stabel: An R package for variable selection and prediction in high-dimensional cross-sectional data.

Apu Chandra Das, Ran Dai, Alyssa Bouska, Javeed Iqbal, Lynette M Smith

Abstract read

In one paragraph

Article in Software impacts, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed

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1 · What the graph read from it

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2 · The registry

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Apu Chandra DasDepartment of Biostatistics, University of Nebraska Medical Center, 984375 Nebraska Medical Center, Omaha, 68198, Nebraska, USA.

Ran DaiDepartment of Biostatistics, University of Nebraska Medical Center, 984375 Nebraska Medical Center, Omaha, 68198, Nebraska, USA.

Alyssa BouskaDepartment of Pathology, Microbiology and Immunology, University of Nebraska Medical Center, 984375, Nebraska Medical Center, Omaha, 68198, Nebraska, USA.

Javeed IqbalDepartment of Pathology, Microbiology and Immunology, University of Nebraska Medical Center, 984375, Nebraska Medical Center, Omaha, 68198, Nebraska, USA.

Lynette M SmithDepartment of Biostatistics, University of Nebraska Medical Center, 984375 Nebraska Medical Center, Omaha, 68198, Nebraska, USA.

Funding

Pre-analytical variables of bioanalytes affecting the accuracy of PTCL diagnostic and prognostic genetic signaturesU01CA253218 · NCI · UNIVERSITY OF NEBRASKA MEDICAL CENTER · PI IQBAL, JAVEED, MURTAZA, MUHAMMED · 2021 to 2025

$1.8M

NCI NIH HHS U01 CA253218

6 · The paper itself

Abstract

Variable selection is crucial in high-dimensional biomedical research, yet many methods are unstable and select irrelevant variables. Stability selection improves robustness but may miss important variables and does not offer prediction. To address these limitations, we developed stabel, an R package, a framework that integrates multiple stability selection procedures with diverse models and subsampling strategies, followed by ensemble-based prediction. The package supports binary and continuous outcomes, offering LASSO, sparseSVM, and random forest for variable selection, and any prediction algorithm available in the SuperLearner package. stabel provides a flexible and reliable tool for high-dimensional variable selection and prediction.

Indexed as

Ensemble learningPredictionstabelStability selectionVariable selection

Identifiers

PMID42877674

DOI10.1016/j.simpa.2026.100856

PMCPMC13662937

What OpenQuestion holds

Textmetadata

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.