{"doi":"10.1093/aje/kwae006","title":"Omics feature selection with the extended SIS R package: identification of a body mass index epigenetic multimarker in the Strong Heart Study","abstract":"The statistical analysis of omics data poses a great computational challenge given their ultra-high-dimensional nature and frequent between-features correlation. In this work, we extended the iterative sure independence screening (ISIS) algorithm by pairing ISIS with elastic-net (Enet) and 2 versions of adaptive elastic-net (adaptive elastic-net (AEnet) and multistep adaptive elastic-net (MSAEnet)) to efficiently improve feature selection and effect estimation in omics research. We subsequently used genome-wide human blood DNA methylation data from American Indian participants in the Strong Heart Study (n = 2235 participants; measured in 1989-1991) to compare the performance (predictive accuracy, coefficient estimation, and computational efficiency) of ISIS-paired regularization methods with that of a bayesian shrinkage and traditional linear regression to identify an epigenomic multimarker of body mass index (BMI). ISIS-AEnet outperformed the other methods in prediction. In biological pathway enrichment analysis of genes annotated to BMI-related differentially methylated positions, ISIS-AEnet captured most of the enriched pathways in common for at least 2 of all the evaluated methods. ISIS-AEnet can favor biological discovery because it identifies the most robust biological pathways while achieving an optimal balance between bias and efficient feature selection. In the extended SIS R package, we also implemented ISIS paired with Cox and logistic regression for time-to-event and binary endpoints, respectively, and a bootstrap approach for the estimation of regression coefficients.","journal":"American Journal of Epidemiology","year":2024,"id":475438,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":3,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9548,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1312174,"name":"Feng Yang","orcid":"0000-0002-7183-5756","position":1,"is_corresponding":false},{"id":761174,"name":"Zulema Rodriguez-Hernandez","orcid":"0000-0003-0720-384X","position":2,"is_corresponding":false},{"id":532081,"name":"Karin Haack","orcid":"0000-0003-3067-3575","position":3,"is_corresponding":false},{"id":246476,"name":"Shelley A. Cole","orcid":"0000-0002-2651-0127","position":4,"is_corresponding":false},{"id":288772,"name":"Ana Navas‐Acién","orcid":"0000-0001-9824-7797","position":5,"is_corresponding":false},{"id":604511,"name":"María Téllez-Plaza","orcid":"0000-0002-3850-1228","position":6,"is_corresponding":false},{"id":1112746,"name":"José D. Bermúdez","orcid":"0000-0003-4699-5923","position":7,"is_corresponding":false},{"id":400145,"name":"Arce Domingo‐Relloso","orcid":"0000-0001-6928-8290","position":0,"is_corresponding":true}],"reference_count":58,"raw_metadata":null,"created_at":"2026-07-19T02:06:16.992586Z","pmid":"38375692","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}