Testing zooplankton secondary production against growth in the marine mysid, "Leptomysis lingvura" (G.O. Sars, 1866)

[EN]Zooplankton growth and secondary production are key input parameters in marine ecosystem modelling, but their direct measurement is difficult to make. Accordingly, zooplanktologists have developed several statistical-based secondary production models. Here, three of these secondary production models are tested in Leptomysis lingvura (Mysidacea, Crustacea). Mysid length was measured in two cultures grown on two different food concentrations. The relationship between length and dry-mass was determined in a pilot study and used to calculate dry-mass from the experimental length data. Growth rates ranged from 0.11 to 0.64 , while secondary production rates ranged from 1.77 to 12.23 mg dry-mass . None of the three selected models were good predictors of growth and secondary production in this species of mysid.

Multiple testing in spatial epidemiology: a Bayesian approach

In this work we aim to propose a new approach for preliminary epidemiological studies on Standardized Mortality Ratios (SMR) collected in many spatial regions. A preliminary study on SMRs aims to formulate hypotheses to be investigated via individual epidemiological studies that avoid bias carried on by aggregated analyses. Starting from collecting disease counts and calculating expected disease counts by means of reference population disease rates, in each area an SMR is derived as the MLE under the Poisson assumption on each observation. Such estimators have high standard errors in small areas, i.e. where the expected count is low either because of the low population underlying the area or the rarity of the disease under study. Disease mapping models and other techniques for screening disease rates among the map aiming to detect anomalies and possible high-risk areas have been proposed in literature according to the classic and the Bayesian paradigm. Our proposal is approaching this issue by a decision-oriented method, which focus on multiple testing control, without however leaving the preliminary study perspective that an analysis on SMR indicators is asked to. We implement the control of the FDR, a quantity largely used to address multiple comparisons problems in the eld of microarray data analysis but which is not usually employed in disease mapping. Controlling the FDR means providing an estimate of the FDR for a set of rejected null hypotheses. The small areas issue arises diculties in applying traditional methods for FDR estimation, that are usually based only on the p-values knowledge (Benjamini and Hochberg, 1995; Storey, 2003). Tests evaluated by a traditional p-value provide weak power in small areas, where the expected number of disease cases is small. Moreover tests cannot be assumed as independent when spatial correlation between SMRs is expected, neither they are identical distributed when population underlying the map is heterogeneous. The Bayesian paradigm oers a way to overcome the inappropriateness of p-values based methods. Another peculiarity of the present work is to propose a hierarchical full Bayesian model for FDR estimation in testing many null hypothesis of absence of risk.We will use concepts of Bayesian models for disease mapping, referring in particular to the Besag York and Mollié model (1991) often used in practice for its exible prior assumption on the risks distribution across regions. The borrowing of strength between prior and likelihood typical of a hierarchical Bayesian model takes the advantage of evaluating a singular test (i.e. a test in a singular area) by means of all observations in the map under study, rather than just by means of the singular observation. This allows to improve the power test in small areas and addressing more appropriately the spatial correlation issue that suggests that relative risks are closer in spatially contiguous regions. The proposed model aims to estimate the FDR by means of the MCMC estimated posterior probabilities b i's of the null hypothesis (absence of risk) for each area. An estimate of the expected FDR conditional on data (\FDR) can be calculated in any set of b i's relative to areas declared at high-risk (where thenull hypothesis is rejected) by averaging the b i's themselves. The\FDR can be used to provide an easy decision rule for selecting high-risk areas, i.e. selecting as many as possible areas such that the\FDR is non-lower than a prexed value; we call them\FDR based decision (or selection) rules. The sensitivity and specicity of such rule depend on the accuracy of the FDR estimate, the over-estimation of FDR causing a loss of power and the under-estimation of FDR producing a loss of specicity. Moreover, our model has the interesting feature of still being able to provide an estimate of relative risk values as in the Besag York and Mollié model (1991). A simulation study to evaluate the model performance in FDR estimation accuracy, sensitivity and specificity of the decision rule, and goodness of estimation of relative risks, was set up. We chose a real map from which we generated several spatial scenarios whose counts of disease vary according to the spatial correlation degree, the size areas, the number of areas where the null hypothesis is true and the risk level in the latter areas. In summarizing simulation results we will always consider the FDR estimation in sets constituted by all b i's selected lower than a threshold t. We will show graphs of the\FDR and the true FDR (known by simulation) plotted against a threshold t to assess the FDR estimation. Varying the threshold we can learn which FDR values can be accurately estimated by the practitioner willing to apply the model (by the closeness between\FDR and true FDR). By plotting the calculated sensitivity and specicity (both known by simulation) vs the\FDR we can check the sensitivity and specicity of the corresponding\FDR based decision rules. For investigating the over-smoothing level of relative risk estimates we will compare box-plots of such estimates in high-risk areas (known by simulation), obtained by both our model and the classic Besag York Mollié model. All the summary tools are worked out for all simulated scenarios (in total 54 scenarios). Results show that FDR is well estimated (in the worst case we get an overestimation, hence a conservative FDR control) in small areas, low risk levels and spatially correlated risks scenarios, that are our primary aims. In such scenarios we have good estimates of the FDR for all values less or equal than 0.10. The sensitivity of\FDR based decision rules is generally low but specicity is high. In such scenario the use of\FDR = 0:05 or\FDR = 0:10 based selection rule can be suggested. In cases where the number of true alternative hypotheses (number of true high-risk areas) is small, also FDR = 0:15 values are well estimated, and \FDR = 0:15 based decision rules gains power maintaining an high specicity. On the other hand, in non-small areas and non-small risk level scenarios the FDR is under-estimated unless for very small values of it (much lower than 0.05); this resulting in a loss of specicity of a\FDR = 0:05 based decision rule. In such scenario\FDR = 0:05 or, even worse,\FDR = 0:1 based decision rules cannot be suggested because the true FDR is actually much higher. As regards the relative risk estimation, our model achieves almost the same results of the classic Besag York Molliè model. For this reason, our model is interesting for its ability to perform both the estimation of relative risk values and the FDR control, except for non-small areas and large risk level scenarios. A case of study is nally presented to show how the method can be used in epidemiology.

The electron antineutrino angular correlation coefficient a in free neutron decay: Testing the standard model with the aSPECT-spectrometer

The beta-decay of free neutrons is a strongly over-determined process in the Standard Model (SM) of Particle Physics and is described by a multitude of observables. Some of those observables are sensitive to physics beyond the SM. For example, the correlation coefficients of the involved particles belong to them. The spectrometer aSPECT was designed to measure precisely the shape of the proton energy spectrum and to extract from it the electron anti-neutrino angular correlation coefficient "a". A first test period (2005/ 2006) showed the “proof-of-principles”. The limiting influence of uncontrollable background conditions in the spectrometer made it impossible to extract a reliable value for the coefficient "a" (publication: Baessler et al., 2008, Europhys. Journ. A, 38, p.17-26). A second measurement cycle (2007/ 2008) aimed to under-run the relative accuracy of previous experiments (Stratowa et al. (1978), Byrne et al. (2002)) da/a =5%. I performed the analysis of the data taken there which is the emphasis of this doctoral thesis. A central point are background studies. The systematic impact of background on a was reduced to da/a(syst.)=0.61 %. The statistical accuracy of the analyzed measurements is da/a(stat.)=1.4 %. Besides, saturation effects of the detector electronics were investigated which were initially observed. These turned out not to be correctable on a sufficient level. An applicable idea how to avoid the saturation effects will be discussed in the last chapter.

Earthquake forecasting and seismic hazard analysis: some insights on the testing phase and the modeling

This thesis is divided in three chapters. In the first chapter we analyse the results of the world forecasting experiment run by the Collaboratory for the Study of Earthquake Predictability (CSEP). We take the opportunity of this experiment to contribute to the definition of a more robust and reliable statistical procedure to evaluate earthquake forecasting models. We first present the models and the target earthquakes to be forecast. Then we explain the consistency and comparison tests that are used in CSEP experiments to evaluate the performance of the models. Introducing a methodology to create ensemble forecasting models, we show that models, when properly combined, are almost always better performing that any single model. In the second chapter we discuss in depth one of the basic features of PSHA: the declustering of the seismicity rates. We first introduce the Cornell-McGuire method for PSHA and we present the different motivations that stand behind the need of declustering seismic catalogs. Using a theorem of the modern probability (Le Cam's theorem) we show that the declustering is not necessary to obtain a Poissonian behaviour of the exceedances that is usually considered fundamental to transform exceedance rates in exceedance probabilities in the PSHA framework. We present a method to correct PSHA for declustering, building a more realistic PSHA. In the last chapter we explore the methods that are commonly used to take into account the epistemic uncertainty in PSHA. The most widely used method is the logic tree that stands at the basis of the most advanced seismic hazard maps. We illustrate the probabilistic structure of the logic tree, and then we show that this structure is not adequate to describe the epistemic uncertainty. We then propose a new probabilistic framework based on the ensemble modelling that properly accounts for epistemic uncertainties in PSHA.

Implementazione Libreria C per il Multiple Testing correction

Nell'era genomica moderna, la mole di dati generata dal sequenziamento genetico è diventata estremamente elevata. L’analisi di dati genomici richiede l’utilizzo di metodi di significatività statistica per quantificare la robustezza delle correlazioni individuate nei dati. La significatività statistica ci permette di capire se le relazioni nei dati che stiamo analizzando abbiano effettivamente un peso statistico, cioè se l’evento che stiamo analizzando è successo “per caso” o è effettivamente corretto pensare che avvenga con una probabilità utile. Indipendentemente dal test statistico utilizzato, in presenza di test multipli di verifica (“Multiple Testing Hypothesis”) è necessario utilizzare metodi per la correzione della significatività statistica (“Multiple Testing Correction”). Lo scopo di questa tesi è quello di rendere disponibili le implementazioni dei più noti metodi di correzione della significatività statistica. È stata creata una raccolta di questi metodi, sottoforma di libreria, proprio perché nel panorama bioinformatico moderno non è stato trovato nulla del genere.

The Permanent Income Hypothesis: A Test on Czech Privatisation

Since the late eighties, economists have been regarding the transition from command to market economies in Central and Eastern Europe with intense interest. In addition to studying the transition per se, they have begun using the region as a testing ground on which to investigate the validity of certain classic economic propositions. In his research, comprising three articles written in English and totalling 40 pages, Mr. Hanousek uses the so-called "Czech national experiment" (voucher privatisation scheme) to test the permanent income hypothesis (PIH). He took as his inspiration Kreinin's recommendation: "Since data concerning the behaviour of windfall income recipients is relatively scanty, and since such data can constitute an important test of the permanent income hypothesis, it is of interest to bring to bear on the hypothesis whatever information is available". Mr. Hanousek argues that, since the transfer of property to Czech citizens from 1992 to 1994 through the voucher scheme was not anticipated, it can be regarded as windfall income. The average size of the windfall was more than three month's salary and over 60 percent of the Czech population received this unexpected income. Furthermore, there are other reasons for conducting such an analysis in the Czech Republic. Firstly, the privatisation process took place quickly. Secondly, both the economy and consumer behaviour have been very stable. Thirdly, out of a total population of 10 million Czech citizens, an astonishing 6 million, that is, virtually every household, participated in the scheme. Thus Czech voucher privatisation provides a sample for testing the PIH almost equivalent to a full population, thus avoiding problems with the distribution of windfalls. Compare this, for instance with the fact that only 4% of the Israeli urban population received personal restitution from Germany, while the number of veterans who received the National Service Life Insurance Dividends amounted to less than 9% of the US population and were concentrated in certain age groups. But to begin with, Mr. Hanousek considers the question of whether the public percieves the transfer from the state to individual as an increase in net wealth. It can be argued that the state is only divesting itself of assets that would otherwise provide a future source of transfers. According to this argument, assigning these assets to individuals creates an offsetting change in the present value of potential future transfers so that individuals are no better off after the transfer. Mr. Hanousek disagrees with this approach. He points out that a change in the ownership of inefficient state-owned enterprises should lead to higher efficiency, which alone increases the value of enterprises and creates a windfall increase in citizens' portfolios. More importantly, the state and individuals had very different preferences during the transition. Despite government propaganda, it is doubtful that citizens of former communist countries viewed government-owned enterprises as being operated in the citizens' best interest. Moreover, it is unlikely that the public fully comprehended the sophisticated links between the state budget, state-owned enterprises, and transfers to individuals. Finally, the transfers were not equal across the population. Mr. Hanousek conducted a survey on 1263 individuals, dividing them into four monthly earnings categories. After determining whether the respondent had participated in the voucher process, he asked those who had how much of what they received from voucher privatisation had been (a) spent on goods and services, (b) invested elsewhere, (c) transferred to newly emerging pension funds, (d) given to a family member, and (e) retained in their original form as an investment. Both the mean and the variance of the windfall rise with income. He obtained similar results with respect to education, where the mean (median) windfall for those with a basic school education was 13,600 Czech Crowns (CZK), a figure that increased to 15,000 CZK for those with a high school education without exams, 19,900 CZK for high school graduates with exams, and 24,600 CZK for university graduates. Mr. Hanousek concludes that it can be argued that higher income (and better educated) groups allocated their vouchers or timed the disposition of their shares better. He turns next to an analysis of how respondents reported using their windfalls. The key result is that only a relatively small number of individuals reported spending on goods. Overall, the results provide strong support for the permanent income hypothesis, the only apparent deviation being the fact that both men and women aged 26 to 35 apparently consume more than they should if the windfall were annuitised. This finding is still fully consistent with the PIH, however, if this group is at a stage in their life-cycle where, without the windfall, they would be borrowing to finance consumption associated with family formation etc. Indeed, the PIH predicts that individuals who would otherwise borrow to finance consumption would consume the windfall up to the level equal to the annuitised fraction of the increase in lifetime income plus the full amount of the previously planned borrowing for consumption. Greater consumption would then be financed, not from investing the windfall, but from avoidance of future repayment obligations for debts that would have been incurred without the windfall.

A graph theoretic approach to testing associations between disparate sources of functional genomic data

The last few years have seen the advent of high-throughput technologies to analyze various properties of the transcriptome and proteome of several organisms. The congruency of these different data sources, or lack thereof, can shed light on the mechanisms that govern cellular function. A central challenge for bioinformatics research is to develop a unified framework for combining the multiple sources of functional genomics information and testing associations between them, thus obtaining a robust and integrated view of the underlying biology. We present a graph theoretic approach to test the significance of the association between multiple disparate sources of functional genomics data by proposing two statistical tests, namely edge permutation and node label permutation tests. We demonstrate the use of the proposed tests by finding significant association between a Gene Ontology-derived "predictome" and data obtained from mRNA expression and phenotypic experiments for Saccharomyces cerevisiae. Moreover, we employ the graph theoretic framework to recast a surprising discrepancy presented in Giaever et al. (2002) between gene expression and knockout phenotype, using expression data from a different set of experiments.

Pain relief in ventilated preterms during endotracheal suctioning: a randomized controlled trial

BACKGROUND: In Switzerland approximately 8% of infants are born prematurely. Some of them undergo mechanical ventilation including endotracheal suctioning (ETS). ETS is one of the most frequently performed interventions and is linked to stress and pain, but its treatment is controversial. In Switzerland there is a lack of standardisation in pain relief for ETS. AIMS: To test the hypothesis that an intermittent dose of morphine reduces pain during ETS and that subsequent multisensorial stimulation (MSS), as a non pharmacological comforting intervention, helps infants to recover from experienced pain. METHOD: A randomized placebo controlled trial in two tertiary neonatal intensive care units (NICU) with a sample of 30 mechanically ventilated preterm infants was conducted. Pain was measured by three pain assessment tools (Bernese Pain Scale for Neonates, Premature Infant Pain Profile and Visual Analogue Scale) RESULTS: Morphine did not lead to any pain relief from ETS as measured by three pain scales. Nor did the comforting intervention of MSS show any effect. Repeated-measure analysis of variance for the within and between groups comparison showed no statistical significance. CONCLUSIONS: The administration of morphine for pain relief in ventilated preterm neonates during ETS remains questionable and the use of MSS as a comforting intervention after painful stimulus cannot be recommended. The validity testing of the instruments for this patient population should undergo a systematic validation trajectory. Future research should focus on options among non pharmacological interventions for relieving pain during ETS.

STATISTICAL METHODS FOR RARE AND COMMON VARIANT ASSOCIATION STUDIES

Complex human diseases are a major challenge for biological research. The goal of my research is to develop effective methods for biostatistics in order to create more opportunities for the prevention and cure of human diseases. This dissertation proposes statistical technologies that have the ability of being adapted to sequencing data in family-based designs, and that account for joint effects as well as gene-gene and gene-environment interactions in the GWA studies. The framework includes statistical methods for rare and common variant association studies. Although next-generation DNA sequencing technologies have made rare variant association studies feasible, the development of powerful statistical methods for rare variant association studies is still underway. Chapter 2 demonstrates two adaptive weighting methods for rare variant association studies based on family data for quantitative traits. The results show that both proposed methods are robust to population stratification, robust to the direction and magnitude of the effects of causal variants, and more powerful than the methods using weights suggested by Madsen and Browning [2009]. In Chapter 3, I extended the previously proposed test for Testing the effect of an Optimally Weighted combination of variants (TOW) [Sha et al., 2012] for unrelated individuals to TOW &ndash F, TOW for Family &ndash based design. Simulation results show that TOW &ndash F can control for population stratification in wide range of population structures including spatially structured populations, is robust to the directions of effect of causal variants, and is relatively robust to percentage of neutral variants. In GWA studies, this dissertation consists of a two &ndash locus joint effect analysis and a two-stage approach accounting for gene &ndash gene and gene &ndash environment interaction. Chapter 4 proposes a novel two &ndash stage approach, which is promising to identify joint effects, especially for monotonic models. The proposed approach outperforms a single &ndash marker method and a regular two &ndash stage analysis based on the two &ndash locus genotypic test. In Chapter 5, I proposed a gene &ndash based two &ndash stage approach to identify gene &ndash gene and gene &ndash environment interactions in GWA studies which can include rare variants. The two &ndash stage approach is applied to the GAW 17 dataset to identify the interaction between KDR gene and smoking status.

Testing an alternative search algorithm for compound identification with the 'Wiley Registry of Tandem Mass Spectral Data. MSforID'

A tandem mass spectral database system consists of a library of reference spectra and a search program. State-of-the-art search programs show a high tolerance for variability in compound-specific fragmentation patterns produced by collision-induced decomposition and enable sensitive and specific 'identity search'. In this communication, performance characteristics of two search algorithms combined with the 'Wiley Registry of Tandem Mass Spectral Data, MSforID' (Wiley Registry MSMS, John Wiley and Sons, Hoboken, NJ, USA) were evaluated. The search algorithms tested were the MSMS search algorithm implemented in the NIST MS Search program 2.0g (NIST, Gaithersburg, MD, USA) and the MSforID algorithm (John Wiley and Sons, Hoboken, NJ, USA). Sample spectra were acquired on different instruments and, thus, covered a broad range of possible experimental conditions or were generated in silico. For each algorithm, more than 30,000 matches were performed. Statistical evaluation of the library search results revealed that principally both search algorithms can be combined with the Wiley Registry MSMS to create a reliable identification tool. It appears, however, that a higher degree of spectral similarity is necessary to obtain a correct match with the NIST MS Search program. This characteristic of the NIST MS Search program has a positive effect on specificity as it helps to avoid false positive matches (type I errors), but reduces sensitivity. Thus, particularly with sample spectra acquired on instruments differing in their Setup from tandem-in-space type fragmentation, a comparably higher number of false negative matches (type II errors) were observed by searching the Wiley Registry MSMS.