Package: sigminer.prediction 0.2.0
sigminer.prediction: Train and Predict Cancer Subtype with Keras Model based on Mutational Signatures
Mutational signatures represent mutational processes occured in cancer evolution, thus are stable and genetic resources for subtyping. This tool provides functions for training neutral network models to predict the subtype a sample belongs to based on 'keras' and 'sigminer' packages.
Authors:
sigminer.prediction_0.2.0.tar.gz
sigminer.prediction_0.2.0.zip(r-4.5)sigminer.prediction_0.2.0.zip(r-4.4)sigminer.prediction_0.2.0.zip(r-4.3)
sigminer.prediction_0.2.0.tgz(r-4.4-any)sigminer.prediction_0.2.0.tgz(r-4.3-any)
sigminer.prediction_0.2.0.tar.gz(r-4.5-noble)sigminer.prediction_0.2.0.tar.gz(r-4.4-noble)
sigminer.prediction_0.2.0.tgz(r-4.4-emscripten)sigminer.prediction_0.2.0.tgz(r-4.3-emscripten)
sigminer.prediction.pdf |sigminer.prediction.html✨
sigminer.prediction/json (API)
# Install 'sigminer.prediction' in R: |
install.packages('sigminer.prediction', repos = c('https://shixiangwang.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/shixiangwang/sigminer.prediction/issues
kerasmutational-signaturesprostate-cancersigminer
Last updated 2 years agofrom:0572bfc65f. Checks:OK: 1 ERROR: 6. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 14 2024 |
R-4.5-win | ERROR | Nov 14 2024 |
R-4.5-linux | ERROR | Nov 14 2024 |
R-4.4-win | ERROR | Nov 14 2024 |
R-4.4-mac | ERROR | Nov 14 2024 |
R-4.3-win | ERROR | Nov 14 2024 |
R-4.3-mac | ERROR | Nov 14 2024 |
Exports:batch_modeling_and_fittingcopy_modellist_trained_modelsload_trained_modelmodeling_and_fittingprepare_datatidy
Dependencies:abindbackportsbase64encBiobaseBiocGenericsBiocManagerbootbroomcarcarDatacaretclasscliclockclustercodetoolscolorspaceconfigcorrplotcowplotcpp11data.tableDerivdiagramdigestDNAcopydoBydoParalleldplyre1071fansifarverforeachFormulafurrrfuturefuture.applygenericsggplot2ggpubrggrepelggsciggsignifglobalsgluegowergridBasegridExtragtablehardhathereipredisobanditeratorsjsonlitekerasKernSmoothlabelinglatticelavalifecyclelistenvlme4lubridatemaftoolsmagrittrMASSMatrixMatrixModelsmgcvmicrobenchmarkminqaModelMetricsmodelrmunsellnlmenloptrNMFnnetnumDerivparallellypbkrtestpheatmappillarpkgconfigplyrpngpolynompROCprocessxprodlimprogressrproxypspurrrquantregR6rappdirsRColorBrewerRcppRcppEigenRcppTOMLrecipesregistryreshape2reticulateRhtslibrlangrngtoolsrpartrprojrootrstatixrstudioapiscalesshapesigminerSparseMSQUAREMstringistringrsurvivaltensorflowtfautographtfrunstibbletidyrtidyselecttimechangetimeDatetzdbutf8vctrsviridisLitewhiskerwithryamlzeallotzlibbioc
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Construct A Batch of Keras Models | batch_modeling_and_fitting |
Copy Model File | copy_model |
List Current Available Trained Keras Models | list_trained_models |
Load Trained Models | load_trained_model |
Create 5-layer Keras Model and Fitting Datasets | modeling_and_fitting |
Prepare Training and Test Dataset | prepare_data |
Tidy Modeling Result | tidy |