{"doi":"10.1101/2023.05.02.538599","title":"Enhanced Feature Selection for Microbiome Data using FLORAL: Scalable Log-ratio Lasso Regression","abstract":"Identifying predictive biomarkers of patient outcomes from high-throughput microbiome data is of high interest, while existing computational methods do not satisfactorily account for complex survival endpoints, longitudinal samples, and taxa-specific sequencing biases. We present FLORAL (https://vdblab.github.io/FLORAL/), an open-source computational tool to perform scalable log-ratio lasso regression and microbial feature selection for continuous, binary, time-to-event, and competing risk outcomes, with compatibility of longitudinal microbiome data as time-dependent covariates. The proposed method adapts the augmented Lagrangian algorithm for a zero-sum constraint optimization problem while enabling a two-stage screening process for extended false-positive control. In extensive simulation and real-data analyses, FLORAL achieved consistently better false-positive control compared to other lasso-based approaches, and better sensitivity over popular differential abundance testing methods for datasets with smaller sample size. In a survival analysis in allogeneic hematopoietic-cell transplant, we further demonstrated considerable improvement by FLORAL in microbial feature selection by utilizing longitudinal microbiome data over only using baseline microbiome data.","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2023,"id":394500,"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":0.9455,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":811257,"name":"Tyler Funnell","orcid":"0000-0003-1612-5644","position":1,"is_corresponding":false},{"id":813064,"name":"Nicholas R. Waters","orcid":"0000-0002-9035-2143","position":2,"is_corresponding":false},{"id":1169070,"name":"Sandeep Raj","orcid":"0000-0003-4629-0528","position":3,"is_corresponding":false},{"id":1027946,"name":"Keimya Sadeghi","orcid":"0000-0001-5473-1747","position":4,"is_corresponding":false},{"id":298456,"name":"Anqi Dai","orcid":"0000-0003-3106-4624","position":5,"is_corresponding":false},{"id":767161,"name":"Oriana Miltiadous","orcid":"0000-0002-1571-3893","position":6,"is_corresponding":false},{"id":55979,"name":"Roni Shouval","orcid":"0000-0001-9827-8032","position":7,"is_corresponding":false},{"id":1169071,"name":"Meng Lv","orcid":"0000-0001-6625-9523","position":8,"is_corresponding":false},{"id":225648,"name":"Jonathan U. Peled","orcid":"0000-0002-4029-7625","position":9,"is_corresponding":false},{"id":108872,"name":"Doris M. Ponce","orcid":"0000-0002-9422-5766","position":10,"is_corresponding":false},{"id":108873,"name":"Miguel‐Angel Perales","orcid":"0000-0002-5910-4571","position":11,"is_corresponding":false},{"id":266133,"name":"Mithat Gönen","orcid":"0000-0001-8683-8477","position":12,"is_corresponding":false},{"id":108880,"name":"Marcel R.M. van den Brink","orcid":"0000-0003-0696-4401","position":13,"is_corresponding":false},{"id":457319,"name":"Teng Fei","orcid":"0000-0001-7888-1715","position":0,"is_corresponding":true}],"reference_count":84,"raw_metadata":null,"created_at":"2026-07-19T01:19:14.590635Z","pmid":"37205350","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":[]}