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immunaut: Machine Learning Immunogenicity and Vaccine Response Analysis

Used for analyzing immune responses and predicting vaccine efficacy using machine learning and advanced data processing techniques. 'Immunaut' integrates both unsupervised and supervised learning methods, managing outliers and capturing immune response variability. It performs multiple rounds of predictive model testing to identify robust immunogenicity signatures that can predict vaccine responsiveness. The platform is designed to handle high-dimensional immune data, enabling researchers to uncover immune predictors and refine personalized vaccination strategies across diverse populations.

Version: 1.0.1
Depends: R (≥ 3.4.0)
Imports: cluster, plyr, dplyr, caret, pROC, PRROC, stats, rlang, Rtsne, dbscan, FNN, igraph, fpc, mclust, ggplot2, grDevices, RColorBrewer, R.utils, clusterSim, parallel, doParallel
Published: 2024-10-25
DOI: 10.32614/CRAN.package.immunaut
Author: Ivan Tomic ORCID iD [aut, cre, cph], Adriana Tomic ORCID iD [aut, ctb, cph, fnd], Stephanie Hao ORCID iD [aut]
Maintainer: Ivan Tomic <info at ivantomic.com>
BugReports: https://github.com/atomiclaboratory/immunaut/issues
License: GPL-3
URL: https://github.com/atomiclaboratory/immunaut, <https://atomic-lab.org>
NeedsCompilation: no
Materials: README
CRAN checks: immunaut results

Documentation:

Reference manual: immunaut.pdf

Downloads:

Package source: immunaut_1.0.1.tar.gz
Windows binaries: r-devel: immunaut_1.0.1.zip, r-release: immunaut_1.0.1.zip, r-oldrel: immunaut_1.0.1.zip
macOS binaries: r-release (arm64): immunaut_1.0.1.tgz, r-oldrel (arm64): immunaut_1.0.1.tgz, r-release (x86_64): immunaut_1.0.1.tgz, r-oldrel (x86_64): immunaut_1.0.1.tgz
Old sources: immunaut archive

Linking:

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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.