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102
Sequence analysis EBSeq-HMM: a Bayesian approach for
"... identifying gene-expression changes in ordered RNA-seq experiments ..."
Supplementary manual. Sequential design of RNA-seq experiments
"... This manual explains how to use casper to help design RNA-seq experi-ments, for the main manual please load the package and type vignette(’casper’) at the command prompt. casper provides tools to design RNA-seq isoform expression experiments, both single and multiple sample studies. The former may e ..."
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This manual explains how to use casper to help design RNA-seq experi-ments, for the main manual please load the package and type vignette(’casper’) at the command prompt. casper provides tools to design RNA-seq isoform expression experiments, both single and multiple sample studies. The former may
EBSeq: an empirical Bayes hierarchical model for inference in RNA-seq experiments
- Bioinformatics
, 2013
"... Motivation: Messenger RNA expression is important in normal development and differentiation, as well as in manifestation of disease. RNA-seq experiments allow for the identification of differentially expressed (DE) genes and their corresponding isoforms on a genome-wide scale. However, statistical m ..."
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Cited by 31 (3 self)
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in an RNA-seq experiment comparing two or more biological conditions. Results demonstrate substantially improved power and performance of EBSeq for identifying DE isoforms. EBSeq also proves to be a robust approach for identifying DE genes. Availability: An R package containing examples and sample data sets
Gene Mapping via Bulked Segregant RNA-Seq (BSR-Seq)
, 2012
"... Bulked segregant analysis (BSA) is an efficient method to rapidly and efficiently map genes responsible for mutant phenotypes. BSA requires access to quantitative genetic markers that are polymorphic in the mapping population. We have developed a modification of BSA (BSR-Seq) that makes use of RNA-S ..."
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Cited by 4 (2 self)
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data using an empirical Bayesian approach. In addition, analysis of the RNA-Seq data provides information on the effects of the mutant on global patterns of gene expression at no extra cost. In combination these results greatly simplify gene cloning experiments. To demonstrate the utility
Flexible analysis of RNA-seq data using mixed effects models. Bioinformatics 30: 180–188. doi
, 2014
"... Motivation: Most methods for estimating differential expression from RNA-seq are based on statistics that compare normalised read counts between treatment classes. Unfortunately, reads are in general too short to be mapped unambiguously to features of interest, such as genes, isoforms or haplotype-s ..."
Abstract
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Cited by 5 (0 self)
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comparisons between treatment groups. Results: In this paper we make two proposals that improve the power, specificity and versatility of expression analysis using RNA-seq data. Firstly, we present a Bayesian method for model selection that accounts for read mapping ambiguities using random effects
Bayesian Models for Keyhole Plan Recognition in an Adventure Game
, 1998
"... We present an approach to keyhole plan recognition which uses a dynamic belief (Bayesian) network to represent features of the domain that are needed to identify users' plans and goals. The application domain is a Multi-User Dungeon adventure game with thousands of possible actions and locatio ..."
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Cited by 131 (10 self)
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We present an approach to keyhole plan recognition which uses a dynamic belief (Bayesian) network to represent features of the domain that are needed to identify users' plans and goals. The application domain is a Multi-User Dungeon adventure game with thousands of possible actions
RNA-seq Analysis of Early Hepatic Response to Handling and Confinement Stress in Rainbow Trout
"... Fish under intensive rearing conditions experience various stressors which have negative impacts on survival, growth, reproduction and fillet quality. Identifying and characterizing the molecular mechanisms underlying stress responses will facilitate the development of strategies that aim to improve ..."
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for qPCR to validate the RNA-seq approach. The fold changes in gene expression identified by RNA-seq and qPCR were highly correlated (R2 = 0.88). Several gene ontology terms including transcription factor activity and biological process such as glucose metabolic process were enriched among these DETs
Improved statistical inference from DNA microarray data using analysis of variance and a Bayesian statistical framework
"... et of candidate genes than those identified using only fold-change or statistical tests not incorporating a Bayesian prior. We also show that using statistical tests based on analysis of variance and a Bayesian prior identifies genes that are up- or down- regulated following an experimental manipula ..."
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Cited by 83 (0 self)
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et of candidate genes than those identified using only fold-change or statistical tests not incorporating a Bayesian prior. We also show that using statistical tests based on analysis of variance and a Bayesian prior identifies genes that are up- or down- regulated following an experimental
A Bayesian Approach to Transcript Estimation from Gene
- In Proceedings of the Sixth Annual International Conference on Research in Computational Molecular Biology (RECOMB
, 2002
"... We present a new statistically optimal approach to estimate transcript levels and ratios from one or more gene array experiments. The Bayesian Estimation of Array Measurements (BEAM) technique uses a model of measurement noise and prior information to estimate biological expression levels. It provid ..."
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We present a new statistically optimal approach to estimate transcript levels and ratios from one or more gene array experiments. The Bayesian Estimation of Array Measurements (BEAM) technique uses a model of measurement noise and prior information to estimate biological expression levels
An empirical Bayesian approach for identifying differential co-expression in high-throughput experiments. Biometrics E-publication before print: http://onlinelibrary.wiley.com/doi/10.1111/j.15410420.2011.01688.x/abstract
, 2011
"... for Identifying Differential Co-expression in High-throughput Experiments A common goal of microarray and related high-throughput genomic experiments is to identify genes that vary across biological condition. Most often this is accomplished by identifying genes with changes in mean expression level ..."
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Cited by 5 (3 self)
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for Identifying Differential Co-expression in High-throughput Experiments A common goal of microarray and related high-throughput genomic experiments is to identify genes that vary across biological condition. Most often this is accomplished by identifying genes with changes in mean expression
Results 1 - 10
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102
