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Data Analysis: A Bayesian Tutorial Devinderjit Sivia, John Skilling
Publisher: Oxford University Press, USA

His well commented R-Code can get you into some simple roll-your-own MCMC and Gibbs sampling and his tutorial-like handling of WinBUGS in the raw and through R2WinBUGS is, I think, the best. Doing Bayesian Data Analysis - Indiana University Doing Bayesian Data Analysis - A Tutorial with R and BUGS.. Jaynes; Introduction to Bayesian statistics, William M. Expensive For theroetical and further readings of MCMC. Bayes and Empirical Bayes Methods for Data Analysis, 2nd Edition. A standardized data analysis pipeline; Skilled bioinformatics specialists; Better (more uniform, less bias, simpler, faster, easier, etc) library preparation protocols; Continued reduction in cost of sequencing reagents/services. These papers introduce Bayesian analysis They describe well known algorithms such as gibbs sampler, Metropolis-Hasting algorithm, Metropolis algorithms, important sampling, nested sampling, and so forth, and their applications in the astronomical data analysis. Bernardo and Smith's 1994 book Bayesian Theory is perhaps most comprehensive, but quite mathematical. For a shorter introduction try Sivia' book: Data analysis - A Bayesian tutorial. Our lab conference table is currently hosting a Bayesian data analysis / programming in R learning group. Bolstad; Doing Bayesian Data Analysis: A Tutorial with R and BUGS, John K. Naively speaking, astronomical papers discussing Bayesian analysis mainly serve as Bayesian analysis tutorials in the astronomical subfields of authors' expertise. Gilks, Richardson, and Spiegelhalter (1996). Bayesian Data Analysis, Third Edition (Chapman & Hall/CRC Texts in. Simon Jackman's Bayesian Analysis for the Social Sciences. Probability Theory: The Logic of Science, E. As a starting point, I'd add Doing Bayesian Data Analysis by John Kruschke and Bayesian Computation with R by Jim Albert to the list.