Author: Chris Walsh <Chris.Walsh@sci.monash.edu.au> and
Description: Variance partition of a multivariate data set

Packaged: Thu Jul 15 22:48:41 2004; root

Packaged: Sat Oct  2 20:07:53 2004; root

Packaged: Sun Nov 20 10:24:56 2005; root

Packaged: Thu Apr 12 09:59:38 2007; dacelo

Author: Chris Walsh <cwalsh@unimelb.edu.au> and Ralph Mac Nally

Authors@R: c(person("Chris", "Walsh", role = c("aut","cre"), email =
"cwalsh@unimelb.edu.au"), person("Ralph", "Mac Nally", role =

Description: Partitioning of the independent and joint contributions of each
variable in a multivariate data set, to a linear regression by hierarchical
decomposition of goodness-of-fit measures of regressions using all subsets
of predictors in the data set. (i.e., model (1), (2), ..., (N), (1,2), ...,
(1,N), ..., (1,2,3,...,N)). A Z-score based estimate of the 'importance' of
each predictor is provided by using a randomisation test.
Authors@R: c(person("Chris", "Walsh", role = c("aut","cre"),
person("Ralph", "Mac Nally", role = "aut",

Packaged: Mon Nov  1 21:36:00 2004; root

Title: Bipartite Graph-Based Hierarchical Clustering
Authors@R: c(person("Calvin", "Chi", email = "calvin.chi@berkeley.edu", role = c("aut", "cre", "cph")),
person("Woojoo", "Lee", role = c("ctb")),
person("Donghwan", "Lee", role = c("ctb")),
person("Youngjo", "Lee", role = c("ctb")),
person("Yudi", "Pawitan", role = c("ctb")))
Bipartite graph-based hierarchical clustering, developed for pharmacogenomic
datasets and datasets sharing the same data structure. The goal is to
construct a hierarchical clustering of groups of samples based on
association patterns between two sets of variables. In the context of
pharmacogenomic datasets, the samples are cell lines, and the two sets of
variables are typically expression levels and drug sensitivity values.
For this method, sparse canonical correlation analysis from
is first applied to extract association patterns for each group of samples.
Then, a nuclear norm-based dissimilarity measure is used to construct a
dissimilarity matrix between groups based on the extracted associations.
Finally, hierarchical clustering is applied.
Packaged: 2021-02-12 15:02:07 UTC; calvinchi