Anne-Laure Boulesteix <boulesteix@slcmsr.org>,
Sophie Lambert-Lacroix <Sophie.Lambert@imag.fr>,
Julie Peyre <Julie.Peyre@imag.fr>, and
Korbinian Strimmer <strimmer@uni-leipzig.de>.
This package provides routines for PLS-based genomic analyses.
It implements PLS methods for classification with microarray
data  and  prediction of transcription factor activities from combined
ChIP-chip analysis. The >=1.2-1 versions include two new classification
methods for microarray data: GSIM and Ridge PLS.

Anne-Laure Boulesteix <boulesteix@ibe.med.uni-muenchen.de>,
Sophie Lambert-Lacroix <Sophie.Lambert@imag.fr>, Julie Peyre
<Julie.Peyre@imag.fr>, and Korbinian Strimmer
<strimmer@uni-leipzig.de>.
This package provides routines for PLS-based genomic
analyses. It implements PLS methods for classification with
microarray data and prediction of transcription factor
activities from combined ChIP-chip analysis. The >=1.2-1
versions include two new classification methods for microarray
data: GSIM and Ridge PLS.

Anne-Laure Boulesteix <boulesteix@ibe.med.uni-muenchen.de>,
Ghislain Durif <ghislain.durif@univ-lyon1.fr>,
Sophie Lambert-Lacroix <Sophie.Lambert@imag.fr>, Julie Peyre
<Julie.Peyre@imag.fr>, and Korbinian Strimmer
<strimmer@uni-leipzig.de>.
Routines for PLS-based genomic analyses,
implementing PLS methods for classification with
microarray data and prediction of transcription factor
activities from combined ChIP-chip analysis. The >=1.2-1
versions include two new classification methods for microarray
data: GSIM and Ridge PLS. The >=1.3 versions includes a
new classification method combining variable selection and
compression in logistic regression context: RIRLS-SPLS; and
an adaptive version of the sparse PLS.

Anne-Laure Boulesteix <boulesteix@ibe.med.uni-muenchen.de>,
Ghislain Durif <gd.dev@libertymail.net>,
Sophie Lambert-Lacroix <Sophie.Lambert@imag.fr>, Julie Peyre
<Julie.Peyre@imag.fr>, and Korbinian Strimmer
<strimmer@uni-leipzig.de>.

Routines for PLS-based genomic analyses.
They implements PLS methods for classification with
microarray data and prediction of transcription factor
activities from combined ChIP-chip analysis. The >=1.2-1
versions include two new classification methods for microarray
data: GSIM and Ridge PLS. The >=1.3 versions includes an other
new classification method combining variable selection and
compression in logistic regression context: RIRLS-SPLS; and
an adaptive version of the sparse PLS.