spatstat.geom, spatstat.linnet, spatstat (>= 2.0-0), spdep,

Author: Keyan Salari, Robert Tibshirani, Jonathan R. Pollack
Description: Integrative analysis of DNA copy number and gene
expression data described in Salari et al 2009
Packaged: 2009-08-04 19:05:36 UTC; pollacklab

Packaged: 2009-11-17 08:36:21 UTC; pollacklab

Title: Discontinuous Regression and Image Processing
Description: This is a collection of functions for discontinuous regression
Depends: R (>= 2.10.0), readbitmap, caTools, graphics, stats

analysis and image processing (DRIP). A recent addition is the
blind image deblurring via jump-preserving extrapolation.

Depends: R (>= 2.10.0), readbitmap, graphics, stats

blind image deblurring via jump-preserving extrapolation. This
version removes the dependence on the GNU Scientific Library.
Depends: R (>= 3.5.0), parallel, readbitmap, graphics, stats

analysis and image processing (DRIP). This version removes the
dependence on the GNU Scientific Library.
Depends: R (>= 3.5.0), parallel, graphics, stats

Title: Dimensionality Reduction via Regression
Description: An Implementation of Dimensionality Reduction
via Regression using Kernel Ridge Regression.

Authors@R: person("Guido", "Kraemer", email = "gkraemer@bgc-jena.mpg.de", role = c("aut","cre"))

Package: DRaWR
Title: Discriminative Random Walk with Restart
Version: 1.0.1
Authors@R: person("Charles", "Blatti", email = "blatti@illinois.edu", role = c("aut", "cre"))
Author: Charles Blatti [aut, cre]
Maintainer: Charles Blatti <blatti@illinois.edu>
Description: We present DRaWR, a network-based method for ranking genes or
properties related to a given gene set. Such related genes or properties are
identified from among the nodes of a large, heterogeneous network of biological
information. Our method involves a random walk with restarts, performed on
an initial network with multiple node and edge types, preserving more of the
original, specific property information than current methods that operate
on homogeneous networks. In this first stage of our algorithm, we find the
properties that are the most relevant to the given gene set and extract a
subnetwork of the original network, comprising only the relevant properties. We
then rerank genes by their similarity to the given gene set, based on a second
random walk with restarts, performed on the above subnetwork.
Depends: R (>= 3.0)
License: GPL-2
LazyData: true
Imports: Matrix, ROCR
RoxygenNote: 5.0.1.9000
NeedsCompilation: no
Packaged: 2016-02-04 15:59:44 UTC; root
Repository: CRAN
Date/Publication: 2016-02-05 00:55:30