Package: asmbPLS 1.0.0

Runzhi Zhang

asmbPLS: Predicting and Classifying Patient Phenotypes with Multi-Omics Data

Adaptive Sparse Multi-block Partial Least Square, a supervised algorithm, is an extension of the Sparse Multi-block Partial Least Square, which allows different quantiles to be used in different blocks of different partial least square components to decide the proportion of features to be retained. The best combinations of quantiles can be chosen from a set of user-defined quantiles combinations by cross-validation. By doing this, it enables us to do the feature selection for different blocks, and the selected features can then be further used to predict the outcome. For example, in biomedical applications, clinical covariates plus different types of omics data such as microbiome, metabolome, mRNA data, methylation data, copy number variation data might be predictive for patients outcome such as survival time or response to therapy. Different types of data could be put in different blocks and along with survival time to fit the model. The fitted model can then be used to predict the survival for the new samples with the corresponding clinical covariates and omics data. In addition, Adaptive Sparse Multi-block Partial Least Square Discriminant Analysis is also included, which extends Adaptive Sparse Multi-block Partial Least Square for classifying the categorical outcome.

Authors:Runzhi Zhang [aut, cre], Susmita Datta [aut, ths]

asmbPLS_1.0.0.tar.gz
asmbPLS_1.0.0.tar.gz(r-4.5-noble)asmbPLS_1.0.0.tar.gz(r-4.4-noble)
asmbPLS_1.0.0.tgz(r-4.4-emscripten)asmbPLS_1.0.0.tgz(r-4.3-emscripten)
asmbPLS.pdf |asmbPLS.html
asmbPLS/json (API)

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

Peer review:

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
Datasets:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

openblascppopenmp

2.88 score 15 scripts 234 downloads 15 exports 69 dependencies

Last updated 2 years agofrom:09734978c2. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKDec 07 2024
R-4.5-linux-x86_64OKDec 07 2024

Exports:asmbPLS.cvasmbPLS.fitasmbPLS.predictasmbPLSDA.cvasmbPLSDA.fitasmbPLSDA.predictasmbPLSDA.vote.fitasmbPLSDA.vote.predictmbPLS.fitmeanimpplotCorplotPLSplotRelevancequantileCombto.categorical

Dependencies:abindbackportsbootbroomcarcarDataclicolorspacecorrplotcowplotcpp11DerivdoBydplyrfansifarverFormulagenericsggplot2ggpubrggrepelggsciggsignifgluegridExtragtableisobandlabelinglatticelifecyclelme4magrittrMASSMatrixMatrixModelsmgcvmicrobenchmarkminqamodelrmunsellnlmenloptrnnetnumDerivpbkrtestpillarpkgconfigpolynompurrrquantregR6RColorBrewerRcppRcppArmadilloRcppEigenrlangrstatixscalesSparseMstringistringrsurvivaltibbletidyrtidyselectutf8vctrsviridisLitewithr

Tutorial for asmbPLS package

Rendered fromasmbPLS_tutorial.Rmdusingknitr::rmarkdownon Dec 07 2024.

Last update: 2023-04-17
Started: 2023-04-17