Approximate maximum likelihood estimation for population genetic inference.

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：: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：: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：:We present an approach to association studies involving a dozen or so ;response' variables and a few hundred ;explanatory' variables which emphasizes transparency, simplicity, and protection against spurious results. The methods proposed are largely non-parametric, and they are systematically rounded-off by the Benjam...

journal_title：Statistical applications in genetics and molecular biology

authors： Ferreira JA,Berkhof J,Souverein O,Zwinderman K

更新日期：2009-01-01 00:00:00

abstract：:Reproducibility of disease signatures and clinical biomarkers in multi-omics disease analysis has been a key challenge due to a multitude of factors. The heterogeneity of the limited sample, various biological factors such as environmental confounders, and the inherent experimental and technical noises, compounded wit...

journal_title：Statistical applications in genetics and molecular biology

authors： Liang Y,Kelemen A,Kelemen A

更新日期：2019-05-11 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：:The problem of finding periodically expressed genes from time course microarray experiments is at the center of numerous efforts to identify the molecular components of biological clocks. We present a new approach to this problem based on the cyclohedron test, which is a rank test inspired by recent advances in algebr...

journal_title：Statistical applications in genetics and molecular biology

authors： Morton J,Pachter L,Shiu A,Sturmfels B

更新日期：2007-01-01 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：:Certain residues have no known function yet are co-conserved across distantly related protein families and diverse organisms, suggesting that they perform critical roles associated with as-yet-unidentified molecular properties and mechanisms. This raises the question of how to obtain additional clues regarding these m...

journal_title：Statistical applications in genetics and molecular biology

authors： Neuwald AF

更新日期：2011-01-01 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：: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：: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：: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：:Combining correlated p-values from multiple hypothesis testing is a most frequently used method for integrating information in genetic and genomic data analysis. However, most existing methods for combining independent p-values from individual component problems into a single unified p-value are unsuitable for the cor...

journal_title：Statistical applications in genetics and molecular biology

authors： Chien LC

更新日期：2020-11-06 00:00:00

abstract：:In this study, we propose a novel statistical framework for detecting progressive changes in molecular traits as response to a pathogenic stimulus. In particular, we propose to employ Bayesian hierarchical models to analyse changes in mean level, variance and correlation of metabolic traits in relation to covariates. ...

journal_title：Statistical applications in genetics and molecular biology

authors： Salamanca BV,Ebbels TM,Iorio MD

更新日期：2014-04-01 00:00:00

abstract：:Unraveling interactions among variables such as genetic, clinical, demographic and environmental factors is essential to understand the development of common and complex diseases. To increase the power to detect such variables interactions associated with clinical time-to-events outcomes, we borrowed established conce...

journal_title：Statistical applications in genetics and molecular biology

authors： Dazard JE,Ishwaran H,Mehlotra R,Weinberg A,Zimmerman P

更新日期：2018-02-17 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：: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：:In a hidden Markov model, one "estimates" the state of the hidden Markov chain at t by computing via the forwards-backwards algorithm the conditional distribution of the state vector given the observed data. The covariance matrix of this conditional distribution measures the information lost by failure to observe dire...

journal_title：Statistical applications in genetics and molecular biology

authors： Siegmund DO,Yakir B

更新日期：2007-01-01 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：:Longitudinal genomics data and survival outcome are common in biomedical studies, where the genomics data are often of high dimension. It is of great interest to select informative longitudinal biomarkers (e.g. genes) related to the survival outcome. In this paper, we develop a computationally efficient tool, LCox, fo...

journal_title：Statistical applications in genetics and molecular biology

authors： Sun J,Herazo-Maya JD,Wang JL,Kaminski N,Zhao H

更新日期：2019-02-13 00:00:00

abstract：:Approaches based upon sequence weights, to construct a position weight matrix of nucleotides from aligned inputs, are popular but little effort has been expended to measure their quality. We derive optimal sequence weights that minimize the sum of the variances of the estimators of base frequency parameters for sequen...

journal_title：Statistical applications in genetics and molecular biology

authors： Newberg LA,McCue LA,Lawrence CE

更新日期：2005-01-01 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：: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：:Multiple branching trees have been used to model the acquisition of HIV drug resistance mutations, and several different algorithms have been developed to construct the tree set that best describes the data. These algorithms have mainly focused on the structure of the tree set. The focal point of this paper is estimat...

journal_title：Statistical applications in genetics and molecular biology

authors： Healy BC,DeGruttola VG,Hu C

更新日期：2008-01-01 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：: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：: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：:We address a potential shortcoming of three probabilistic models for detecting interspecific recombination in DNA sequence alignments: the multiple change-point model (MCP) of Suchard et al. (2003), the dual multiple change-point model (DMCP) of Minin et al. (2005), and the phylogenetic factorial hidden Markov model (...

journal_title：Statistical applications in genetics and molecular biology

authors： Husmeier D,Mantzaris AV

更新日期：2008-01-01 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