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Recent technological advances have enable the simultaneous collection of multi-omics data i.e., different types or modalities of molecular data, presenting challenges for integrative prediction modeling due to the heterogeneous, high-dimensional nature and possible missing modalities of some individuals. We introduce this package for late integrative prediction modeling, enabling modality-specific variable selection and prediction modeling, followed by the aggregation of the modality-specific predictions to train a final meta-model. This package facilitates conducting late integration predictive modeling in a systematic, structured, and reproducible way.
Version: | 0.0.1 |
Depends: | R (≥ 3.6.0) |
Imports: | R6, stats, digest |
Suggests: | testthat (≥ 3.0.0), UpSetR (≥ 1.4.0), caret, ranger, glmnet, Boruta, knitr, rmarkdown, pROC, checkmate |
Published: | 2024-12-17 |
DOI: | 10.32614/CRAN.package.fuseMLR |
Author: | Cesaire J. K. Fouodo [aut, cre] |
Maintainer: | Cesaire J. K. Fouodo <cesaire.kuetefouodo at uni-luebeck.de> |
BugReports: | https://github.com/imbs-hl/fuseMLR/issues |
License: | GPL-3 |
NeedsCompilation: | no |
Materials: | README |
CRAN checks: | fuseMLR results |
Reference manual: | fuseMLR.pdf |
Vignettes: |
How does fuseMLR work? (source, R code) |
Package source: | fuseMLR_0.0.1.tar.gz |
Windows binaries: | r-devel: fuseMLR_0.0.1.zip, r-release: fuseMLR_0.0.1.zip, r-oldrel: fuseMLR_0.0.1.zip |
macOS binaries: | r-release (arm64): fuseMLR_0.0.1.tgz, r-oldrel (arm64): fuseMLR_0.0.1.tgz, r-release (x86_64): fuseMLR_0.0.1.tgz, r-oldrel (x86_64): fuseMLR_0.0.1.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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