Package: iC10 2.0.2
iC10: A Copy Number and Expression-Based Classifier for Breast Tumours
Implementation of the classifier described in the paper Ali HR et al (2014) <doi:10.1186/s13059-014-0431-1>. It uses copy number and/or expression form breast cancer data, trains a Tibshirani's 'pamr' classifier with the features available and predicts the iC10 group.
Authors:
iC10_2.0.2.tar.gz
iC10_2.0.2.zip(r-4.5)iC10_2.0.2.zip(r-4.4)iC10_2.0.2.zip(r-4.3)
iC10_2.0.2.tgz(r-4.4-any)iC10_2.0.2.tgz(r-4.3-any)
iC10_2.0.2.tar.gz(r-4.5-noble)iC10_2.0.2.tar.gz(r-4.4-noble)
iC10_2.0.2.tgz(r-4.4-emscripten)iC10_2.0.2.tgz(r-4.3-emscripten)
iC10.pdf |iC10.html✨
iC10/json (API)
NEWS
| # Install 'iC10' in R: |
| install.packages('iC10', repos = c('https://rueda-lab.r-universe.dev', 'https://cloud.r-project.org')) |
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:6aaca03625. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Sep 18 2024 |
| R-4.5-win | OK | Sep 18 2024 |
| R-4.5-linux | OK | Sep 18 2024 |
| R-4.4-win | OK | Sep 18 2024 |
| R-4.4-mac | OK | Sep 18 2024 |
| R-4.3-win | OK | Sep 18 2024 |
| R-4.3-mac | OK | Sep 18 2024 |
Exports:comparegoodnessOfFitiC10matchFeaturesnormalizeFeatures
Dependencies:clusteriC10TrainingDataimputelatticeMatrixpamrsurvival
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| A Copy Number and Expression-Based Classifier for Breast Tumours | iC10-package |
| Compare results of the iC10 classifier | compare compare.iC10 |
| Internal function for matching copy number features. | getCNfeatures |
| Internal function for matching expression features. | getExpfeatures |
| Goodness of fit results of the iC10 classifier | goodnessOfFit goodnessOfFit.iC10 |
| A copy number and expression-based classfier for breast cancers | iC10 |
| Matching features from the classifier to the test data. | matchFeatures |
| Normalization of expression features | normalizeFeatures |
| Plot results of the iC10 classifier | plot.iC10 |
| Print results of the iC10 classifier | print.iC10 |
| Summary results of the iC10 classifier | summary.iC10 |
