Detecting differential gene expression with a semiparametric hierarchical mixture method

From MaRDI portal
Publication:5701280

DOI10.1093/biostatistics/5.2.155zbMath1096.62124OpenAlexW2170264612WikidataQ47850306 ScholiaQ47850306MaRDI QIDQ5701280

Amine Noueiry, Michael A. Newton, Deepayan Sarkar, Paul Ahlquist

Publication date: 2 November 2005

Published in: Biostatistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1093/biostatistics/5.2.155



Related Items

Nonparametric Bayesian learning of heterogeneous dynamic transcription factor networks, Vladimir Steklov: a mathematician at the turn of the era, Generalized estimating equations by considering additive terms for analyzing time-course gene sets data, Estimating Effect Sizes of Differentially Expressed Genes for Power and Sample-Size Assessments in Microarray Experiments, Hierarchical Bayes variable selection and microarray experiments, Reciprocal graphical models for integrative gene regulatory network analysis, A Unified Approach for Simultaneous Gene Clustering and Differential Expression Identification, A spatiotemporal nonparametric Bayesian model of multi-subject fMRI data, A semi-parametric Bayesian approach for detection of gene expression heterosis with RNA-seq data, A semiparametric Bayesian model for comparing DNA copy numbers, Improved Detection of Differentially Expressed Genes Through Incorporation of Gene Locations, A new approach to multiple testing of grouped hypotheses, Large-Scale Multiple Testing under Dependence, Multivariate functional response regression, with application to fluorescence spectroscopy in a cervical pre-cancer study, Bayesian local false discovery rate for sparse count data with application to the discovery of hotspots in protein domains, Covariate-adjusted multiple testing in genome-wide association studies via factorial hidden Markov models, An empirical Bayes optimal discovery procedure based on semiparametric hierarchical mixture models, BOPA: A Bayesian hierarchical model for outlier expression detection, Gamma-based clustering via ordered means with application to gene-expression analysis, A Flexible and Powerful Bayesian Hierarchical Model for ChIP-Chip Experiments, Bayesian Analysis of Mass Spectrometry Proteomic Data Using Wavelet-Based Functional Mixed Models, Microarrays, empirical Bayes and the two-groups model, A general framework for multiple testing dependence, A Bayesian measurement error model for two-channel cell-based RNAi data with replicates, Sequential tests of multiple hypotheses controlling false discovery and nondiscovery rates, A semi-parametric Bayesian approach for differential expression analysis of RNA-seq data, Multiple hypothesis testing and clustering with mixtures of non-central \(t\)-distributions applied in microarray data analysis, A Bayesian model averaging approach for observational gene expression studies, Hierarchical Bayesian meta-analysis models for cross-platform microarray studies, A probabilistic framework for microarray data analysis: fundamental probability models and statistical inference, Spectral clustering via sparse graph structure learning with application to proteomic signaling networks in cancer, A hierarchical Bayesian model for inference of copy number variants and their association to gene expression, Size, power and false discovery rates, Covariate adjusted differential variability analysis of DNA methylation with propensity score method, Bayesian sparse graphical models for classification with application to protein expression data, Selecting massive variables using an iterated conditional modes/medians algorithm, Multiple testing on standardized mortality ratios: a Bayesian hierarchical model for FDR estimation, Estimation and selection in high-dimensional genomic studies for developing molecular diagnostics, Efficient Bayesian regularization for graphical model selection, A Bayesian nonparametric spiked process prior for dynamic model selection, Bayesian ranking and selection methods using hierarchical mixture models in microarray studies, A statistical analysis of memory CD8 T cell differentiation: An application of a hierarchical state space model to a short time course microarray experiment, Bayesian Error‐in‐Variable Survival Model for the Analysis of GeneChip Arrays, Wavelet Thresholding with Bayesian False Discovery Rate Control, A compositional model to assess expression changes from single-cell RNA-seq data, A Time‐Series DDP for Functional Proteomics Profiles, Limit theorems for hybridization reactions on oligonucleotide microarrays, Bayesian inference and testing of group differences in brain networks, Hadamard matrix methods in identifying differentially expressed genes from microarray experi\-ments, A new class of mixture models for differential gene expression in DNA microarray data, A two-stage empirical Bayes method for identifying differentially expressed genes, A heavy-tailed empirical Bayes method for replicated microarray data, A mixture model approach for the analysis of small exploratory microarray experiments, A robust unified approach to analyzing methylation and gene expression data, Shrinkage estimation of effect sizes as an alternative to hypothesis testing followed by estimation in high-dimensional biology: applications to differential gene expression, Semiparametric Bayesian Inference for Phage Display Data, Bayesian hidden Markov models to identify RNA–protein interaction sites in PAR‐CLIP, A statistical framework for testing functional categories in microarray data, Bayesian decision theoretic multiple comparison procedures: An application to phage display data, A Bayesian graphical modeling approach to microRNA regulatory network inference, Spiked Dirichlet process priors for Gaussian process models, Classification of brain activation via spatial Bayesian variable selection in fMRI regression, Mixture Modeling for Genome‐Wide Localization of Transcription Factors, Assessing Differential Gene Expression with Small Sample Sizes in Oligonucleotide Arrays Using a Mean‐Variance Model, An empirical Bayes mixture method for effect size and false discovery rate estimation, Unsupervised empirical Bayesian multiple testing with external covariates, The importance of distinct modeling strategies for gene and gene-specific treatment effects in hierarchical models for microarray data, Gaga: a parsimonious and flexible model for differential expression analysis, Bayesian testing of many hypotheses \(\times \) many genes: a study of sleep apnea, A Robust Method for Large-Scale Multiple Hypotheses Testing, A Bayesian Mixture Model for Differential Gene Expression, A nested mixture model for protein identification using mass spectrometry, Extracting gene regulation information for cancer classification, A Bayesian Approach for Estimating Dynamic Functional Network Connectivity in fMRI Data, Proximity Model for Expression Quantitative Trait Loci (eQTL) Detection, Bayesian indicator variable selection to incorporate hierarchical overlapping group structure in multi-omics applications, Bayesian Modeling of ChIP-chip Data Through a High-Order Ising Model, A Bayesian model of microbiome data for simultaneous identification of covariate associations and prediction of phenotypic outcomes, Cluster analysis using multivariate normal mixture models to detect differential gene expression with microarray data, Flexible temporal expression profile modelling using the Gaussian process, HmmSeq: a hidden Markov model for detecting differentially expressed genes from RNA-seq data, Exploiting blank spots for model-based background correction in discovering genes with DNA array data, Estimating the Proportion of True Null Hypotheses, with application to DNA Microarray Data, Bayesian Modeling of Differential Gene Expression, Bayesian Robust Inference for Differential Gene Expression in Microarrays with Multiple Samples, Statistical Methods for Expression Quantitative Trait Loci (eQTL) Mapping, Generalized Species Sampling Priors With Latent Beta Reinforcements, A Bayesian extension of the hypergeometric test for functional enrichment analysis, Spatially Dependent Multiple Testing Under Model Misspecification, With Application to Detection of Anthropogenic Influence on Extreme Climate Events, Batch Effects Correction with Unknown Subtypes, Functional Hierarchical Models for Identifying Genes with Different Time‐Course Expression Profiles, A Bayesian time-varying effect model for behavioral mHealth data, Estimating heterogeneous gene regulatory networks from zero-inflated single-cell expression data, Bayesian Structure Learning in Multilayered Genomic Networks, Nonparametric analysis of replicated microarray experiments, An Integrative Bayesian Modeling Approach to Imaging Genetics, A Decision‐Theory Approach to Interpretable Set Analysis for High‐Dimensional Data, A graphical model method for integrating multiple sources of genome-scale data, Computational Biology: Toward Deciphering Gene Regulatory Information in Mammalian Genomes, Local false discovery rate based methods for multiple testing of one-way classified hypotheses, Bayesian functional enrichment analysis for the Reactome database, LAWS: A Locally Adaptive Weighting and Screening Approach to Spatial Multiple Testing, Heteroscedasticity-Adjusted Ranking and Thresholding for Large-Scale Multiple Testing, Distributed eQTL analysis with auxiliary information, Bayesian Genome- and Epigenome-Wide Association Studies with Gene Level Dependence, Two‐group Poisson‐Dirichlet mixtures for multiple testing, On Joint Estimation of Gaussian Graphical Models for Spatial and Temporal Data, A loss‐based prior for Gaussian graphical models, A Bayesian model to identify multiple expression patterns with simultaneous FDR control for a multi-factor RNA-seq experiment, Bayesian Mixture Models for Complex High Dimensional Count Data in Phage Display Experiments


Uses Software