Bubble Chart to Compare Biological Annotations by using DAVID
R-based graphical tool to concisely visualise and compare biological annotations queried from the DAVID web service. It provides R functions to perform enrichment analysis (via DAVID - http://david.abcc.ncifcrf.gov) on several gene lists at once, and then visualizing all the results in one generated figure that allows R users to compare the annotations found for each list.

Bayesian Analysis of Computer Code Output
Bayesian analysis of computer code software.  The
bundle contains routines that evaluate the formulae of Kennedy,
O'Hagan, and Oakley.
Robin K. S. Hankin <r.hankin@noc.soton.ac.uk>

Robin K. S. Hankin <hankin.robin@gmail.com>

Bayesian Analysis of Computer Code Output (BACCO)
The BACCO bundle of packages is replaced by the BACCO
package, which provides a vignette that illustrates the
constituent packages (emulator, approximator, calibrator) in
use.

emulator (>= 1.2-13), calibrator (>= 1.2-5), approximator (>=
1.2-6)
The BACCO bundle of packages is replaced by the BACCO
package, which provides a vignette that illustrates the constituent
packages (emulator, approximator, calibrator) in use.

Bayesian Augmented Control for Clinical Trials
c(
person("Hongtao", "Zhang", role = c("aut", "cre"), email = "hongtao.zhang@abbvie.com"),
person("Qi", "Tang", role = "aut", email = "qi.tang@abbvie.com")
)
Implements the Bayesian Augmented Control (BAC, a.k.a. Bayesian historical data borrowing) method under clinical trial setting by calling 'Just Another Gibbs Sampler' ('JAGS') software. In addition, the 'BACCT' package evaluates user-specified decision rules by computing the type-I error/power, or probability of correct go/no-go decision at interim look. The evaluation can be presented numerically or graphically. Users need to have 'JAGS' 4.0.0 or newer installed due to a compatibility issue with 'rjags' package. Currently, the package implements the BAC method for binary outcome only. Support for continuous and survival endpoints will be added in future releases. We would like to thank AbbVie's Statistical Innovation group and Clinical Statistics group for their support in developing the 'BACCT' package.