Package: IntegratedLearner 0.99.0

Nalin Arora

IntegratedLearner: Integrated Multi-Omics Learning for Survival and Other Outcomes

Provides a unified interface for multi-omics prediction using early, late, and intermediate fusion for continuous, binary, multiclass, and survival outcomes. It supports both MultiAssayExperiment and PCL-style inputs, performs input validation and feature/sample harmonization across layers, and provides model fitting, prediction, plotting, and variable-importance utilities.

Authors:Nalin Arora [aut, cre, cph], Anupreet Porwal [aut], Himel Mallick [aut]

IntegratedLearner_0.99.0.tar.gz
IntegratedLearner_0.99.0.zip(r-4.7)IntegratedLearner_0.99.0.zip(r-4.6)IntegratedLearner_0.99.0.zip(r-4.5)
IntegratedLearner_0.99.0.tgz(r-4.6-any)IntegratedLearner_0.99.0.tgz(r-4.5-any)
IntegratedLearner_0.99.0.tar.gz(r-4.7-any)IntegratedLearner_0.99.0.tar.gz(r-4.6-any)
IntegratedLearner_0.99.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
IntegratedLearner/json (API)
NEWS

# Install 'IntegratedLearner' in R:

install.packages('IntegratedLearner', repos = c('https://biocstaging.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/himelmallick/integratedlearner/issues

Datasets:

FranzosaE_2019_CuratedMetabolome - Franzosa et al. 2019 training metabolome table
FranzosaE_2019_CuratedMetadata - Franzosa et al. 2019 training metadata
FranzosaE_2019_CuratedSpeciesProfile - Franzosa et al. 2019 training species profile
FranzosaE_2019_Validation_CuratedMetabolome - Franzosa et al. 2019 validation metabolome table
FranzosaE_2019_Validation_CuratedMetadata - Franzosa et al. 2019 validation metadata
FranzosaE_2019_Validation_CuratedSpeciesProfile - Franzosa et al. 2019 validation species profile
gene_all - TCGA BRCA gene-level table
mir_all - TCGA BRCA microRNA-level table
NLIBD - NLIBD binary-outcome PCL fixture
pregnancy - Pregnancy continuous-outcome PCL fixture
PRISM - PRISM binary-outcome PCL fixture

On CRAN:

software classification survival microbiome

4.19 score 11 scripts 14 exports 101 dependencies

Last updated from:2952c7c8ee. Checks:1 NOTE, 9 OK. Indexed: yes.

Target	Result	Time
bioc-checks	NOTE	203
linux-devel-x86_64	OK	237
source / vignettes	OK	354
linux-release-x86_64	OK	250
macos-release-arm64	OK	151
macos-oldrel-arm64	OK	160
windows-devel	OK	177
windows-release	OK	184
windows-oldrel	OK	176
wasm-release	OK	170

Exports:auc.obj IL_conbin IL_multiclass IL_survival ILsurv IntegratedLearner NNLS SL.BART SL.enet SL.glmnet2 SL.horseshoe SL.LASSO SL.mxBART SL.nnls.auc

Dependencies:abind Biobase BiocBaseUtils BiocGenerics bitops caret caTools class cli clock codetools cpp11 cvAUC data.table DelayedArray diagram digest dplyr e1071 farver foreach future future.apply gam generics GenomicRanges ggplot2 glmnet globals glue gower gplots gtable gtools hardhat ipred IRanges isoband iterators KernSmooth labeling lattice lava lifecycle listenv lubridate magrittr MASS Matrix MatrixGenerics matrixStats ModelMetrics MultiAssayExperiment nlme nnet nnls numDeriv parallelly pillar pkgconfig plyr pROC prodlim progressr proxy purrr R6 ranger RColorBrewer Rcpp RcppEigen recipes reshape2 rlang ROCR rpart S4Arrays S4Vectors S7 scales Seqinfo shape SparseArray sparsevctrs SQUAREM stringi stringr SummarizedExperiment SuperLearner survival tibble tidyr tidyselect timechange timeDate tzdb utf8 vctrs viridisLite withr XVector

IntegratedLearner

Nalin Arora, Anupreet Porwal and Himel Mallick

Rendered fromIntegratedLearner.Rmdusingknitr::rmarkdownon Jun 09 2026.

Last update: 2026-06-09
Started: 2025-11-13

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Title Meta level Objective function: NNLS for gaussian; Rank loss for binary observations	auc.obj
Franzosa et al. 2019 training metabolome table	FranzosaE_2019_CuratedMetabolome
Franzosa et al. 2019 training metadata	FranzosaE_2019_CuratedMetadata
Franzosa et al. 2019 training species profile	FranzosaE_2019_CuratedSpeciesProfile
Franzosa et al. 2019 validation metabolome table	FranzosaE_2019_Validation_CuratedMetabolome
Franzosa et al. 2019 validation metadata	FranzosaE_2019_Validation_CuratedMetadata
Franzosa et al. 2019 validation species profile	FranzosaE_2019_Validation_CuratedSpeciesProfile
TCGA BRCA gene-level table	gene_all
Integrated machine learning for multi-omics prediction (continuous/binary outcomes)	IL_conbin
Integrated machine learning for multi-omics multiclass classification	IL_multiclass
IntegratedLearner Survival Engine	ILsurv IL_survival
Integrated machine learning for multi-omics prediction and classification	IntegratedLearner
TCGA BRCA microRNA-level table	mir_all
NLIBD binary-outcome PCL fixture	NLIBD
NNLS function to optimize weights of several base learners	NNLS
Plot the summary curves produced by an IntegratedLearner object	plot.learner
Make predictions using a trained 'IntegratedLearner' model	predict.learner
Predict function for SL.BART	predict.SL.BART
Predict function for SL.nnls.auc	predict.SL.nnls.auc
Pregnancy continuous-outcome PCL fixture	pregnancy
PRISM binary-outcome PCL fixture	PRISM
Wrapper for bartMachine learner	SL.BART
Elastic net regression, including lasso and ridge with optimized alpha and lambda	SL.enet
Elastic net regression, including lasso and ridge with a fixed alpha	SL.glmnet2
Horseshoe regression	SL.horseshoe
Elastic net regression, including lasso and ridge with a fixed alpha	SL.LASSO
mxBART SuperLearner wrapper	SL.mxBART
Combined SuperLearner function for both NNLS/AUC maximization	SL.nnls.auc
Update IntegratedLearner fit object based on layers available in the test set	update.learner