Fast approximate inference for variable selection in Dirichlet process mixtures, with an application to pan-cancer proteomics.

abstract：:Various discriminant methods have been applied for classification of tumors based on gene expression profiles, among which the nearest neighbor (NN) method has been reported to perform relatively well. Usually cross-validation (CV) is used to select the neighbor size as well as the number of variables for the NN metho...

journal_title：Statistical applications in genetics and molecular biology

authors： Paik M,Yang Y

更新日期：2004-01-01 00:00:00

abstract：:In many population genetic problems, parameter estimation is obstructed by an intractable likelihood function. Therefore, approximate estimation methods have been developed, and with growing computational power, sampling-based methods became popular. However, these methods such as Approximate Bayesian Computation (ABC...

journal_title：Statistical applications in genetics and molecular biology

authors： Bertl J,Ewing G,Kosiol C,Futschik A

更新日期：2017-11-27 00:00:00

abstract：:Multiple testing procedures are commonly used in gene expression studies for the detection of differential expression, where typically thousands of genes are measured over at least two experimental conditions. Given the need for powerful testing procedures, and the attendant danger of false positives in multiple testi...

journal_title：Statistical applications in genetics and molecular biology

authors： Green GH,Diggle PJ

更新日期：2007-01-01 00:00:00

abstract：:Several important syndromes are caused by deleterious germline mutations of individual genes. In both clinical and research applications it is useful to evaluate the probability that an individual carries an inherited genetic variant of these genes, and to predict the risk of disease for that individual, using informa...

journal_title：Statistical applications in genetics and molecular biology

authors： Chen S,Wang W,Broman KW,Katki HA,Parmigiani G

更新日期：2004-01-01 00:00:00

abstract：:We evaluate variable selection by multiple tests controlling the false discovery rate (FDR) to build a linear score for prediction of clinical outcome in high-dimensional data. Quality of prediction is assessed by the receiver operating characteristic curve (ROC) for prediction in independent patients. Thus we try to ...

journal_title：Statistical applications in genetics and molecular biology

authors： Graf AC,Bauer P

更新日期：2009-01-01 00:00:00

abstract：:In cellular biology, node-and-edge graph or "network" data collection often uses bait-prey technologies such as co-immunoprecipitation (CoIP). Bait-prey technologies assay relationships or "interactions" between protein pairs, with CoIP specifically measuring protein complex co-membership. Analyses of CoIP data freque...

journal_title：Statistical applications in genetics and molecular biology

authors： Scholtens DM,Spencer BD

更新日期：2015-08-01 00:00:00

abstract：:High-throughput sequencing techniques are increasingly affordable and produce massive amounts of data. Together with other high-throughput technologies, such as microarrays, there are an enormous amount of resources in databases. The collection of these valuable data has been routine for more than a decade. Despite di...

journal_title：Statistical applications in genetics and molecular biology

authors： Schimek MG,Budinská E,Kugler KG,Švendová V,Ding J,Lin S

更新日期：2015-06-01 00:00:00

abstract：:The objective of the present paper is to develop a truly functional Bayesian method specifically designed for time series microarray data. The method allows one to identify differentially expressed genes in a time-course microarray experiment, to rank them and to estimate their expression profiles. Each gene expressio...

journal_title：Statistical applications in genetics and molecular biology

authors： Angelini C,De Canditiis D,Mutarelli M,Pensky M

更新日期：2007-01-01 00:00:00

abstract：:Locus heterogeneity is one of the most important issues in gene mapping and can cause significant reductions in statistical power for gene mapping, yet no research to date has provided power and sample size calculations for family-based association methods in the presence of locus heterogeneity. The purpose of this re...

journal_title：Statistical applications in genetics and molecular biology

authors： Chen C,Yang G,Buyske S,Matise T,Finch SJ,Gordon D

更新日期：2009-01-01 00:00:00

abstract：:We present a weighted-LASSO method to infer the parameters of a first-order vector auto-regressive model that describes time course expression data generated by directed gene-to-gene regulation networks. These networks are assumed to own prior internal structures of connectivity which drive the inference method. This ...

journal_title：Statistical applications in genetics and molecular biology

authors： Charbonnier C,Chiquet J,Ambroise C

更新日期：2010-01-01 00:00:00

abstract：:In the exploding field of gene expression techniques such as DNA microarrays, there are still few general probabilistic methods for analysis of variance. Linear models and ANOVA are heavily used tools in many other disciplines of scientific research. The usual F-statistic is unsatisfactory for microarray data, which e...

journal_title：Statistical applications in genetics and molecular biology

authors： Lönnstedt I,Rimini R,Nilsson P

更新日期：2005-01-01 00:00:00

abstract：:Making sound proteomic inferences using ELISA microarray assay requires both an accurate prediction of protein concentration and a credible estimate of its error. We present a method using monotonic spline statistical models (MS), penalized constrained least squares fitting (PCLS) and Monte Carlo simulation (MC) to pr...

journal_title：Statistical applications in genetics and molecular biology

authors： Daly DS,Anderson KK,White AM,Gonzalez RM,Varnum SM,Zangar RC

更新日期：2008-01-01 00:00:00

abstract：:Germline mosaicism is a genetic condition in which some germ cells of an individual contain a mutation. This condition violates the assumptions underlying classic genetic analysis and may lead to failure of such analysis. In this work we extend the statistical model used for genetic linkage analysis in order to incorp...

journal_title：Statistical applications in genetics and molecular biology

authors： Weissbrod O,Geiger D

更新日期：2011-10-04 00:00:00

abstract：:We are concerned with statistical inference for 2 × C × K contingency tables in the context of genetic case-control association studies. Multivariate methods based on asymptotic Gaussianity of vectors of test statistics require information about the asymptotic correlation structure among these test statistics under th...

journal_title：Statistical applications in genetics and molecular biology

authors： Dickhaus T,Stange J,Demirhan H

更新日期：2015-11-01 00:00:00

abstract：:Mass spectrometry is an important high-throughput technique for profiling small molecular compounds in biological samples and is widely used to identify potential diagnostic and prognostic compounds associated with disease. Commonly, this data generated by mass spectrometry has many missing values resulting when a com...

journal_title：Statistical applications in genetics and molecular biology

authors： Taylor SL,Leiserowitz GS,Kim K

更新日期：2013-12-01 00:00:00

abstract：:There has been increasing interest in predicting patients' survival after therapy by investigating gene expression microarray data. In the regression and classification models with high-dimensional genomic data, boosting has been successfully applied to build accurate predictive models and conduct variable selection s...

journal_title：Statistical applications in genetics and molecular biology

authors： Wang Z,Wang CY

更新日期：2010-01-01 00:00:00

abstract：:With the increasing availability of experimental data on gene interactions, modeling of gene regulatory pathways has gained special attention. Gradient descent algorithms have been widely used for regression and classification applications. Unfortunately, results obtained after training a model by gradient descent are...

journal_title：Statistical applications in genetics and molecular biology

authors： Das M,Murthy CA,De RK

更新日期：2014-02-01 00:00:00

abstract：:Gametic models for fitting breeding values at QTL as random effects in outbred populations have become popular because they require few assumptions about the number and distribution of QTL alleles segregating. The covariance matrix of the gametic effects has an inverse that is sparse and can be constructed rapidly by ...

journal_title：Statistical applications in genetics and molecular biology

authors： Thallman RM,Hanford KJ,Kachman SD,Van Vleck LD

更新日期：2004-01-01 00:00:00

abstract：:We develop an approach for microarray differential expression analysis, i.e. identifying genes whose expression levels differ between two or more groups. Current approaches to inference rely either on full parametric assumptions or on permutation-based techniques for sampling under the null distribution. In some situa...

journal_title：Statistical applications in genetics and molecular biology

authors： Rossell D,Guerra R,Scott C

更新日期：2008-01-01 00:00:00

abstract：:Likelihood-based cross-validation is a statistical tool for selecting a density estimate based on n i.i.d. observations from the true density among a collection of candidate density estimators. General examples are the selection of a model indexing a maximum likelihood estimator, and the selection of a bandwidth index...

journal_title：Statistical applications in genetics and molecular biology

authors： van der Laan MJ,Dudoit S,Keles S

更新日期：2004-01-01 00:00:00

abstract：:In this paper, we address the problem of detecting outlier samples with highly different expression patterns in microarray data. Although outliers are not common, they appear even in widely used benchmark data sets and can negatively affect microarray data analysis. It is important to identify outliers in order to exp...

journal_title：Statistical applications in genetics and molecular biology

authors： Shieh AD,Hung YS

更新日期：2009-01-01 00:00:00

abstract：:The approach adopted involved two-stages. First the 11205 measurements in the mass spectrometry data were reduced to 14 scores by a principal component analysis of the centered but otherwise untreated and unscaled data matrix. Then a linear classifier was derived by linear discriminant analysis using these 14 scores a...

journal_title：Statistical applications in genetics and molecular biology

authors： Fearn T

更新日期：2008-01-01 00:00:00

abstract：:In this paper, we explore the use of M-quantile regression and M-quantile coefficients to detect statistical differences between temporal curves that belong to different experimental conditions. In particular, we consider the application of temporal gene expression data. Here, the aim is to detect genes whose temporal...

journal_title：Statistical applications in genetics and molecular biology

authors： Vinciotti V,Yu K

更新日期：2009-01-01 00:00:00

abstract：:Output from analysis of a high-throughput 'omics' experiment very often is a ranked list. One commonly encountered example is a ranked list of differentially expressed genes from a gene expression experiment, with a length of many hundreds of genes. There are numerous situations where interest is in the comparison of ...

journal_title：Statistical applications in genetics and molecular biology

authors： Donald MR,Wilson SR

更新日期：2017-03-01 00:00:00

abstract：:Gene microarray technology is often used to compare the expression of thousand of genes in two different cell lines. Typically, one does not expect measurable changes in transcription amounts for a large number of genes; furthermore, the noise level of array experiments is rather high in relation to the available numb...

journal_title：Statistical applications in genetics and molecular biology

authors： Erickson S,Sabatti C

更新日期：2005-01-01 00:00:00

abstract：:Consider the standard multiple testing problem where many hypotheses are to be tested, each hypothesis is associated with a test statistic, and large test statistics provide evidence against the null hypotheses. One proposal to provide probabilistic control of Type-I errors is the use of procedures ensuring that the e...

journal_title：Statistical applications in genetics and molecular biology

authors： Rubin D,Dudoit S,van der Laan M

更新日期：2006-01-01 00:00:00

abstract：:Recent analytic and technological breakthroughs have set the stage for genome-wide linkage disequilibrium studies to map disease-susceptibility variants. This paper discusses a probabilistic methodology for making disease-mapping inferences in large-scale case-control genetic studies. The semi-Bayesian approach promot...

journal_title：Statistical applications in genetics and molecular biology

authors： Schrodi SJ

更新日期：2005-01-01 00:00:00

abstract：:Accurately measuring epigenetic marks such as 5-methylcytosine (5-mC) and 5-hydroxymethylcytosine (5-hmC) at the single-nucleotide level, requires combining data from DNA processing methods including traditional (BS), oxidative (oxBS) or Tet-Assisted (TAB) bisulfite conversion. We introduce the R package MLML2R, which...

journal_title：Statistical applications in genetics and molecular biology

authors： Kiihl SF,Martinez-Garrido MJ,Domingo-Relloso A,Bermudez J,Tellez-Plaza M

更新日期：2019-01-17 00:00:00

abstract：:Polytomous phenotypes arise when a disease has multiple subtypes or when two dichotomous phenotypes are analyzed simultaneously. Few software programs offer the option to analyze such phenotypes in family studies, and none implements conditional polytomous logistic regression for within-family analysis robust to popul...

journal_title：Statistical applications in genetics and molecular biology

authors： Bureau A,Croteau J

更新日期：2017-03-01 00:00:00

abstract：:In candidate gene association studies, usually several elementary hypotheses are tested simultaneously using one particular set of data. The data normally consist of partly correlated SNP information. Every SNP can be tested for association with the disease, e.g., using the Cochran-Armitage test for trend. To account ...

journal_title：Statistical applications in genetics and molecular biology

authors： Elsäβer A,Victor A,Hommel G

更新日期：2011-01-01 00:00:00