Some links to genomics data analysis software in which I was involved

Available from BioConductor
CGHbase (with Sjoerd Vosse) Base functions and classes for DNA copy number data analysis
CGHcall Calling for array CGH data
CGHregions (with Sjoerd Vosse) Dimension reduction for called CGH and DNAseq data
globalSeq (by Armin Rauschenberger)
Testing for association between RNA-Seq and high-dimensional data
GRridge (with Putri Novianti) Improved prediction performance by objective and automatic use of co-data in high-dimensional problems.
HCsnip (by Askar Obulkasim) Semi-supervised adaptive-height snipping of the Hierarchical Clustering tree
QDNAseq (by Ilari Scheinin/Daoud Sie) Quantitative DNA sequencing for chromosomal aberrations
PLRS (by Gwenael Leday) Modeling the association between DNA copy number and gene expression with constrained Piecewise Linear Regression Splines
sigaR (by Wessel van Wieringen) Statistics for integrative genomics analyses in R

SSPA (by Maarten van Iterson) General Sample size and power analysis for microarray and next-generation sequencing data
StepwiseCM (by Askar Obulkasim) Stepwise classification using clinical and genomics data

Available from Github
GRridge  (see above; includes co-data imformation; with Putri Novianti)
ShrinkBayes  Bayesian analysis of high-dimensional omics data, either Gaussian (arrays, RNAi) or counts. Includes ShrinkSeq.
ShrinkNet (by Gwenael Leday) Gene network reconstruction using global-local shrinkage priors
WECCA (by Wessel van Wieringen) Weighted clustering for aCGH data

Available elsewhere
CGHtest Statistical permutation tests for called aCGH data
(with Kyung In Kim) Clustering plus hierarchical testing for aCGH data
 Smoothing waves for tumor aCGH profiles
PDE test
(by Wessel van Wieringen) Partial differential expression test for gene expression data