Modern likelihood inference for the parameter of skewness: an application to monozygotic twin studies

We consider the use of modern likelihood asymptotics in the construction of confidence intervals for the parameter which determines the skewness of the distribution of the maximum/minimumof an exchangeable bivariate normal randomvector. This distribution represents the reference model for assessing the degree of concordance of a continuos mono-zygotic twin trait when interest focuses on the pairwise maximum or minimum. Simulation studies were conducted to investigate the accuracy of the proposed method and to compare it to available alternatives. Accuracy is evaluated in terms of both coverage probability and expected length of the interval. We, furthermore, illustrate the suitability of our method by re-analyzing the data from a study which compares different measurements taken on the brains of mono-zygotic twins

Cross-Clustering: A Partial Clustering Algorithm with Automatic Estimation of the Number of Clusters

Four of the most common limitations of the many available clustering methods are: i) the lack of a proper strategy to deal with outliers; ii) the need for a good a priori estimate of the number of clusters to obtain reasonable results; iii) the lack of a method able to detect when partitioning of a specific data set is not appropriate; and iv) the dependence of the result on the initialization. Here we propose Cross-clustering (CC), a partial clustering algorithm that overcomes these four limitations by combining the principles of two well established hierarchical clustering algorithms: Ward's minimum variance and Complete-linkage. We validated CC by comparing it with a number of existing clustering methods, including Ward's and Complete-linkage. We show on both simulated and real datasets, that CC performs better than the other methods in terms of: the identification of the correct number of clusters, the identification of outliers, and the determination of real cluster memberships. We used CC to cluster samples in order to identify disease subtypes, and on gene profiles, in order to determine groups of genes with the same behavior. Results obtained on a non-biological dataset show that the method is general enough to be successfully used in such diverse applications. The algorithm has been implemented in the statistical language R and is freely available from the CRAN contributed packages repository

G-quadruplex forming sequences in the genome of all known human viruses: A comprehensive guide

G-quadruplexes are non-canonical nucleic-acid structures that control transcription, replication, and recombination in organisms. G-quadruplexes are present in eukaryotes, prokaryotes, and viruses. In the latter, mounting evidence indicates their key biological activity. Since data on viruses are scattered, we here present a comprehensive analysis of potential quadruplex-forming sequences (PQS) in the genome of all known viruses that can infect humans. We show that occurrence and location of PQSs are features characteristic of each virus class and family. Our statistical analysis proves that their presence within the viral genome is orderly arranged, as indicated by the possibility to correctly assign up to two-thirds of viruses to their exact class based on the PQS classification. For each virus we provide: i) the list of all PQS present in the genome (positive and negative strands), ii) their position in the viral genome, iii) the degree of conservation among strains of each PQS in its genome context, iv) the statistical significance of PQS abundance. This information is accessible from a database to allow the easy navigation of the results: http://www.medcomp.medicina.unipd.it/main_site/doku.php?id=g4virus. The availability of these data will greatly expedite research on G-quadruplex in viruses, with the possibility to accelerate finding therapeutic opportunities to numerous and some fearsome human diseases

The Role of Positron Emission Tomography in Clinical Management of Intraductal Papillary Mucinous Neoplasms of the Pancreas

Intraductal papillary mucinous neoplasms (IPMNs) of the pancreas represent a heterogeneous group of tumors, increasingly diagnosed in clinical practice. An early differential diagnosis between malignant and benign lesions is crucial to patient management and the choice of surgery or observation. The therapeutic approach is currently based on a patient's clinical, biochemical, and morphological characteristics. The latest published International Consensus Guidelines (ICG) make no mention of the role of metabolic assessments of IPMNs. The aim of this study was to review the current literature, examining the role of 18-fluorodeoxyglucose (FDG) positron emission tomography (PET) in IPMN management. An extensive literature review was conducted according to the 2009 Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, and 10 articles were analyzed in detail, focusing on the value of PET as opposed to other standard imaging criteria. Data were retrieved on 419 patients. The 18-FDG-PET proved more sensitive, specific, and accurate than the ICG criteria in detecting malignant IPMNs (reaching 80%, 95%, and 87% vs. 67%, 58%, and 63%, respectively). Metabolic assessments may be used as an additional tool for the appropriate management of patients with doubtful imaging findings

Modern likelihood inference for the parameter of skewness: an application to monozygotic twin studies

We consider the use of modern likelihood asymptotics in the construction of confidence intervals for the parameter which determines the skewness of the distribution of the maximum/minimumof an exchangeable bivariate normal randomvector. This distribution represents the reference model for assessing the degree of concordance of a continuos mono-zygotic twin trait when interest focuses on the pairwise maximum or minimum. Simulation studies were conducted to investigate the accuracy of the proposed method and to compare it to available alternatives. Accuracy is evaluated in terms of both coverage probability and expected length of the interval. We, furthermore, illustrate the suitability of our method by re-analyzing the data from a study which compares different measurements taken on the brains of mono-zygotic twins

Advances in the implementation of higher-order asymptotics

Practical use of modern likelihood asymptotics is still limited by the lack of flexible and easy to use computational tools. The aim of this contribution is to show that the implementation is not as hard as it might look at the first sight. We will illustrate this point by showing how higher-order asymptotics for heteroscedastic regression models may be easily implemented into S-PLU

SIMULAZIONI CONDIZIONATE PER FAMIGLIE DI REGRESSIONE E SCALA

A regression-scale model is of the form y=X\beta+\sigma\epsilon, where X is a fixed nxp design matrix, \beta\in\Real^p an unknown regression coefficient, \sigma>0 a scale parameter, and \epsilon represents an n-dimensional vector of errors whose density is known. Inference is usually made conditionally on the sample configuration a=(y-X\hat\beta)/\hat\sigma, where (\hat\beta,\hat\sigma) are the maximum likelihood estimates. Higher-order asymptotics provide very accurate approximations to exact conditional procedure thus avoiding multidimensional numerical integration. This paper presents how by means of the Metropolis-Hastings algorithm, a powerful Markov Chain Monte Carlo technique, conditional properties of these methods can be assessed. MCMC are necessary, as the conditional distributions involved are only known up to the normalizing constant

Fisher's Legacy: (Pseudo) Likelihood and Some Recent Challenges

Il presente lavoro intende fornire una panoramica sugli sviluppi pi\uf9 recenti ed innovativi nella teoria dell\u2019inferenza basata sulla funzione di verosimiglianza. I metodi saranno illustrati utilizzando due esempi. Il primo si ispira a risultati recenti in \ufb01sica nucleare; il secondo riguarda due sperimentazioni in ambito forestale

Valutazione dell'intercambiabilità ed affidabilità della strumentazione EMDEX(TM) utilizzata nello studio SETIL

none1Il progetto SETIL riguarda uno studio epidemiologico multicentrico italiano sull'eziologia dei tumori del sistema linfoemopoietico e dei neuroblastomi nel bambino attualmente in corso di svolgimento. Uno dei punti chiave dello studio è valutare se e come l'esposizione a campi magnetici a bassissima frequenza (ELF-MF) modifichi il rischio delle patologie oggetto di studio. Il protocollo prevede l'impiego di due diversi strumenti per la misurazione dei campi magnetici ELF. Misure a breve termine (o spot) dovrebbero essere eseguite con strumenti EMDEX II , mentre per le misure prolungate si dovrebbero utilizzare dosimetri del tipo EMDEX Lite , meno precisi (e costosi) dei primi. Sul campo si è, tuttavia, verificata la necessità di adottare il primo dosimetro disponibile, non differenziando, dunque, tra misure spot e misure prolungate, onde evitare tempi di attesa eccessivamente lunghi. La domanda che si pone è se i due strumenti siano intercambiabili, ovvero forniscano, in condizioni sperimentali comparabili, valori equivalenti al fine dell'analisi epidemiologica. Un secondo quesito d'interesse riguarda l'affidabilità dei valori rilevati, ovvero se questi effettivamente rispecchino l'intensità del campo magnetico misurato. // L'obiettivo del presente lavoro è rispondere ai due quesiti posti circa l'intercambiabilità della strumentazione adottata e l'affidabilità delle misure fornite. A questi fini si sono utilizzati i dati ottenuti in due sessioni di taratura degli strumenti utilizzati per la misurazione dei campi magnetici residenziali dei casi e controlli reclutati, effettuate presso il Dipartimento di Ivrea dell'Agenzia Regionale per la Protezione Ambientale (A.R.P.A.) del Piemonte. Si riportano, inoltre, alcune considerazioni circa le implicazioni dei risultati ottenuti sul funzionamento della strumentazione EMDEX per lo studio SETIL.Rapporto Interno no. 02/02, Istituto di Ingegneria Biomedica, Consiglio Nazionale delle RicerchenoneA. R. BrazzaleBrazzale, ALESSANDRA ROSALB