Medical Genetics Commons^™

Piscine Myocarditis Virus (Pmcv) In Wild Atlantic Salmon Salmo Salar, Torstein Tengs Dr.

Dr. Torstein Tengs

Cardiomyopathy syndrome (CMS) is a severe cardiac disease of sea-farmed Atlantic salmon Salmo salar L., but CMS-like lesions have also been found in wild Atlantic salmon. In 2010 a double-stranded RNA virus of the Totiviridae family, provisionally named piscine myocarditis virus (PMCV), was described as the causative agent of CMS. In the present paper we report the first detection of PMCV in wild Atlantic salmon. The study is based on screening of 797 wild Atlantic salmon by real-time RT-PCR. The samples were collected from 35 different rivers along the coast of Norway, and all individuals included in the study were …

Prevalence Of Tick Borne Encephalitis Virus In Tick Nymphs In Relation To Climatic Factors On The Southern Coast Of Norway, Torstein Tengs Dr.

Dr. Torstein Tengs

BACKGROUND

Tick-borne encephalitis (TBE) is among the most important vector borne diseases of humans in Europe and is currently identified as a major health problem in many countries. TBE endemic zones have expanded over the past two decades, as well as the number of reported cases within endemic areas. Multiple factors are ascribed for the increased incidence of TBE, including climatic change. The number of TBE cases has also increased in Norway over the past decade, and the human cases cluster along the southern coast of Norway. In Norway the distribution and prevalence of TBE virus (TBEV) in tick populations …

A Strain Of Piscine Myocarditis Virus (Pmcv) Infecting Argentina Silus (Ascanius), Torstein Tengs Dr.

Dr. Torstein Tengs

No abstract.

Quantification Of Piscine Reovirus (Prv) At Different Stages Of Atlantic Salmon Salmo Salar Production, Torstein Tengs Dr.

Dr. Torstein Tengs

The newly described piscine reovirus (PRV) appears to be associated with the development of heart and skeletal muscle inflammation (HSMI) in farmed Atlantic salmon Salmo salar L. PRV seems to be ubiquitous among fish in Norwegian salmon farms, but high viral loads and tissue distribution support a causal relationship between virus and disease. In order to improve understanding of the distribution of PRV in the salmon production line, we quantified PRV by using real-time PCR on heart samples collected at different points in the life cycle from pre-smolts to fish ready for slaughter. PRV positive pre-smolts were found in about …

James-Stein Estimation And The Benjamini-Hochberg Procedure, Debashis Ghosh

Debashis Ghosh

For the problem of multiple testing, the Benjamini-Hochberg (B-H) procedure has become a very popular method in applications. Based on a spacings theory representation of the B-H procedure, we are able to motivate the use of shrinkage estimators for modifying the B-H procedure. Several generalizations in the paper are discussed, and the methodology is applied to real and simulated datasets.

Shrinkage In Adaptive Procedures For False Discovery Rate Estimation In Multiple Testing: Structure And Synthesis, Debashis Ghosh

Debashis Ghosh

There has been much interest in the study of adaptive estimation procedures for controlling the false discovery rate (FDR). In this article, we take the direct approach to estimation of FDR of Storey (2002) and show how it can reexpressed as a particular type of shrinkage estimator. This representation leads to natural conditions on finite-sample FDR control for a general class of shrinkage estimators. In addition, many previous proposals from the literature can be unified under this framework for which finite-sample FDR results can be developed. Some asymptotic results are also provided.

Prevalence Of Piscine Myocarditis Virus (Pmcv) In Marine Fish Species, Torstein Tengs Dr.

Dr. Torstein Tengs

No abstract.

Generalized Benjamini-Hochberg Procedures Using Spacings, Debashis Ghosh

Debashis Ghosh

For the problem of multiple testing, the Benjamini-Hochberg (B-H) procedure has become a very popular method in applications. We show how the B-H procedure can be interpreted as a test based on the spacings corresponding to the p-value distributions. Using this equivalence, we develop a class of generalized B-H procedures that maintain control of the false discovery rate in finite-samples. We also consider the effect of correlation on the procedure; simulation studies are used to illustrate the methodology.

Software For Assumption Weighting For Meta-Analysis Of Genomic Data, Debashis Ghosh, Yihan Li

Debashis Ghosh

This is the software that accompanies Li and Ghosh, "Assumption weighting for incorporating heterogeneity into meta-analysis of genomic data."

A Causal Framework For Surrogate Endpoints With Semi-Competing Risks Data, Debashis Ghosh

Debashis Ghosh

In this note, we address the problem of surrogacy using a causal modelling framework that differs substantially from the potential outcomes model that pervades the biostatistical literature. The framework comes from econometrics and conceptualizes direct effects of the surrogate endpoint on the true endpoint. While this framework can incorporate the so-called semi-competing risks data structure, we also derive a fundamental non-identifiability result. Relationships to existing causal modelling frameworks are also discussed.

Propensity Score Modelling In Observational Studies Using Dimension Reduction Methods, Debashis Ghosh

Debashis Ghosh

Conditional independence assumptions are very important in causal inference modelling as well as in dimension reduction methodologies. These are two very strikingly different statistical literatures, and we study links between the two in this article. The concept of covariate sufficiency plays an important role, and we provide theoretical justication when dimension reduction and partial least squares methods will allow for valid causal inference to be performed. The methods are illustrated with application to a medical study and to simulated data.

A Novel Totivirus And Piscine Reovirus (Prv) In Atlantic Salmon (Salmo Salar) With Cardiomyopathy Syndrome (Cms), Torstein Tengs

Dr. Torstein Tengs

BACKGROUNDCardiomyopathy syndrome (CMS) is a severe disease affecting large farmed Atlantic salmon. Mortality often appears without prior clinical signs, typically shortly prior to slaughter. We recently reported the finding and the complete genomic sequence of a novel piscine reovirus (PRV), which is associated with another cardiac disease in Atlantic salmon; heart and skeletal muscle inflammation (HSMI). In the present work we have studied whether PRV or other infectious agents may be involved in the etiology of CMS.RESULTSUsing high throughput sequencing on heart samples from natural outbreaks of CMS and from fish experimentally challenged with material from fish diagnosed with CMS …

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

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 …

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. …

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 …

Detecting Outlier Genes From High-Dimensional Data: A Fuzzy Approach, Debashis Ghosh

Debashis Ghosh

A recent nding in cancer research has been the characterization of previously undis- covered chromosomal abnormalities in several types of solid tumors. This was found based on analyses of high-throughput data from gene expression microarrays and motivated the development of so-called `outlier' tests for dierential expression. One statistical issue was the potential discreteness of the test statistics. Using ideas from fuzzy set theory, we develop fuzzy outlier detection algorithms that have links to ideas in multiple comparisons. Two- and K-sample extensions are considered. The methodology is illustrated by application to two microarray studies.

Links Between Analysis Of Surrogate Endpoints And Endogeneity, Debashis Ghosh, Jeremy M. Taylor, Michael R. Elliott

Debashis Ghosh

There has been substantive interest in the assessment of surrogate endpoints in medical research. These are measures which could potentially replace \true" endpoints in clinical trials and lead to studies that require less follow-up. Recent research in the area has focused on assessments using causal inference frameworks. Beginning with a simple model for associating the surrogate and true endpoints in the population, we approach the problem as one of endogenous covariates. An instrumental variables estimator and general two-stage algorithm is proposed. Existing surrogacy frameworks are then evaluated in the context of the model. A numerical example is used to illustrate …

Meta-Analysis For Surrogacy: Accelerated Failure Time Models And Semicompeting Risks Modelling, Debashis Ghosh, Jeremy M. Taylor, Daniel J. Sargent

Debashis Ghosh

There has been great recent interest in the medical and statistical literature in the assessment and validation of surrogate endpoints as proxies for clinical endpoints in medical studies. More recently, authors have focused on using meta-analytical methods for quanti cation of surrogacy. In this article, we extend existing procedures for analysis based on the accelerated failure time model to this setting. An advantage of this approach relative to proportional hazards model is that it allows for analysis in the semi-competing risks setting, where we constrain the surrogate endpoint to occur before the true endpoint. A novel principal components procedure is …

Spline-Based Models For Predictiveness Curves, Debashis Ghosh, Michael Sabel

Debashis Ghosh

A biomarker is dened to be a biological characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention. The use of biomarkers in cancer has been advocated for a variety of purposes, which include use as surrogate endpoints, early detection of disease, proxies for environmental exposure and risk prediction. We deal with the latter issue in this paper. Several authors have proposed use of the predictiveness curve for assessing the capacity of a biomarker for risk prediction. For most situations, it is reasonable to assume monotonicity of …

Combining Multiple Models With Survival Data: The Phase Algorithm, Debashis Ghosh, Zheng Yuan

Debashis Ghosh

In many scientic studies, one common goal is to develop good prediction rules based on a set of available measurements. This paper proposes a model averaging methodology using proportional hazards regression models to construct new estimators of predicted survival probabilities. A screening step based on an adaptive searching algorithm is used to handle large numbers of covariates. The nite-sample properties of the proposed methodology is assessed using simulation studies. Application of the method to a cancer biomarker study is also given.

Semiparametric Analysis Of Recurrent Events: Artificial Censoring, Truncation, Pairwise Estimation And Inference, Debashis Ghosh

Debashis Ghosh

The analysis of recurrent failure time data from longitudinal studies can be complicated by the presence of dependent censoring. There has been a substantive literature that has developed based on an artificial censoring device. We explore in this article the connection between this class of methods with truncated data structures. In addition, a new procedure is developed for estimation and inference in a joint model for recurrent events and dependent censoring. Estimation proceeds using a mixed U-statistic based estimating function approach. New resampling-based methods for variance estimation and model checking are also described. The methods are illustrated by application to …

Multiple Loci Within The Major Histocompatibility Complex Confer Risk Of Psoriasis, Bing-Jian Feng, Liang-Dan Sun, Razieh Soltani-Arabshahi, Anne M. Bowcock, Rajan P. Nair, Philip Stuart, James T. Elder, Steven J. Schrodi, Ann B. Begovich, Goncalo R. Abecasis, Xue-Jun Zhang, Kristina P. Callis Duffin, Gerald G. Krueger, David E. Goldgar

Steven J Schrodi

Psoriasis is a common inflammatory skin disease characterized by thickened scaly red plaques. Previously we have performed a genome-wide association study (GWAS) on psoriasis with 1,359 cases and 1,400 controls, which were genotyped for 447,249 SNPs. The most significant finding was for SNP rs12191877, which is in tight linkage disequilibrium with HLA-Cw*0602, the consensus risk allele for psoriasis. However, it is not known whether there are other psoriasis loci within the MHC in addition to HLA-C. In the present study, we searched for additional susceptibility loci within the human leukocyte antigen (HLA) region through in-depth analyses of the GWAS data; …

Uniqueprimer - A Web Utility For Design Of Specific Pcr Primers And Probes, Torstein Tengs

Dr. Torstein Tengs

We have developed a web-based tool for design of specific PCR primers and probes. The program allows you to enter primer sequence information as well as an optional probe, and sequence similarity searches (MegaBLAST) will be performed to see if the sequences match the same sequence entry in the specified database. If primers (and probe) match, this will be reported. The program can handle overlapping amplicons, amplification from a single primer, ambiguous bases and other problematic cases.

Hierarchical Hidden Markov Model With Application To Joint Analysis Of Chip-Chip And Chip-Seq Data, Hyungwon Choi, Debashis Ghosh, Zhaohui S. Qin

Debashis Ghosh

Motivation: Identication of transcription factor binding sites (TFBS) is a fundamental problem in understanding the mechanism of gene regulation. The ChIP-chip technology has accelerated this eort by providing a simultaneous genome-wide map of TFBS in a high-throughput fashion. Recently, a sequencing-based ChIP-seq has appeared as a promising alternative that can identify targets with an improved sensitivity/specicity in high resolution. However, studies have suggested that distinct experimental platforms can be complementary in TFBS identication. The availability of data obtained from multiple platforms motivates a meta-analysis for improved identication of candidate motifs.

Results: In this work, we propose a hierarchical hidden Markov …

A Double-Layered Mixture Model For The Joint Analysis Of Dna Copy Number And Gene Expression Data, Debashis Ghosh

Debashis Ghosh

Copy number aberration is a common form of genomic instability in cancer. Gene expression is closely tied to cytogenetic events by the central dogma of molecular biology, and serves as a mediator of copy number changes in disease phenotypes. Accordingly, it is of interest to develop proper statistical methods for jointly analyzing copy number and gene expression data. This work describes a novel Bayesian inferential approach for a double-layered mixture model (DLMM) which directly models the stochastic nature of copy number data and identifies abnormally expressed genes due to aberrant copy number. Simulation studies were conducted to illustrate the robustness …

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 microarrays, differential 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 differential 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 procedures …

A Double-Layered Mixture Model For The Joint Analysis Of Dna Copy Number And Gene Expression Data, Debashis Ghosh

Debashis Ghosh

Copy number aberration is a common form of genomic instability in cancer. Gene expression is closely tied to cytogenetic events by the central dogma of molecular biology, and serves as a mediator of copy number changes in disease phenotypes. Accordingly, it is of interest to develop proper statistical methods for jointly analyzing copy number and gene expression data. This work describes a novel Bayesian inferential approach for a double-layered mixture model (DLMM) which directly models the stochastic nature of copy number data and identifies abnormally expressed genes due to aberrant copy number. Simulation studies were conducted to illustrate the robustness …

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 microarrays, differential 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 differential 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 procedures …

A Quantitative Taqman Mgb Real-Time Polymerase Chain Reaction Based Assay For Detection Of The Causative Agent Of Crayfish Plague Aphanomyces Astaci, Torstein Tengs

Dr. Torstein Tengs

Here we present the development and first validation of a TaqMan minor groove binder (MGB) real-time polymerase chain reaction (RT-PCR) method for quantitative and highly specific detection of Aphanomyces astaci, the causative agent of crayfish plague. The assay specificity was experimentally assessed by testing against DNA representative of closely related oomycetes, and theoretically assessed by additional sequence similarity analyses comparing the primers and probe sequences to available sequences in EMBL/GenBank. The target of the assay is a 59 bp unique sequence motif of A. astaci found in the internal transcribed spacer 1 of the nuclear ribosomal gene cluster. A standard …