Package: DRaWR 1.0.3

DRaWR: Discriminative Random Walk with Restart

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.

Authors:Charles Blatti [aut, cre]

DRaWR_1.0.3.tar.gz
DRaWR_1.0.3.zip(r-4.7-any)DRaWR_1.0.3.zip(r-4.6-any)DRaWR_1.0.3.zip(r-4.5-any)
DRaWR_1.0.3.tgz(r-4.6-any)DRaWR_1.0.3.tgz(r-4.5-any)
DRaWR_1.0.3.tar.gz(r-4.7-any)DRaWR_1.0.3.tar.gz(r-4.6-any)
DRaWR_1.0.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
DRaWR/json (API)

# Install 'DRaWR' in R:
install.packages('DRaWR', repos = c('https://cblatti3.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.48 score 7 scripts 342 downloads 3 mentions 4 exports 8 dependencies

Last updated from:01afe80e04. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK137
source / vignettesOK146
linux-releaseOK133
macos-releaseOK168
macos-oldrelOK166
windows-develOK82
windows-releaseOK67
windows-oldrelOK61
wasm-releaseOK95

Exports:DRaWRRWRthreeCol2listMatthreeCol2MaxMat

Dependencies:bitopscaToolsgplotsgtoolsKernSmoothlatticeMatrixROCR

Readme and manuals

Help Manual

Help pageTopics
DRaWRDRaWR
RWRRWR
threeCol2listMatthreeCol2listMat
threeCol2MaxMatthreeCol2MaxMat
Sample transition matrix.transmat