Package: DysPIA 1.4

DysPIA: Dysregulated Pathway Identification Analysis

It is used to identify dysregulated pathways based on a pre-ranked gene pair list. A fast algorithm is used to make the computation really fast. The data in package 'DysPIAData' is needed.

Authors:Limei Wang [aut, cre], Jin Li [aut, ctb]

DysPIA_1.4.tar.gz
DysPIA_1.4.zip(r-4.7)DysPIA_1.4.zip(r-4.6)DysPIA_1.4.zip(r-4.5)
DysPIA_1.4.tgz(r-4.6-x86_64)DysPIA_1.4.tgz(r-4.6-arm64)DysPIA_1.4.tgz(r-4.5-x86_64)DysPIA_1.4.tgz(r-4.5-arm64)
DysPIA_1.4.tar.gz(r-4.7-arm64)DysPIA_1.4.tar.gz(r-4.7-x86_64)DysPIA_1.4.tar.gz(r-4.6-arm64)DysPIA_1.4.tar.gz(r-4.6-x86_64)
DysPIA_1.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
DysPIA/json (API)

# Install 'DysPIA' in R:
install.packages('DysPIA', repos = c('https://lemonwang2020.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/lemonwang2020/dyspia/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

Conda:

cpp

2.70 score 242 downloads 1 mentions 9 exports 14 dependencies

Last updated from:b15711bbb9. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK120
linux-devel-x86_64OK177
source / vignettesOK183
linux-release-arm64OK154
linux-release-x86_64OK171
macos-release-arm64OK167
macos-release-x86_64OK357
macos-oldrel-arm64OK237
macos-oldrel-x86_64OK166
windows-develOK110
windows-releaseOK146
windows-oldrelOK144
wasm-releaseOK108

Exports:calcDyspiaStatcalcDyspiaStatCumulativecalcDyspiaStatCumulativeBatchcalEdgeCorScore_ESEADysGPSDysPIADyspiaSigDyspiaSimpleImplsetUpBPPARAM

Dependencies:BHBiocParallelcodetoolscpp11data.tableDysPIADatafastmatchFNNformatRfutile.loggerfutile.optionslambda.rRcppsnow