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Heart And Skeletal Muscle Inflammation Of Farmed Salmon Is Associated With Infection With A Novel Reovirus, Torstein Tengs 2010 Norwegian Veterinary Institute

Heart And Skeletal Muscle Inflammation Of Farmed Salmon Is Associated With Infection With A Novel Reovirus, Torstein Tengs

Dr. Torstein Tengs

Atlantic salmon (Salmo salar L.) mariculture has been associated with epidemics of infectious diseases that threaten not only local production, but also wild fish coming into close proximity to marine pens and fish escaping from them. Heart and skeletal muscle inflammation (HSMI) is a frequently fatal disease of farmed Atlantic salmon. First recognized in one farm in Norway in 1999, HSMI was subsequently implicated in outbreaks in other farms in Norway and the United Kingdom. Although pathology and disease transmission studies indicated an infectious basis, efforts to identify an agent were unsuccessful. Here we provide evidence that HSMI is associated ...


Non-Prejudiced Detection And Characterization Of Genetic Modifications, Torstein Tengs 2010 Norwegian Veterinary Institute

Non-Prejudiced Detection And Characterization Of Genetic Modifications, Torstein Tengs

Dr. Torstein Tengs

The application of gene technology is becoming widespread much thanks to the rapid increase in technology, resource, and knowledge availability. Consequently, the diversity and number of genetically modified organisms (GMOs) that may find their way into the food chain or the environment, intended or unintended, is rapidly growing. From a safety point of view the ability to detect and characterize in detail any GMO, independent of publicly available information, is fundamental. Pre-release risk assessments of GMOs are required in most jurisdictions and are usually based on application of technologies with limited ability to detect unexpected rearrangements and insertions. We present ...


On Distance-Based Permutation Tests For Between-Group Comparisons, Philip T. Reiss, M. Henry H. Stevens, Zarrar Shehzad, Eva Petkova, Michael P. Milham 2010 New York University

On Distance-Based Permutation Tests For Between-Group Comparisons, Philip T. Reiss, M. Henry H. Stevens, Zarrar Shehzad, Eva Petkova, Michael P. Milham

Philip T. Reiss

Permutation tests based on distances among multivariate observations have found many applications in the biological sciences. Two major testing frameworks of this kind are multiresponse permutation procedures and pseudo-F tests arising from a distance-based extension of multivariate analysis of variance. In this paper we derive conditions under which these two frameworks are equivalent. The methods and equivalence results are illustrated by reanalyzing an ecological data set and by a novel application to functional magnetic resonance imaging data.


Comparison Of Nine Different Real-Time Pcr Chemistries For Qualitative And Quantitative Applications In Gmo Detection, Torstein Tengs 2010 Norwegian Veterinary Institute

Comparison Of Nine Different Real-Time Pcr Chemistries For Qualitative And Quantitative Applications In Gmo Detection, Torstein Tengs

Dr. Torstein Tengs

Several techniques have been developed for detection and quantification of genetically modified organisms, but quantitative real-time PCR is by far the most popular approach. Among the most commonly used realtime PCR chemistries are TaqMan probes and SYBR green, but many other detection chemistries have also been developed. Because their performance has never been compared systematically, here we present an extensive evaluation of some promising chemistries: sequenceunspecific DNA labeling dyes (SYBR green), primer-based technologies (AmpliFluor, Plexor, Lux primers), and techniques involving double-labeled probes, comprising hybridization (molecular beacon) and hydrolysis (TaqMan, CPT, LNA, and MGB) probes, based on recently published experimental data ...


Prevalence, Incidence, And Persistence Of Major Depressive Symptoms In The Cardiovascular Health Study, Stephen M. Thielke MD, MS, Paula Diehr PhD 2010 University of Washington

Prevalence, Incidence, And Persistence Of Major Depressive Symptoms In The Cardiovascular Health Study, Stephen M. Thielke Md, Ms, Paula Diehr Phd

Paula Diehr

PURPOSE: To explore the association of major depressive symptoms with advancing age, sex, and self-rated health among older adults. DESIGN AND METHODS: We analyzed 10 years of annual assessments in a longitudinal cohort of 5888 Medicare recipients in the Cardiovascular Health Study. Self-rated health was assessed with a single question, and subjects categorized as healthy or sick. Major depressive symptoms were assessed using the Center for Epidemiologic Studies Short Depression Scale, with subjects categorized as nondepressed (score < 10) or depressed (> or =10). Age-, sex-, and health-specific prevalence of depression and the probabilities of transition between depressed and nondepressed states were estimated. RESULTS: The ...


A Mixture Model Based Approach For Estimating The Fdr In Replicated Microarray Data, SHUO JIAO, Shunpu Zhang 2010 Fred Hutchinson Cancer Research Center

A Mixture Model Based Approach For Estimating The Fdr In Replicated Microarray Data, Shuo Jiao, Shunpu Zhang

Shuo Jiao

One of the mostly used methods for estimating the false discovery rate (FDR) is the permutation based method. The permutation based method has the well-known granularity problem due to the discrete nature of the permuted null scores. The granularity problem may produce very unstable FDR estimates. Such instability may cause scientists to over- or under-estimate the number of false positives among the genes declared as significant, and hence result in inaccurate interpretation of biological data. In this paper, we propose a new model based method as an improvement of the permutation based FDR estimation method of SAM [1] The new ...


Event Adjudication Changes Key Results In Open-Label Trials: The Affirm Experience, Elaine M. Nasco, April Slee, Kent M. Koprowicz, Robert G. Hart 2010 Axio Research

Event Adjudication Changes Key Results In Open-Label Trials: The Affirm Experience, Elaine M. Nasco, April Slee, Kent M. Koprowicz, Robert G. Hart

Kent M Koprowicz

Event Adjudication Changes Key Results in Open-Label Trials: The AFFIRM Experience Author Block: Elaine M. Nasco, April Slee, Kent Koprowicz, Robert G. Hart, Axio Research, LLC, Seattle, WA Abstract: Background: The value of central event adjudication of endpoints in multi-center randomized trials has recently been questioned. Methods: The NIH-sponsored Atrial Fibrillation Follow-up Investigation of Rhythm Management (AFFIRM) trial randomized 4,060 atrial fibrillation patients to antiarrhythmic drugs (rhythm control) vs. rate-controlling drugs, given open-label, at 213 clinical sites. While the primary outcome was mortality, a key secondary endpoint was ischemic stroke (IS), centrally adjudicated by those reviewing source documents from ...


Functional Generalized Linear Models With Images As Predictors, Philip T. Reiss, R. Todd Ogden 2010 New York University

Functional Generalized Linear Models With Images As Predictors, Philip T. Reiss, R. Todd Ogden

Philip T. Reiss

Functional principal component regression (FPCR) is a promising new method for regressing scalar outcomes on functional predictors. In this paper we present a theoretical justification for the use of principal components in functional regression. FPCR is then extended in two directions: from linear to the generalized linear modeling, and from univariate signal predictors to high-resolution image predictors. We show how to implement the method efficiently by adapting generalized additive model technology to the functional regression context. A technique is proposed for estimating simultaneous confidence bands for the coefficient function; in the neuroimaging setting, this yields a novel means to identify ...


Estimating The Proportion Of Equivalently Expressed Genes In Microarray Data Based On Transformed Test Statistics, SHUO JIAO, Shunpu Zhang 2010 Fred Hutchinson Cancer Research Center

Estimating The Proportion Of Equivalently Expressed Genes In Microarray Data Based On Transformed Test Statistics, Shuo Jiao, Shunpu Zhang

Shuo Jiao

In microarray data analysis, false discovery rate (FDR) is now widely accepted as the control criterion to account for multiple hypothesis testing. The proportion of equivalently expressed genes (π0) is a key component to be estimated in the estimation of FDR. Some commonly used π0 estimators (BUM, SPLOSH, QVALUE, and LBE ) are all based on p-values, and they are essentially upper bounds of π0. The simulations we carried out show that these four methods significantly overestimate the true π0 when differentially expressed genes and equivalently expressed genes are not well separated. To solve this problem, we first introduce a novel ...


Wavelet-Based Functional Linear Mixed Models: An Application To Measurement Error–Corrected Distributed Lag Models, Elizabeth J. Malloy, Jeffrey S. Morris, Sara D. Adar, Helen Suh, Diane R. Gold, Brent A. Coull 2010 American University

Wavelet-Based Functional Linear Mixed Models: An Application To Measurement Error–Corrected Distributed Lag Models, Elizabeth J. Malloy, Jeffrey S. Morris, Sara D. Adar, Helen Suh, Diane R. Gold, Brent A. Coull

Jeffrey S. Morris

Frequently, exposure data are measured over time on a grid of discrete values that collectively define a functional observation. In many applications, researchers are interested in using these measurements as covariates to predict a scalar response in a regression setting, with interest focusing on the most biologically relevant time window of exposure. One example is in panel studies of the health effects of particulate matter (PM), where particle levels are measured over time. In such studies, there are many more values of the functional data than observations in the data set so that regularization of the corresponding functional regression coefficient ...


Members’ Discoveries: Fatal Flaws In Cancer Research, Jeffrey S. Morris 2010 The University of Texas M.D. Anderson Cancer Center

Members’ Discoveries: Fatal Flaws In Cancer Research, Jeffrey S. Morris

Jeffrey S. Morris

A recent article published in The Annals of Applied Statistics (AOAS) by two MD Anderson researchers—Keith Baggerly and Kevin Coombes—dissects results from a highly-influential series of medical papers involving genomics-driven personalized cancer therapy, and outlines a series of simple yet fatal flaws that raises serious questions about the veracity of the original results. Having immediate and strong impact, this paper, along with related work, is providing the impetus for new standards of reproducibility in scientific research.


Statistical Contributions To Proteomic Research, Jeffrey S. Morris, Keith A. Baggerly, Howard B. Gutstein, Kevin R. Coombes 2010 The University of Texas M.D. Anderson Cancer Center

Statistical Contributions To Proteomic Research, Jeffrey S. Morris, Keith A. Baggerly, Howard B. Gutstein, Kevin R. Coombes

Jeffrey S. Morris

Proteomic profiling has the potential to impact the diagnosis, prognosis, and treatment of various diseases. A number of different proteomic technologies are available that allow us to look at many proteins at once, and all of them yield complex data that raise significant quantitative challenges. Inadequate attention to these quantitative issues can prevent these studies from achieving their desired goals, and can even lead to invalid results. In this chapter, we describe various ways the involvement of statisticians or other quantitative scientists in the study team can contribute to the success of proteomic research, and we outline some of the ...


Informatics And Statistics For Analyzing 2-D Gel Electrophoresis Images, Andrew W. Dowsey, Jeffrey S. Morris, Howard G. Gutstein, Guang Z. Yang 2010 Imperial College London

Informatics And Statistics For Analyzing 2-D Gel Electrophoresis Images, Andrew W. Dowsey, Jeffrey S. Morris, Howard G. Gutstein, Guang Z. Yang

Jeffrey S. Morris

Whilst recent progress in ‘shotgun’ peptide separation by integrated liquid chromatography and mass spectrometry (LC/MS) has enabled its use as a sensitive analytical technique, proteome coverage and reproducibility is still limited and obtaining enough replicate runs for biomarker discovery is a challenge. For these reasons, recent research demonstrates the continuing need for protein separation by two-dimensional gel electrophoresis (2-DE). However, with traditional 2-DE informatics, the digitized images are reduced to symbolic data though spot detection and quantification before proteins are compared for differential expression by spot matching. Recently, a more robust and automated paradigm has emerged where gels are ...


Bayesian Random Segmentationmodels To Identify Shared Copy Number Aberrations For Array Cgh Data, Veerabhadran Baladandayuthapani, Yuan Ji, Rajesh Talluri, Luis E. Nieto-Barajas, Jeffrey S. Morris 2010 Texas A&M University

Bayesian Random Segmentationmodels To Identify Shared Copy Number Aberrations For Array Cgh Data, Veerabhadran Baladandayuthapani, Yuan Ji, Rajesh Talluri, Luis E. Nieto-Barajas, Jeffrey S. Morris

Jeffrey S. Morris

Array-based comparative genomic hybridization (aCGH) is a high-resolution high-throughput technique for studying the genetic basis of cancer. The resulting data consists of log fluorescence ratios as a function of the genomic DNA location and provides a cytogenetic representation of the relative DNA copy number variation. Analysis of such data typically involves estimation of the underlying copy number state at each location and segmenting regions of DNA with similar copy number states. Most current methods proceed by modeling a single sample/array at a time, and thus fail to borrow strength across multiple samples to infer shared regions of copy number ...


Code For Fitting Bdsacgh, Veera Baladandayuthapani 2010 UT MD Anderson Cancer Center

Code For Fitting Bdsacgh, Veera Baladandayuthapani

Veera Baladandayuthapani

No abstract provided.


R Package For Bayesian Ensemble Methods For Survival Prediction In Gene Expression Data, Veera Baladandayuthapani 2010 UT MD Anderson Cancer Center

R Package For Bayesian Ensemble Methods For Survival Prediction In Gene Expression Data, Veera Baladandayuthapani

Veera Baladandayuthapani

This is the R package for the methods described in Bayesian ensemble methods for survival prediction in gene expression data by Vinicius Bonato , Veerabhadran Baladandayuthapani, Kim-Anh Do, Bradley M. Broom, Erik P. Sulman, and Kenneth D. Aldape Submitted to Bioinformatics (2010)


Bayesian Random Segmentationmodels To Identify Shared Copy Number Aberrations For Array Cgh Data, Veera Baladandayuthapani 2010 UT MD Anderson Cancer Center

Bayesian Random Segmentationmodels To Identify Shared Copy Number Aberrations For Array Cgh Data, Veera Baladandayuthapani

Veera Baladandayuthapani

No abstract provided.


Identification Of Ovarian Cancer Symptoms In Health Insurance Claims Data., Paula Diehr, Sean Devlin 2010 University of Washington

Identification Of Ovarian Cancer Symptoms In Health Insurance Claims Data., Paula Diehr, Sean Devlin

Paula Diehr

Background: Women with ovarian cancer have reported abdominal=pelvic pain, bloating, difficulty eating or feeling full quickly, and urinary frequency=urgency prior to diagnosis. We explored these findings in a general population using a dataset of insured women aged 40–64 and investigated the potential effectiveness of a routine review of claims data as a prescreen to identify women at high risk for ovarian cancer. Methods: Data from a large Washington State health insurer were merged with the Seattle-Puget Sound Surveillance, Epidemiology and End Results (SEER) cancer registry for 2000–2004. We estimated the prevalence of symptoms in the 36 ...


Targeted Maximum Likelihood Estimation Of The Parameter Of A Marginal Structural Model, Michael Rosenblum, Mark J. van der Laan 2010 Johns Hopkins University

Targeted Maximum Likelihood Estimation Of The Parameter Of A Marginal Structural Model, Michael Rosenblum, Mark J. Van Der Laan

Michael Rosenblum

Targeted maximum likelihood estimation is a versatile tool for estimating parameters in semiparametric and nonparametric models. We work through an example applying targeted maximum likelihood methodology to estimate the parameter of a marginal structural model. In the case we consider, we show how this can be easily done by clever use of standard statistical software. We point out differences between targeted maximum likelihood estimation and other approaches (including estimating function based methods). The application we consider is to estimate the effect of adherence to antiretroviral medications on virologic failure in HIV positive individuals.


Discrete Nonparametric Algorithms For Outlier Detection With Genomic Data, Debashis Ghosh 2010 Penn State University

Discrete Nonparametric Algorithms For Outlier Detection With Genomic Data, Debashis Ghosh

Debashis Ghosh

In high-throughput studies involving genetic data such as from gene expression mi- croarrays, dierential expression analysis between two or more experimental conditions has been a very common analytical task. Much of the resulting literature on multiple comparisons has paid relatively little attention to the choice of test statistic. In this article, we focus on the issue of choice of test statistic based on a special pattern of dierential expression. The approach here is based on recasting multiple comparisons procedures for assessing outlying expression values. A major complication is that the resulting p-values are discrete; some theoretical properties of sequential testing ...


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