Phil Spector, Jerome Friedman, Robert Tibshirani, Thomas Lumley, Shawn Garbett, Jonathan Baron

Two nonparametric methods for multiple regression transform selection are provided.
  The first, Alternative Conditional Expectations (ACE), 
  is an algorithm to find the fixed point of maximal
  correlation, i.e. it finds a set of transformed response variables that maximizes R^2
  using smoothing functions [see Breiman, L., and J.H. Friedman. 1985. "Estimating Optimal Transformations
  for Multiple Regression and Correlation". Journal of the American Statistical Association.
  80:580-598. <doi:10.1080/01621459.1985.10478157>].
  Also included is the Additivity Variance Stabilization (AVAS) method which works better than ACE when
  correlation is low [see Tibshirani, R.. 1986. "Estimating Transformations for Regression via Additivity
  and Variance Stabilization". Journal of the American Statistical Association. 83:394-405. 
  <doi:10.1080/01621459.1988.10478610>]. A good introduction to these two methods is in chapter 16 of
  Frank Harrel's "Regression Modeling Strategies" in the Springer Series in Statistics.

ACE and AVAS for Selecting Multiple Regression Transformations

Thomas Lin Pedersen, Vladislav A Petyuk with contributions from
    Laurent Gatto and Sebastian Gibb.

A parser for mzIdentML files implemented using the XML package.
    The parser tries to be general and able to handle all types of mzIdentML
    files with the drawback of having less 'pretty' output than a vendor
    specific parser. Please contact the maintainer with any problems and supply
    an mzIdentML file so the problems can be fixed quickly.

XML, plyr, parallel, doParallel, foreach, iterators,
ProtGenerics

'aaa.R' 'generics.R' 'mzIDpsm.R' 'mzIDpeptides.R'
'mzIDparameters.R' 'mzIDevidence.R' 'mzIDdatabase.R' 'mzID.R'
'mzIDCollection.R' 'mzID-constructor.R' 'mzID-package.R'

Create Elegant Data Visualisations Using the Grammar of Graphics

A system for 'declaratively' creating graphics,
    based on "The Grammar of Graphics". You provide the data, tell 'ggplot2'
    how to map variables to aesthetics, what graphical primitives to use,
    and it takes care of the details.