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Thèses sur le sujet « Bayes False discovery rate »

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Publié le 9 mars 2023

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1

DI, BRISCO AGNESE MARIA. "Statistical Network Analysis: a Multiple Testing Approach." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2015. http://hdl.handle.net/10281/96090.

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The problem of identifying connections between nodes in a network model is of fundamental importance in the analysis of brain networks because each node represents a specific brain region that can potentially be connected to other brain regions by means of functional relations; the dynamical behavior of each node can be quantified by adopting a correlation measure among time series. In this contest, the whole set of links between nodes in a network can be represented by means of an adjacency matrix with high dimension, that can be obtained by performing a huge number of simultaneous tests on

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Rahal, Abbas. "Bayesian Methods Under Unknown Prior Distributions with Applications to The Analysis of Gene Expression Data." Thesis, Université d'Ottawa / University of Ottawa, 2021. http://hdl.handle.net/10393/42408.

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The local false discovery rate (LFDR) is one of many existing statistical methods that analyze multiple hypothesis testing. As a Bayesian quantity, the LFDR is based on the prior probability of the null hypothesis and a mixture distribution of null and non-null hypothesis. In practice, the LFDR is unknown and needs to be estimated. The empirical Bayes approach can be used to estimate that mixture distribution. Empirical Bayes does not require complete information about the prior and hyper prior distributions as in hierarchical Bayes. When we do not have enough information at the prior level

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Liu, Fang. "New Results on the False Discovery Rate." Diss., Temple University Libraries, 2010. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/96718.

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Statistics<br>Ph.D.<br>The false discovery rate (FDR) introduced by Benjamini and Hochberg (1995) is perhaps the most standard error controlling measure being used in a wide variety of applications involving multiple hypothesis testing. There are two approaches to control the FDR - the fixed error rate approach of Benjamini and Hochberg (BH, 1995) where a rejection region is determined with the FDR below a fixed level and the estimation based approach of Storey (2002) where the FDR is estimated for a fixed rejection region before it is controlled. In this proposal, we concentrate on both these

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Miller, Ryan. "Marginal false discovery rate approaches to inference on penalized regression models." Diss., University of Iowa, 2018. https://ir.uiowa.edu/etd/6474.

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Data containing large number of variables is becoming increasingly more common and sparsity inducing penalized regression methods, such the lasso, have become a popular analysis tool for these datasets due to their ability to naturally perform variable selection. However, quantifying the importance of the variables selected by these models is a difficult task. These difficulties are compounded by the tendency for the most predictive models, for example those which were chosen using procedures like cross-validation, to include substantial amounts of noise variables with no real relationship wit

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Wong, Adrian Kwok-Hang. "False discovery rate controller for functional brain parcellation using resting-state fMRI." Thesis, University of British Columbia, 2016. http://hdl.handle.net/2429/58332.

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Parcellation of brain imaging data is desired for proper neurological interpretation in resting-state functional magnetic resonance imaging (rs-fMRI) data. Some methods require specifying a number of parcels and using model selection to determine the number of parcels with rs-fMRI data. However, this generalization does not fit with all subjects in a given dataset. A method has been proposed using parametric formulas for the distribution of modularity in random networks to determine the statistical significance between parcels. In this thesis, we propose an agglomerative clustering algorithm u

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Kubat, Jamie. "Comparing Dunnett's Test with the False Discovery Rate Method: A Simulation Study." Thesis, North Dakota State University, 2013. https://hdl.handle.net/10365/27025.

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Recently, the idea of multiple comparisons has been criticized because of its lack of power in datasets with a large number of treatments. Many family-wise error corrections are far too restrictive when large quantities of comparisons are being made. At the other extreme, a test like the least significant difference does not control the family-wise error rate, and therefore is not restrictive enough to identify true differences. A solution lies in multiple testing. The false discovery rate (FDR) uses a simple algorithm and can be applied to datasets with many treatments. The current resea

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Guo, Ruijuan. "Sample comparisons using microarrays -- application of false discovery rate and quadratic logistic regression." Worcester, Mass. : Worcester Polytechnic Institute, 2007. http://www.wpi.edu/Pubs/ETD/Available/etd-010808-173747/.

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Guo, Ruijuan. "Sample comparisons using microarrays: - Application of False Discovery Rate and quadratic logistic regression." Digital WPI, 2008. https://digitalcommons.wpi.edu/etd-theses/28.

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In microarray analysis, people are interested in those features that have different characters in diseased samples compared to normal samples. The usual p-value method of selecting significant genes either gives too many false positives or cannot detect all the significant features. The False Discovery Rate (FDR) method controls false positives and at the same time selects significant features. We introduced Benjamini's method and Storey's method to control FDR, applied the two methods to human Meningioma data. We found that Benjamini's method is more conservative and that, after the number of

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Dalmasso, Cyril. "Estimation du positive False Discovery Rate dans le cadre d'études comparatives en génomique." Paris 11, 2006. http://www.theses.fr/2006PA11T015.

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Liley, Albert James. "Statistical co-analysis of high-dimensional association studies." Thesis, University of Cambridge, 2017. https://www.repository.cam.ac.uk/handle/1810/270628.

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Modern medical practice and science involve complex phenotypic definitions. Understanding patterns of association across this range of phenotypes requires co-analysis of high-dimensional association studies in order to characterise shared and distinct elements. In this thesis I address several problems in this area, with a general linking aim of making more efficient use of available data. The main application of these methods is in the analysis of genome-wide association studies (GWAS) and similar studies. Firstly, I developed methodology for a Bayesian conditional false discovery rate (cFDR)

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Benditkis, Julia [Verfasser], Arnold [Akademischer Betreuer] Janssen, and Helmut [Akademischer Betreuer] Finner. "Martingale Methods for Control of False Discovery Rate and Expected Number of False Rejections / Julia Benditkis. Gutachter: Arnold Janssen ; Helmut Finner." Düsseldorf : Universitäts- und Landesbibliothek der Heinrich-Heine-Universität Düsseldorf, 2015. http://d-nb.info/1077295170/34.

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Iyer, Vishwanath. "An adaptive single-step FDR controlling procedure." Diss., Temple University Libraries, 2010. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/75410.

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Statistics<br>Ph.D.<br>This research is focused on identifying a single-step procedure that, upon adapting to the data through estimating the unknown parameters, would asymptotically control the False Discovery Rate when testing a large number of hypotheses simultaneously, and exploring some of the characteristics of this procedure.<br>Temple University--Theses

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Gomez, Kayeromi Donoukounmahou. "A Comparison of False Discovery Rate Method and Dunnett's Test for a Large Number of Treatments." Diss., North Dakota State University, 2015. http://hdl.handle.net/10365/24842.

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It has become quite common nowadays to perform multiple tests simultaneously in order to detect differences of a certain trait among groups. This often leads to an inflated probability of at least one Type I Error, a rejection of a null hypothesis when it is in fact true. This inflation generally leads to a loss of power of the test especially in multiple testing and multiple comparisons. The aim of the research is to use simulation to address what a researcher should do to determine which treatments are significantly different from the control when there is a large number of treatments and th

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ALHARBI, YOUSEF S. "RECOVERING SPARSE DIFFERENCES BETWEEN TWO HIGH-DIMENSIONAL COVARIANCE MATRICES." Kent State University / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=kent1500392318023941.

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Jesus, Marcelo de. "Falso positivo na performance dos fundos de investimento com gestão ativa no Brasil: mensurando sorte dos gestores nos alfas estimados." Universidade Presbiteriana Mackenzie, 2011. http://tede.mackenzie.br/jspui/handle/tede/770.

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Made available in DSpace on 2016-03-15T19:30:42Z (GMT). No. of bitstreams: 1 Marcelo de Jesus.pdf: 753815 bytes, checksum: 4b3631ad6c0a3a4e6928e2b70685850d (MD5) Previous issue date: 2011-02-01<br>This study investigates, for the period between 2002 and 2009, what is the impact of luck on the performance of stocks mutual funds managers with active management in Brazil to surpass its benchmark. To that purpose, we used a new method, the False Discovery Rate approach - FDR to empirically test those impact. To measure precisely luck and unluck, ig, the frequency of false positives (Type I error

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Qian, Yi. "Topics in multiple hypotheses testing." Texas A&M University, 2005. http://hdl.handle.net/1969.1/4754.

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It is common to test many hypotheses simultaneously in the application of statistics. The probability of making a false discovery grows with the number of statistical tests performed. When all the null hypotheses are true, and the test statistics are indepen- dent and continuous, the error rates from the family wise error rate (FWER)- and the false discovery rate (FDR)-controlling procedures are equal to the nominal level. When some of the null hypotheses are not true, both procedures are conservative. In the first part of this study, we review the background of the problem and propose methods

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Clements, Nicolle. "Multiple Testing in Grouped Dependent Data." Diss., Temple University Libraries, 2013. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/253695.

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Statistics<br>Ph.D.<br>This dissertation is focused on multiple testing procedures to be used in data that are naturally grouped or possess a spatial structure. We propose `Two-Stage' procedure to control the False Discovery Rate (FDR) in situations where one-sided hypothesis testing is appropriate, such as astronomical source detection. Similarly, we propose a `Three-Stage' procedure to control the mixed directional False Discovery Rate (mdFDR) in situations where two-sided hypothesis testing is appropriate, such as vegetation monitoring in remote sensing NDVI data. The Two and Three-Stage pr

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Abbas, Aghababazadeh Farnoosh. "Estimating the Local False Discovery Rate via a Bootstrap Solution to the Reference Class Problem: Application to Genetic Association Data." Thesis, Université d'Ottawa / University of Ottawa, 2015. http://hdl.handle.net/10393/33367.

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Modern scientific technology such as microarrays, imaging devices, genome-wide association studies or social science surveys provide statisticians with hundreds or even thousands of tests to consider simultaneously. Testing many thousands of null hypotheses may increase the number of Type $I$ errors. In large-scale hypothesis testing, researchers can use different statistical techniques such as family-wise error rates, false discovery rates, permutation methods, local false discovery rate, where all available data usually should be analyzed together. In applications, the thousands of tests are

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Bancroft, Timothy J. "Estimating the number of true null hypotheses and the false discovery rate from multiple discrete non-uniform permutation p-values." [Ames, Iowa : Iowa State University], 2009. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3389284.

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SALA, SARA. "Statistical analysis of brain network." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2013. http://hdl.handle.net/10281/43723.

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Recent developments in the complex networks analysis, based largely on graph theory, have been used to study the brain network organization. The brain is a complex system that can be represented by a graph. A graph is a mathematical representation which can be useful to study the connectivity of the brain. Nodes in the brain can be identified dividing its volume in regions of interest and links can be identified calculating a measure of dependence between pairs of regions whose activation signal, measured by functional magnetic resonance imaging (fMRI) techniques, represents the strength

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Heesen, Philipp [Verfasser], Arnold [Akademischer Betreuer] Janssen, and Helmut [Akademischer Betreuer] Finner. "Adaptive step up tests for the false discovery rate (FDR) under independence and dependence / Philipp Heesen. Gutachter: Arnold Janssen ; Helmut Finner." Düsseldorf : Universitäts- und Landesbibliothek der Heinrich-Heine-Universität Düsseldorf, 2015. http://d-nb.info/1064694039/34.

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Yi, Hui. "Assessment of Penalized Regression for Genome-wide Association Studies." Diss., Virginia Tech, 2014. http://hdl.handle.net/10919/64845.

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The data from genome-wide association studies (GWAS) in humans are still predominantly analyzed using single marker association methods. As an alternative to Single Marker Analysis (SMA), all or subsets of markers can be tested simultaneously. This approach requires a form of Penalized Regression (PR) as the number of SNPs is much larger than the sample size. Here we review PR methods in the context of GWAS, extend them to perform penalty parameter and SNP selection by False Discovery Rate (FDR) control, and assess their performance (including penalties incorporating linkage disequilibrium) in

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Breheny, Patrick John. "Regularized methods for high-dimensional and bi-level variable selection." Diss., University of Iowa, 2009. https://ir.uiowa.edu/etd/325.

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Many traditional approaches cease to be useful when the number of variables is large in comparison with the sample size. Penalized regression methods have proved to be an attractive approach, both theoretically and empirically, for dealing with these problems. This thesis focuses on the development of penalized regression methods for high-dimensional variable selection. The first part of this thesis deals with problems in which the covariates possess a grouping structure that can be incorporated into the analysis to select important groups as well as important members of those groups. I introd

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Labare, Mathieu. "Search for cosmic sources of high energy neutrinos with the AMANDA-II detector." Doctoral thesis, Universite Libre de Bruxelles, 2010. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/210183.

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AMANDA-II est un télescope à neutrinos composé d'un réseau tri-dimensionnel de senseurs optiques déployé dans la glace du Pôle Sud.<p>Son principe de détection repose sur la mise en évidence de particules secondaires chargées émises lors de l'interaction d'un neutrino de haute énergie (> 100 GeV) avec la matière environnant le détecteur, sur base de la détection de rayonnement Cerenkov.<p><p>Ce travail est basé sur les données enregistrées par AMANDA-II entre 2000 et 2006, afin de rechercher des sources cosmiques de neutrinos.<p>Le signal recherché est affecté d'un bruit de fond important de m

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Shen, Shihao. "Statistical methods for deep sequencing data." Diss., University of Iowa, 2012. https://ir.uiowa.edu/etd/5059.

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Ultra-deep RNA sequencing has become a powerful approach for genome-wide analysis of pre-mRNA alternative splicing. We develop MATS (Multivariate Analysis of Transcript Splicing), a Bayesian statistical framework for flexible hypothesis testing of differential alternative splicing patterns on RNA-Seq data. MATS uses a multivariate uniform prior to model the between-sample correlation in exon splicing patterns, and a Markov chain Monte Carlo (MCMC) method coupled with a simulation-based adaptive sampling procedure to calculate the P value and false discovery rate (FDR) of differential alternati

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Scott, Nigel A. "An Application of Armitage Trend Test to Genome-wide Association Studies." Digital Archive @ GSU, 2009. http://digitalarchive.gsu.edu/math_theses/74.

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Genome-wide Association (GWA) studies have become a widely used method for analyzing genetic data. It is useful in detecting associations that may exist between particular alleles and diseases of interest. This thesis investigates the dataset provided from problem 1 of the Genetic Analysis Workshop 16 (GAW 16). The dataset consists of GWA data from the North American Rheumatoid Arthritis Consortium (NARAC). The thesis attempts to determine a set of single nucleotide polymorphisms (SNP) that are associated significantly with rheumatoid arthritis. Moreover, this thesis also attempts to address t

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Xu, Yihuan. "ROBUST ESTIMATION OF THE PARAMETERS OF g - and - h DISTRIBUTIONS, WITH APPLICATIONS TO OUTLIER DETECTION." Diss., Temple University Libraries, 2014. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/294733.

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Statistics<br>Ph.D.<br>The g - and - h distributional family is generated from a relatively simple transformation of the standard normal. By changing the skewness and elongation parameters g and h, this distributional family can approximate a broad spectrum of commonly used distributional shapes, such as normal, lognormal, Weibull and exponential. Consequently, it is easy to use in simulation studies and has been applied in multiple areas, including risk management, stock return analysis and missing data imputation studies. The current available methods to estimate the g - and - h distribution

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Nascimento, Guilherme Batista do [UNESP]. "Estratégias de imputação e associação genômica com dados de sequenciamento para características de produção de leite na raça Gir." Universidade Estadual Paulista (UNESP), 2018. http://hdl.handle.net/11449/153060.

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Submitted by Guilherme Batista do Nascimento null (guilhermebn@msn.com) on 2018-03-16T12:24:54Z No. of bitstreams: 1 Tese_Guilherme_Batista_do_Nascimento.pdf: 1770231 bytes, checksum: ad03948ecc7b09b89d46d26b7c9e3bf8 (MD5)<br>Approved for entry into archive by Alexandra Maria Donadon Lusser Segali null (alexmar@fcav.unesp.br) on 2018-03-16T19:03:02Z (GMT) No. of bitstreams: 1 nascimento_gb_dr_jabo.pdf: 1770231 bytes, checksum: ad03948ecc7b09b89d46d26b7c9e3bf8 (MD5)<br>Made available in DSpace on 2018-03-16T19:03:02Z (GMT). No. of bitstreams: 1 nascimento_gb_dr_jabo.pdf: 1770231 bytes, chec

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Manandhr-Shrestha, Nabin K. "Statistical Learning and Behrens Fisher Distribution Methods for Heteroscedastic Data in Microarray Analysis." Scholar Commons, 2010. http://scholarcommons.usf.edu/etd/3513.

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The aim of the present study is to identify the di®erentially expressed genes be- tween two di®erent conditions and apply it in predicting the class of new samples using the microarray data. Microarray data analysis poses many challenges to the statis- ticians because of its high dimensionality and small sample size, dubbed as "small n large p problem". Microarray data has been extensively studied by many statisticians and geneticists. Generally, it is said to follow a normal distribution with equal vari- ances in two conditions, but it is not true in general. Since the number of replications

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Mogrovejo, Carrasco Daniel Estuardo. "Enhancing Pavement Surface Macrotexture Characterization." Diss., Virginia Tech, 2015. http://hdl.handle.net/10919/51957.

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One of the most important objectives for transportation engineers is to understand pavement surface properties and their positive and negative effects on the user. This can improve the design of the infrastructure, adequacy of tools, and consistency of methodologies that are essential for transportation practitioners regarding macrotexture characterization. Important pavement surface characteristics, or tire-pavement interactions, such as friction, tire-pavement noise, splash and spray, and rolling resistance, are significantly influenced by pavement macrotexture. This dissertation compare

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Elmi, Mohamed Abdillahi. "Détection des changements de points multiples et inférence du modèle autorégressif à seuil." Thesis, Bourgogne Franche-Comté, 2018. http://www.theses.fr/2018UBFCD005/document.

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Cette thèse est composée de deux parties: une première partie traite le problème de changement de régime et une deuxième partie concerne le processusautorégressif à seuil dont les innovations ne sont pas indépendantes. Toutefois, ces deux domaines de la statistique et des probabilités se rejoignent dans la littérature et donc dans mon projet de recherche. Dans la première partie, nous étudions le problème de changements derégime. Il existe plusieurs méthodes pour la détection de ruptures mais les principales méthodes sont : la méthode de moindres carrés pénalisés (PLS)et la méthode de derivée

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Buschmann, Tilo. "The Systematic Design and Application of Robust DNA Barcodes." Doctoral thesis, Universitätsbibliothek Leipzig, 2016. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-209812.

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High-throughput sequencing technologies are improving in quality, capacity, and costs, providing versatile applications in DNA and RNA research. For small genomes or fraction of larger genomes, DNA samples can be mixed and loaded together on the same sequencing track. This so-called multiplexing approach relies on a specific DNA tag, index, or barcode that is attached to the sequencing or amplification primer and hence accompanies every read. After sequencing, each sample read is identified on the basis of the respective barcode sequence. Alterations of DNA barcodes during synthesis, primer l

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Dewaele, Benoît. "On the performance of hedge funds." Doctoral thesis, Universite Libre de Bruxelles, 2013. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/209487.

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This thesis investigates the performance of hedge funds, funds of hedge funds and alternative Ucits together with the determinants of this performance by using new or well-suited econometric techniques. As such, it lies at the frontier of finance and financial econometrics and contributes to both fields. For the sake of clarity, we summarize the main contributions to each field separately. <p>The contribution of this thesis to the field of financial econometrics is the time-varying style analysis developed in the second chapter. This statistical tool combines the Sharpe analysis with a time-va

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Stephens, Nathan Wallace. "A Comparison of Microarray Analyses: A Mixed Models Approach Versus the Significance Analysis of Microarrays." BYU ScholarsArchive, 2006. https://scholarsarchive.byu.edu/etd/1115.

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DNA microarrays are a relatively new technology for assessing the expression levels of thousands of genes simultaneously. Researchers hope to find genes that are differentially expressed by hybridizing cDNA from known treatment sources with various genes spotted on the microarrays. The large number of tests involved in analyzing microarrays has raised new questions in multiple testing. Several approaches for identifying differentially expressed genes have been proposed. This paper considers two: (1) a mixed models approach, and (2) the Signiffcance Analysis of Microarrays.

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Bécu, Jean-Michel. "Contrôle des fausses découvertes lors de la sélection de variables en grande dimension." Thesis, Compiègne, 2016. http://www.theses.fr/2016COMP2264/document.

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Dans le cadre de la régression, de nombreuses études s’intéressent au problème dit de la grande dimension, où le nombre de variables explicatives mesurées sur chaque échantillon est beaucoup plus grand que le nombre d’échantillons. Si la sélection de variables est une question classique, les méthodes usuelles ne s’appliquent pas dans le cadre de la grande dimension. Ainsi, dans ce manuscrit, nous présentons la transposition de tests statistiques classiques à la grande dimension. Ces tests sont construits sur des estimateurs des coefficients de régression produits par des approches de régressio

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Nguyen, Van Hanh. "Modèles de mélange semi-paramétriques et applications aux tests multiples." Phd thesis, Université Paris Sud - Paris XI, 2013. http://tel.archives-ouvertes.fr/tel-00987035.

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Dans un contexte de test multiple, nous considérons un modèle de mélange semi-paramétrique avec deux composantes. Une composante est supposée connue et correspond à la distribution des p-valeurs sous hypothèse nulle avec probabilité a priori p. L'autre composante f est nonparamétrique et représente la distribution des p-valeurs sous l'hypothèse alternative. Le problème d'estimer les paramètres p et f du modèle apparaît dans les procédures de contrôle du taux de faux positifs (''false discovery rate'' ou FDR). Dans la première partie de cette dissertation, nous étudions l'estimation de la propo

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Rosahl, Agnes Lioba. "How tissues tell time." Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät I, 2015. http://dx.doi.org/10.18452/17113.

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Durch ihren Einfluß auf die Genexpression reguliert die zirkadiane Uhr physiologische Funktionen vieler Organe. Obwohl der zugrundeliegende allgemeine Uhrmechanismus gut untersucht ist, bestehen noch viele Unklarheiten über die gewebespezifische Regulation zirkadianer Gene. Neben ihrer gemeinsamen 24-h-Periode im Expressionsmuster unterscheiden diese sich darin, zu welcher Tageszeit sie am höchsten exprimiert sind und in welchem Gewebe sie oszillieren. Mittels Überrepräsentationsanalyse lassen sich Bindungsstellen von Transkriptionsfaktoren identifizieren, die an der Regulation ähnlich exprim

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Yang-YuCheng and 鄭暘諭. "Estimation of False Discovery Rate Using Empirical Bayes Method." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/78t3ye.

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碩士<br>國立成功大學<br>統計學系<br>104<br>In multiple testing problems, if you do not adjust the individual type I error rate and still set the individual significance level α, then the overall type I error rate of m hypotheses will be expanded to be mα. This study assumes that several genes have mixed normal distribution, and parameters have prior distribution. We use the Bayesian posterior distribution and EM algorithm to estimate the proportion of the null hypothesis which is true, then to estimate the number of null hypothesis which is true, and FDR. We compare the performance of these estimators f

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Lin, Jian-Ping, and 林建平. "A Note on False Discovery Rate." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/03432627778278009898.

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碩士<br>國立東華大學<br>應用數學系<br>97<br>Recent applications, particularly in genomics and imaging, call for testing large number of hypothesis tests at the same time. The False Discovery Rate (FDR) has been proposed and recognized as a powerful criterion in these contexts. Approximations of FDR such as local false discovery rate (lfdr) has been proposed and justified using two-group models, for example Efron (2007a). A generalization of two-group models is proposed. Under this framework, we study various approximations of false discovery rate and their validity. The connection with skew normality is al

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Dickhaus, Thorsten-Ingo [Verfasser]. "False discovery rate and asymptotics / vorgelegt von Thorsten-Ingo Dickhaus." 2008. http://d-nb.info/987358731/34.

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Han, Bing. "A Bayesian approach to false discovery rate for large scale simultaneous inference." 2007. http://etda.libraries.psu.edu/theses/approved/WorldWideIndex/ETD-2014/index.html.

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Jiao, Shuo. "Detecting differentially expressed genes while controlling the false discovery rate for microarray data." 2009. http://proquest.umi.com/pqdweb?did=1921650101&sid=12&Fmt=2&clientId=14215&RQT=309&VName=PQD.

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Thesis (Ph.D.)--University of Nebraska-Lincoln, 2009.<br>Title from title screen (site viewed March 2, 2010). PDF text: 100 p. : col. ill. ; 953 K. UMI publication number: AAT 3379821. Includes bibliographical references. Also available in microfilm and microfiche formats.

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"Regaining control of false findings in feature selection, classification, and prediction on neuroimaging and genomics data." Tulane University, 2018.

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acase@tulane.edu<br>The technological advances of past decades have led to the accumulation of large amounts of genomic and neuroimaging data, enabling novel strategies in precision medicine. These largely rely on machine learning algorithms and modern statistical methods for big biological datasets, which are data-driven rather than hypothesis-driven. These methods often lack guarantees on the validity of the research findings. Because it can be a matter of life and death, when computational methods are deployed in clinical practice in medicine, establishing guarantees on the validity of the

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Clarke, Sandra Jane. "The performance of multiple hypothesis testing procedures in the presence of dependence." 2010. http://repository.unimelb.edu.au/10187/7284.

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Hypothesis testing is foundational to the discipline of statistics. Procedures exist which control for individual Type I error rates and more global or family-wise error rates for a series of hypothesis tests. However, the ability of scientists to produce very large data sets with increasing ease has led to a rapid rise in the number of statistical tests performed, often with small sample sizes. This is seen particularly in the area of biotechnology and the analysis of microarray data. This thesis considers this high-dimensional context with particular focus on the effects of dependence on exi

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Leap, Katie. "Multiple Testing Correction with Repeated Correlated Outcomes: Applications to Epigenetics." 2017. https://scholarworks.umass.edu/masters_theses_2/559.

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Epigenetic changes (specifically DNA methylation) have been associated with adverse health outcomes; however, unlike genetic markers that are fixed over the lifetime of an individual, methylation can change. Given that there are a large number of methylation sites, measuring them repeatedly introduces multiple testing problems beyond those that exist in a static genetic context. Using simulations of epigenetic data, we considered different methods of controlling the false discovery rate. We considered several underlying associations between an exposure and methylation over time. We found that

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Buschmann, Tilo. "The Systematic Design and Application of Robust DNA Barcodes." Doctoral thesis, 2015. https://ul.qucosa.de/id/qucosa%3A14951.

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High-throughput sequencing technologies are improving in quality, capacity, and costs, providing versatile applications in DNA and RNA research. For small genomes or fraction of larger genomes, DNA samples can be mixed and loaded together on the same sequencing track. This so-called multiplexing approach relies on a specific DNA tag, index, or barcode that is attached to the sequencing or amplification primer and hence accompanies every read. After sequencing, each sample read is identified on the basis of the respective barcode sequence. Alterations of DNA barcodes during synthesis, primer l

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Gültas, Mehmet. "Development of novel Classical and Quantum Information Theory Based Methods for the Detection of Compensatory Mutations in MSAs." Doctoral thesis, 2013. http://hdl.handle.net/11858/00-1735-0000-0022-5EB0-1.

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Multiple Sequenzalignments (MSAs) von homologen Proteinen sind nützliche Werkzeuge, um kompensatorische Mutationen zwischen nicht-konservierten Residuen zu charakterisieren. Die Identifizierung dieser Residuen in MSAs ist eine wichtige Aufgabe um die strukturellen Grundlagen und molekularen Mechanismen von Proteinfunktionen besser zu verstehen. Trotz der vielen Anzahl an Literatur über kompensatorische Mutationen sowie über die Sequenzkonservierungsanalyse für die Erkennung von wichtigen Residuen, haben vorherige Methoden meistens die biochemischen Eigenschaften von Aminosäuren nicht mit

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