wavFeatExt
Wavelet-based Feature Extraction for Copy-number Alteration Data
Bioconductor version: 3.23 · Package version: 1.0.0
Other Bioconductor versions
devel is the development version; release is the current stable one.
3.24 (devel), 3.23 (release)
Provides tools for simulating copy-number alteration (CNA) profiles, applying a non-decimated Haar wavelet transform to genomic signals, and extracting wavelet-derived features for use in supervised learning. Multiple machine learning methods including lasso and elastic-net regularisation, random forest, partial least squares, neural networks and k-nearest neighbours are implemented to train predictive models from genomic feature vectors. The workflow enables end-to-end analysis from CNA simulation to feature extraction and classification.
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("wavFeatExt")Details
| Maintainer | Maharani Ahsani Ummi <maharaniahsani@itb.ac.id> |
| Author | Maharani Ahsani Ummi [aut, cre], Arief Gusnanto [aut] |
| License | GPL-3 |
| URL | https://github.com/maharaniau/wavFeatExt |
| Bug Reports | https://github.com/maharaniau/wavFeatExt/issues |
| Source branch | RELEASE_3_23 |
| Build report | Bioconductor build system, r-universe |
| biocViews | Classification, CopyNumberVariation, FeatureExtraction, GenomicVariation, Software |
| Package Short Url | https://bioconductor.org/packages/wavFeatExt/ |
Citation
From within R, enter citation("wavFeatExt"):
Maharani Ahsani Ummi, Arief Gusnanto. wavFeatExt: Wavelet-based Feature Extraction for Copy-number Alteration Data. doi:10.18129/B9.bioc.wavFeatExt, R package version 1.0.0, https://bioconductor.org/packages/wavFeatExt.
Generated from the package metadata; it may differ from the package's own citation.
Documentation
Download
Follow the installation instructions to use this package in your R session.
| Source package | wavFeatExt_1.0.0.tar.gz |
| Windows binary (x86_64) | wavFeatExt_1.0.0.zip |
| macOS binary (arm64) | wavFeatExt_1.0.0.tgz |
| macOS binary (x86_64) | wavFeatExt_1.0.0.tgz |
Dependencies
Depends: R (>= 4.5)
Imports: DNAcopy, wavethresh, MASS, randomForest, glmnet, pROC, neuralnet, e1071, class, caret, ica, stats, graphics, utils, pls, matrixStats
Suggests: BiocStyle, knitr, rmarkdown, testthat (>= 3.0.0)