accounting processes. It can be used to simulate annual or longer flow sequences at hourly time intervals. Due to its capability of simulating historical streamflows from recorded climatological data, it has a great potential in the planning and design of water resources systems. However, widespread use of the Stanford Watershed Model …