BGX: a Bioconductor package for the Bayesian integrated analysis of Affymetrix GeneChips. BGX is a new Bioconductor R package that implements an integrated Bayesian approach to the analysis of 3’ GeneChip data. The software takes into account additive and multiplicative error, non-specific hybridisation and replicate summarisation in the spirit of the model outlined in . It also provides a posterior distribution for the expression of each gene. Moreover, BGX can take into account probe affinity effects from probe sequence information where available. The package employs a novel adaptive Markov chain Monte Carlo (MCMC) algorithm that raises considerably the efficiency with which the posterior distributions are sampled from. Finally, BGX incorporates various ways to analyse the results, such as ranking genes by expression level as well as statistically based methods for estimating the amount of up and down regulated genes between two conditions.
Keywords for this software
References in zbMATH (referenced in 5 articles )
Showing results 1 to 5 of 5.
- Rosenthal, Jeffrey S.; Yang, Jinyoung: Ergodicity of combocontinuous adaptive MCMC algorithms (2018)
- Yang, Jinyoung; Rosenthal, Jeffrey S.: Automatically tuned general-purpose MCMC via new adaptive diagnostics (2017)
- Hellton, Kristoffer Herland; Thoresen, Magne: The impact of measurement error on principal component analysis (2014)
- Łatuszyński, Krzysztof; Roberts, Gareth O.; Rosenthal, Jeffrey S.: Adaptive Gibbs samplers and related MCMC methods (2013)
- Turro, Ernest; Bochkina, Natalia; Hein, Anne-Mette K.; Richardson, Sylvia: BGX: a bioconductor package for the Bayesian integrated analysis of affymetrix genechips (2007) ioport