{"id":24528935,"url":"https://github.com/saezlab/ocean","last_synced_at":"2025-04-14T17:10:42.512Z","repository":{"id":45652090,"uuid":"320298367","full_name":"saezlab/ocean","owner":"saezlab","description":"R package for metabolic enzyme enrichment anaylsis","archived":false,"fork":false,"pushed_at":"2024-11-08T13:00:25.000Z","size":28105,"stargazers_count":12,"open_issues_count":0,"forks_count":4,"subscribers_count":4,"default_branch":"master","last_synced_at":"2025-03-28T05:51:03.314Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"R","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/saezlab.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2020-12-10T14:34:04.000Z","updated_at":"2025-02-11T15:43:19.000Z","dependencies_parsed_at":"2025-01-22T07:44:16.730Z","dependency_job_id":null,"html_url":"https://github.com/saezlab/ocean","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/saezlab%2Focean","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/saezlab%2Focean/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/saezlab%2Focean/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/saezlab%2Focean/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/saezlab","download_url":"https://codeload.github.com/saezlab/ocean/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248923764,"owners_count":21183954,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2025-01-22T07:34:08.986Z","updated_at":"2025-04-14T17:10:42.493Z","avatar_url":"https://github.com/saezlab.png","language":"R","funding_links":[],"categories":[],"sub_categories":[],"readme":"# ocean: an R package for metabolic enzyme enrichment anaylsis\n\n![](https://github.com/saezlab/ocean/blob/master/man/figures/full_logo.png?raw=true)\n\n## Overview\n\nThe functional insights that metabolomic data sets contain currently lies\nunder-exploited. This is in part due to the complexity of metabolic reaction\nnetworks and the indirect relationship between reaction fluxes and metabolite\nabundance. Yet, footprint-based methods have been available for decades in the\ncontext of other omic data sets such as transcriptomic and phosphoproteomic.\nHere, we present ocEAn, a method that defines metabolic enzyme footprint from a\ncurated reduced version of the recon2 reaction network and use them to explore\ncoordinated deregulations of metabolite abundances with respect to their\nposition relative to metabolic enzymes in the same manner as Kinase-substrate\nand TF-targets Enrichment analysis. This picture diplays the TCA cycle with\nderegulated metabolites and estimated metabolic enzyme deregulations in kidney\ncancer. You can generate a dynamic visualisation of this network and other\npathways by following\n[our tutorial](https://saezlab.github.io/ocean/articles/ocean_intro.html).\n\n![Workflow](https://github.com/saezlab/ocean/blob/master/man/figures/Summary.png?raw=true)\n\n![Result](https://github.com/saezlab/ocean/blob/master/man/figures/TCA_shot.png?raw=true)\n\n## Tutorial\n\nInstal the package (from github with remotes) :\n\n```r\n## If needed install the remotes and BiocManager packages\ninstall.packages(\"remotes\")\ninstall.packages(\"BiocManager\")\n\n## instal ocean\nremotes::install_github(\"saezlab/ocean\", repos = BiocManager::repositories())\n```\n\nYou can then run the\n[tutorial scripts](https://saezlab.github.io/ocean/articles/ocean_intro.html)\nwith a kidney cancer toy metabolomic dataset.\n\nyou can find a lightweight tutorial R script [here](https://github.com/saezlab/ocean/blob/master/vignettes/tutorial_ocEAn.R) \n\nPLEASE READ THE TUTORIAL CAREFULLY :) and do not hesitate to have an extensive\nlook at all the variable in it and what information they contain.\n\nA new updated tutorial that showcase how ocean results can be used in parallel\nwith proteomic data will be comming soon!\n\n## Citations\n\nocEAn manuscript: Sciacovelli, Dugourd et al. Nitrogen partitioning between\nbranched-chain amino acids and urea cycle enzymes sustains renal cancer\nprogression; 2022 https://pubmed.ncbi.nlm.nih.gov/36539415/\n\nTo reproduce the result of this manuscript, install ocEAn from the branch\n\"marco_paper\".\n\nThe underlying metabolic model is based on a curated reduced model of human\nmetabolism, see: Masid M, Ataman M \u0026 Hatzimanikatis V (2020) Analysis of human\nmetabolism by reducing the complexity of the genome-scale models using\nredHUMAN.\nNat Commun 11: 2821 https://www.nature.com/articles/s41467-020-16549-2#Tab1\n\nThe scripts to process the redHuman model into the oCEan format can be found\nhere: https://github.com/saezlab/redHuman_models\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsaezlab%2Focean","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsaezlab%2Focean","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsaezlab%2Focean/lists"}