Package: lionessR 1.26.0

Ping-Han Hsieh

lionessR: Modeling networks for individual samples using LIONESS

LIONESS, or Linear Interpolation to Obtain Network Estimates for Single Samples, can be used to reconstruct single-sample networks (https://arxiv.org/abs/1505.06440). This code implements the LIONESS equation in the lioness function in R to reconstruct single-sample networks. The default network reconstruction method we use is based on Pearson correlation. However, lionessR can run on any network reconstruction algorithms that returns a complete, weighted adjacency matrix. lionessR works for both unipartite and bipartite networks.

Authors:Marieke Lydia Kuijjer [aut], Ping-Han Hsieh [cre]

lionessR_1.26.0.tar.gz
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lionessR_1.26.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
lionessR/json (API)
NEWS

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

Bug tracker:https://github.com/mararie/lionessr/issues

Datasets:

On BioConductor:lionessR-1.27.0(bioc 3.24)lionessR-1.26.0(bioc 3.23)

networknetworkinferencegeneexpression

5.72 score 24 stars 22 scripts 376 downloads 1 mentions 2 exports 17 dependencies

Last updated from:aa85c615e0 (on RELEASE_3_23). Checks:8 NOTE, 2 OK. Indexed: no.

TargetResultTimeFilesSyslog
bioc-checksNOTE154
linux-devel-x86_64NOTE335
source / vignettesOK278
linux-release-x86_64NOTE250
macos-release-arm64NOTE117
macos-oldrel-arm64NOTE78
windows-develNOTE140
windows-releaseNOTE103
windows-oldrelNOTE123
wasm-releaseOK101

Exports:lionessnetFun

Dependencies:abindBiobaseBiocGenericsDelayedArraygenericsGenomicRangesIRangeslatticeMatrixMatrixGenericsmatrixStatsS4ArraysS4VectorsSeqinfoSparseArraySummarizedExperimentXVector

lionessR

Rendered fromlionessR.Rmdusingknitr::rmarkdownon Jun 08 2026.

Last update: 2019-09-30
Started: 2018-08-17

Readme and manuals

Help Manual

Help pageTopics
LIONESSlioness
netFunnetFun
OS dataexp OSdata targets