Package ‘ bridge ’ March 22 , 2017
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March 22, 2017 Title Bayesian Robust Inference for Differential Gene Expression Version 1.38.0 Author Raphael Gottardo Description Test for differentially expressed genes with microarray data. This package can be used with both cDNA microarrays or Affymetrix chip. The packge fits a robust Bayesian hierarchical model for testing for differential expression. Outliers are modeled explicitly using a $t$-distribution. The model includes an exchangeable prior for the variances which allow different variances for the genes but still shrink extreme empirical variances. Our model can be used for testing for differentially expressed genes among multiple samples, and can distinguish between the different possible patterns of differential expression when there are three or more samples. Parameter estimation is carried out using a novel version of Markov Chain Monte Carlo that is appropriate when the model puts mass on subspaces of the full parameter space. Maintainer Raphael Gottardo Depends R (>= 1.9.0), rama License GPL (>= 2) biocViews Microarray,OneChannel,TwoChannel,DifferentialExpression NeedsCompilation yes
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Package ‘ bridge ’ March 28 , 2017
March 28, 2017 Title Bayesian Robust Inference for Differential Gene Expression Version 1.38.0 Author Raphael Gottardo Description Test for differentially expressed genes with microarray data. This package can be used with both cDNA microarrays or Affymetrix chip. The packge fits a robust Bayesian hierarchical model for testing for differential expression. Outliers are modeled explicitly using ...
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Article history: Received 22 March 2010 Received in revised form 28 September 2010 Accepted 23 February 2011 Available online 1 March 2011
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Version 3.30.13 Date 2017-03-14 Title Linear Models for Microarray Data Description Data analysis, linear models and differential expression for microarray data. Author Gordon Smyth [cre,aut], Yifang Hu [ctb], Matthew Ritchie [ctb], Jeremy Silver [ctb], James Wettenhall [ctb], Davis McCarthy [ctb], Di Wu [ctb], Wei Shi [ctb], Belinda Phipson [ctb], Aaron Lun [ctb], Natalie Thorne [ctb], Alicia ...
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Summary Reconstructing and analyzing a large number of genome-scale metabolic models is a fundamental part of the integrated study of microbial communities; however, two of the most widely used frameworks for building and analyzing models use different metabolic network representations. Here we describe Mackinac, a Python package that combines ModelSEED's ability to automatically reconstruct me...
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تاریخ انتشار 2017