R-package
protiq: Protein (identification and) quantification based on peptide evidence
References:
Gerster, S., Kwon, T., Ludwig, C., Matondo, M., Vogel, C.,
Marcotte, E., Aebersold, R. and Bühlmann, P. (2014). Statistical
approach to protein quantification. Molecular and Cellular
Proteomics 13, 666-677. Download
Gerster, S., Qeli, E., Ahrens, C.H. and Bühlmann, P. (2010). Protein
and gene model inference based on statistical modeling in k-partite
graphs. Proceedings of the National Academy of Sciences 107, 12101-12106. PDF.
Supporting Information
R-package
mboost: Model-Based Boosting
References:
Bühlmann, P. and Hothorn, T. (2007). Boosting algorithms:
regularization, prediction and model fitting (with discussion). Statistical
Science 22, 477-522. PDF
Hothorn, T., Bühlmann, P., Kneib, T., Schmid M. and Hofner,
B. (2010). Model-based boosting 2.0. Journal of Machine Learning Research
11, 2109-2113. PDF
R-package
glmmlasso: Generalized linear mixed-effects models with Lasso
Reference:
Schelldorfer, J., Meier, L. and Bühlmann, P. (2014). GLMMLasso: An
algorithm for high-dimensional generalized linear mixed models using
L1-penalization. Journal of Computational and Graphical Statistics 23,
460-477.PDF
R-package
lmmlasso: Linear mixed-effects models with Lasso
Reference:
Schelldorfer, J., Bühlmann, P. and van de Geer, S. (2011). Estimation
for high-dimensional linear mixed-effects models
using L1-penalization. Scandinavian Journal of Statistics 38, 197-214. PDF
R-package howmany: Lower bounds for total number of non-null hypotheses in
multiple testing
Reference: Meinshausen, N. and Bühlmann, P. (2005). Lower bounds for the
number of
false null hypotheses for multiple testing of associations under general
dependence structures. Biometrika 92, 893-907.
PDF
R-package VLMC:
Variable Length Markov Chains
Reference: Mächler, M. and Bühlmann, P. (2004). Variable length Markov chains:
methodology, computing and software. Journal of
Computational and Graphical Statistics 13, 435-455.
R-package supclust:
Supervised Clustering of Genes
References:
Dettling, M. and Bühlmann, P. (2002). Supervised clustering of
genes. Genome Biology, 3(12): research0069.1-0069.15. Click
here.
Dettling, M. and Bühlmann, P. (2003). Finding predictive gene groups
from microarray data. Journal of Multivariate Analysis 90, 106-131.
PDF
Boosting for Tumor
Classification with Gene Expression Data
Reference: Dettling, M. and Bühlmann, P. (2003). Boosting for tumor
classification with gene expression data. Bioinformatics 19, No. 9,
1061-1069.
Compressed postscript.
PDF.