Package: lpNet 2.39.0
Lars Kaderali
lpNet: Linear Programming Model for Network Inference
lpNet aims at infering biological networks, in particular signaling and gene networks. For that it takes perturbation data, either steady-state or time-series, as input and generates an LP model which allows the inference of signaling networks. For parameter identification either leave-one-out cross-validation or stratified n-fold cross-validation can be used.
Authors:
lpNet_2.39.0.tar.gz
lpNet_2.39.0.zip(r-4.5)lpNet_2.39.0.zip(r-4.4)lpNet_2.39.0.zip(r-4.3)
lpNet_2.39.0.tgz(r-4.4-any)lpNet_2.39.0.tgz(r-4.3-any)
lpNet_2.39.0.tar.gz(r-4.5-noble)lpNet_2.39.0.tar.gz(r-4.4-noble)
lpNet_2.39.0.tgz(r-4.4-emscripten)lpNet_2.39.0.tgz(r-4.3-emscripten)
lpNet.pdf |lpNet.html✨
lpNet/json (API)
NEWS
| # Install 'lpNet' in R: |
| install.packages('lpNet', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
On BioConductor:lpNet-2.39.0(bioc 3.21)lpNet-2.38.0(bioc 3.20)
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 months agofrom:b90bc0ca3e. Checks:OK: 1 WARNING: 6. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 29 2024 |
| R-4.5-win | WARNING | Nov 29 2024 |
| R-4.5-linux | WARNING | Nov 29 2024 |
| R-4.4-win | WARNING | Nov 29 2024 |
| R-4.4-mac | WARNING | Nov 29 2024 |
| R-4.3-win | WARNING | Nov 29 2024 |
| R-4.3-mac | WARNING | Nov 29 2024 |
Exports:calcActivationcalcPredictionKfoldCVcalcPredictionLOOCVcalcRangeLambdadoILPgenerateTimeSeriesNetStatesgetAdjagetBaselinegetEdgeAnnotgetObsMatgetSampleAdjagetSampleAdjaMADkfoldCVloocvsummarizeRepl
Dependencies:BiocGenericsbitopsgenericsgraphKEGGgraphlpSolveRCurlRgraphvizXML
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Network Inference Of Perturbation Data Using a Linear Programming Approach. | lpNet-package lpNet |
| Calculate Activation Matrix | calcActivation |
| Calculate Predicted Observation. | calcPredictionKfoldCV calcPredictionLOOCV |
| Compute Range Of Penalty Parameter Lambda. | calcRangeLambda |
| Cross-validation | kfoldCV loocv |
| Do The Network Inference With The Linear Programming Approach. | doILP |
| Generate Time Series Network States | generateTimeSeriesNetStates |
| Get Adjacency Matrix. | getAdja |
| Get Baseline Vector. | getBaseline |
| Get the annotation of the edges. | getEdgeAnnot |
| Get Observation Matrix. | getObsMat |
| Get The Sample Adjacency. | getSampleAdja getSampleAdjaMAD |
| Summarize Replicate Measurements | summarizeRepl |
