Package: immunaut 1.0.1

Ivan Tomic

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.

Authors:Ivan Tomic [aut, cre, cph], Adriana Tomic [aut, ctb, cph, fnd], Stephanie Hao [aut]

immunaut_1.0.1.tar.gz
immunaut_1.0.1.tar.gz(r-4.5-noble)immunaut_1.0.1.tar.gz(r-4.4-noble)
immunaut_1.0.1.tgz(r-4.4-emscripten)immunaut_1.0.1.tgz(r-4.3-emscripten)
immunaut.pdf |immunaut.html
immunaut/json (API)

# Install 'immunaut' in R:
install.packages('immunaut', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/atomiclaboratory/immunaut/issues

Datasets:
  • immunautDemo - Demo data set from immunaut package. This data is used in this package examples. It consist of 4x4 feature matrix + additional dummy columns that can be used for testing.

1.70 score 5 exports 99 dependencies

Last updated 28 days agofrom:9e24608880. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 26 2024
R-4.5-linuxOKOct 26 2024

Exports:auto_simon_mlgenerate_demo_datagenerate_file_headerimmunautplot_clustered_tsne

Dependencies:ade4caretclasscliclockclusterclusterSimcodetoolscolorspacecpp11data.tabledbscanDEoptimRdiagramdigestdiptestdoParalleldplyre1071fansifarverflexmixFNNforeachfpcfuturefuture.applygenericsggplot2globalsgluegowergtablehardhatigraphipredisobanditeratorskernlabKernSmoothlabelinglatticelavalifecyclelistenvlubridatemagrittrMASSMatrixmclustmgcvModelMetricsmodeltoolsmunsellnlmennetnumDerivparallellypillarpixmappkgconfigplyrprabcluspROCprodlimprogressrproxyPRROCpurrrR.methodsS3R.ooR.utilsR6RColorBrewerRcppRcppArmadillorecipesreshape2rlangrobustbaserpartRtsnescalesshapespSQUAREMstringistringrsurvivaltibbletidyrtidyselecttimechangetimeDatetzdbutf8vctrsviridisLitewithr