Enhanced Feature Selection for Microbiome Data using FLORAL: Scalable Log-ratio Lasso Regression.

Autor:	Fei T; Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center., Funnell T; Department of Immunology, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center., Waters NR; Department of Immunology, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center., Raj SS; Department of Medicine, Memorial Sloan Kettering Cancer Center., Sadeghi K; Department of Immunology, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center., Dai A; Department of Immunology, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center., Miltiadous O; Department of Pediatrics, Memorial Sloan Kettering Cancer Center., Shouval R; Adult Bone Marrow Transplantation Service, Department of Medicine, Memorial Sloan Kettering Cancer Center.; Department of Medicine, Weill Cornell Medical College., Lv M; Institute of Hematology, Peking University People's Hospital., Peled JU; Adult Bone Marrow Transplantation Service, Department of Medicine, Memorial Sloan Kettering Cancer Center.; Department of Medicine, Weill Cornell Medical College., Ponce DM; Adult Bone Marrow Transplantation Service, Department of Medicine, Memorial Sloan Kettering Cancer Center.; Department of Medicine, Weill Cornell Medical College., Perales MA; Adult Bone Marrow Transplantation Service, Department of Medicine, Memorial Sloan Kettering Cancer Center.; Department of Medicine, Weill Cornell Medical College., Gönen M; Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center., van den Brink MRM; City of Hope Los Angeles and City of Hope National Medical Center.
Jazyk:	angličtina
Zdroj:	BioRxiv : the preprint server for biology [bioRxiv] 2023 Dec 18. Date of Electronic Publication: 2023 Dec 18.
DOI:	10.1101/2023.05.02.538599
Abstrakt:	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. Competing Interests: Authors’ Disclosures J.U. Peled reports research funding, intellectual property fees, and travel reimbursement from Seres Therapeutics, and consulting fees from DaVolterra, CSL Behring, Crestone Inc, and from MaaT Pharma. He serves on an Advisory board of and holds equity in Postbiotics Plus Research. He has filed intellectual property applications related to the microbiome (reference numbers #62/843,849, #62/977,908, and #15/756,845). D.M. Ponce has served as advisory board member for Evive Biotechnology (Shanghai) Ltd (formerly Generon [Shanghai] Corporation Ltd), she served as advisory board member or consultant of Sanofi Corporation, CareDx, Ceramedix, Incyte, and receives research funding from Takeda Corporation and Incyte. M.-A. Perales reports honoraria from Adicet, Allovir, Caribou Biosciences, Celgene, Bristol-Myers Squibb, Equilium, Exevir, Incyte, Karyopharm, Kite/Gilead, Merck, Miltenyi Biotec, MorphoSys, Nektar Therapeutics, Novartis, Omeros, OrcaBio, Syncopation, VectivBio AG, and Vor Biopharma. He serves on DSMBs for Cidara Therapeutics, Medigene, and Sellas Life Sciences, and the scientific advisory board of NexImmune. He has ownership interests in NexImmune and Omeros. He has received institutional research support for clinical trials from Incyte, Kite/Gilead, Miltenyi Biotec, Nektar Therapeutics, and Novartis. M.R.M. van den Brink has received research support and stock options from Seres Therapeutics and stock options from Notch Therapeutics and Pluto Therapeutics; he has received royalties from Wolters Kluwer; has consulted, received honorarium from or participated in advisory boards for Seres Therapeutics, Vor Biopharma, Rheos Medicines, Frazier Healthcare Partners, Nektar Therapeutics, Notch Therapeutics, Ceramedix, Lygenesis, Pluto Therapeutics, GlaskoSmithKline, Da Volterra, Thymofox, Garuda, Novartis (Spouse), Synthekine (Spouse), Beigene (Spouse), Kite (Spouse); he has IP Licensing with Seres Therapeutics and Juno Therapeutics; and holds a fiduciary role on the Foundation Board of DKMS (a nonprofit organization). Memorial Sloan Kettering Cancer Center (MSK) has institutional financial interests relative to Seres Therapeutics.
Databáze:	MEDLINE
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