{"doi":"10.1093/gigascience/giaa162","title":"Lilikoi V2.0: a deep learning–enabled, personalized pathway-based R package for diagnosis and prognosis predictions using metabolomics data","abstract":"BACKGROUND: previously we developed Lilikoi, a personalized pathway-based method to classify diseases using metabolomics data. Given the new trends of computation in the metabolomics field, it is important to update Lilikoi software. RESULTS: here we report the next version of Lilikoi as a significant upgrade. The new Lilikoi v2.0 R package has implemented a deep learning method for classification, in addition to popular machine learning methods. It also has several new modules, including the most significant addition of prognosis prediction, implemented by Cox-proportional hazards model and the deep learning-based Cox-nnet model. Additionally, Lilikoi v2.0 supports data preprocessing, exploratory analysis, pathway visualization, and metabolite pathway regression. CONCULSION: Lilikoi v2.0 is a modern, comprehensive package to enable metabolomics analysis in R programming environment.","journal":"GigaScience","year":2021,"id":177033,"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":20,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.873,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2021-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":299155,"name":"Yu Liu","orcid":"0000-0002-8631-4347","position":1,"is_corresponding":false},{"id":563000,"name":"Zhijie Ren","orcid":"0000-0002-1065-7941","position":2,"is_corresponding":false},{"id":563001,"name":"Yuheng Du","orcid":"0000-0001-6665-5892","position":3,"is_corresponding":false},{"id":299154,"name":"Qianhui Huang","orcid":"0000-0002-3292-7519","position":4,"is_corresponding":false},{"id":556394,"name":"Lana X. Garmire","orcid":"0000-0002-4654-2126","position":5,"is_corresponding":false},{"id":562999,"name":"Xinying Fang","orcid":"0000-0001-9121-5717","position":0,"is_corresponding":true}],"reference_count":44,"raw_metadata":null,"created_at":"2026-07-18T23:47:28.018172Z","pmid":"33484242","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":[]}