{"id":13680957,"url":"https://github.com/lazear/sage","last_synced_at":"2026-01-28T12:19:55.422Z","repository":{"id":46591468,"uuid":"515039720","full_name":"lazear/sage","owner":"lazear","description":"Proteomics search \u0026 quantification so fast that it feels like magic","archived":false,"fork":false,"pushed_at":"2025-12-04T19:43:16.000Z","size":9567,"stargazers_count":261,"open_issues_count":21,"forks_count":56,"subscribers_count":14,"default_branch":"master","last_synced_at":"2025-12-08T03:32:15.531Z","etag":null,"topics":["bioinformatics","mass-spectrometry","proteomics"],"latest_commit_sha":null,"homepage":"https://sage-docs.vercel.app","language":"Rust","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/lazear.png","metadata":{"files":{"readme":"README.md","changelog":"CHANGELOG.md","contributing":"CONTRIBUTING.md","funding":null,"license":"LICENSE","code_of_conduct":"CODE_OF_CONDUCT.md","threat_model":null,"audit":null,"citation":"CITATION.cff","codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2022-07-18T04:55:55.000Z","updated_at":"2025-12-04T19:43:21.000Z","dependencies_parsed_at":"2025-12-05T14:03:53.744Z","dependency_job_id":null,"html_url":"https://github.com/lazear/sage","commit_stats":null,"previous_names":[],"tags_count":36,"template":false,"template_full_name":null,"purl":"pkg:github/lazear/sage","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lazear%2Fsage","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lazear%2Fsage/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lazear%2Fsage/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lazear%2Fsage/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/lazear","download_url":"https://codeload.github.com/lazear/sage/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lazear%2Fsage/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":28845107,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-01-28T10:53:21.605Z","status":"ssl_error","status_checked_at":"2026-01-28T10:53:20.789Z","response_time":57,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"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":["bioinformatics","mass-spectrometry","proteomics"],"created_at":"2024-08-02T13:01:24.281Z","updated_at":"2026-01-28T12:19:55.393Z","avatar_url":"https://github.com/lazear.png","language":"Rust","funding_links":[],"categories":["3. Raw data search software/algorithms"],"sub_categories":["Table of Contents"],"readme":"\u003cimg src=\"figures/logo.png\" width=\"300\"\u003e\n\n# Sage: proteomics searching so fast it seems like magic\n\n[![Rust](https://github.com/lazear/sage/actions/workflows/rust.yml/badge.svg)](https://github.com/lazear/sage/actions/workflows/rust.yml) [![Anaconda-Server Badge](https://anaconda.org/bioconda/sage-proteomics/badges/version.svg)](https://anaconda.org/bioconda/sage-proteomics)\n\n\nFor more information please read [the online documentation!](https://sage-docs.vercel.app/docs)\n\n\n# Introduction\n \nSage is, at it's core, a proteomics database search engine - \n    a tool that transforms raw mass spectra from proteomics experiments into peptide identifications \n    via database searching \u0026 spectral matching. \n\nHowever, Sage includes a variety of advanced features that make it a one-stop shop: retention time prediction, quantification (both isobaric \u0026 LFQ), peptide-spectrum match rescoring, and FDR control. You can directly use results from Sage without needing to use other tools for these tasks.\n\nAdditionally, Sage was designed with cloud computing in mind - massively parallel processing and the ability to directly stream compressed mass spectrometry data to/from AWS S3 enables unprecedented search speeds with minimal cost. \n\n Sage also runs just as well reading local files from your Mac/PC/Linux device!\n\n## Why use Sage instead of other tools?\n\nSage is **simple to configure**, **powerful** and **flexible**. \nIt also happens to be well-tested, **mind-boggingly fast**, open-source (MIT-licensed) and free.\n\n## Citation\n\nIf you use Sage in a scientific publication, please cite the following paper:\n\n[Sage: An Open-Source Tool for Fast Proteomics Searching and Quantification at Scale](https://doi.org/10.1021/acs.jproteome.3c00486)\n\n\n## Features\n\n- Incredible performance out of the box\n- [Effortlessly cross-platform](https://sage-docs.vercel.app/docs/started#download-the-latest-binary-release) (Linux/MacOS/Windows), effortlessly parallel (uses all of your CPU cores)\n- [Fragment indexing strategy](https://sage-docs.vercel.app/docs/how_it_works) allows for blazing fast narrow and open searches (\u003e 500 Da precursor tolerance)\n- [Isobaric quantification](https://sage-docs.vercel.app/docs/how_it_works#tmt-based) (MS2/MS3-TMT, or custom reporter ions)\n- [Label-free quantification](https://sage-docs.vercel.app/docs/how_it_works#label-free): consider all charge states \u0026 isotopologues *a la* FlashLFQ\n- Capable of searching for [chimeric/co-fragmenting spectra](https://sage-docs.vercel.app/docs/configuration/additional)\n- Wide-window (dynamic precursor tolerance) search mode - [enables WWA/PRM/DIA searches](https://sage-docs.vercel.app/docs/configuration/tolerance#wide-window-mode)\n- Retention time prediction models fit to each LC/MS run\n- [PSM rescoring](https://sage-docs.vercel.app/docs/how_it_works#machine-learning-for-psm-rescoring) using built-in linear discriminant analysis (LDA)\n- PEP calculation using a non-parametric model (KDE)\n- FDR calculation using target-decoy competition and picked-peptide \u0026 picked-protein approaches\n- Percolator/Mokapot [compatible output](https://sage-docs.vercel.app/docs/configuration#env)\n- Configuration by [JSON file](https://sage-docs.vercel.app/docs/configuration#file)\n- Built-in support for reading gzipped-mzML files\n- Support for reading/writing directly from [AWS S3](https://sage-docs.vercel.app/docs/configuration/aws)\n\n## Interoperability\n\nSage is well-integrated into the open-source proteomics ecosystem. The following projects support analyzing results from Sage (typically in addition to other tools), or redistribute Sage binaries for use in their pipelines. \n\n- [SearchGUI](http://compomics.github.io/projects/searchgui): a graphical user interface for running searches\n- [PeptideShaker](http://compomics.github.io/projects/peptide-shaker): visualize peptide-spectrum matches\n- [MS2Rescore](http://compomics.github.io/projects/ms2rescore): AI-assisted rescoring of results\n- [Picked group FDR](https://github.com/kusterlab/picked_group_fdr): scalable protein group FDR for large-scale experiments\n- [sagepy](https://github.com/theGreatHerrLebert/sagepy): Python bindings to the sage-core library\n- [quantms](https://github.com/bigbio/quantms): nextflow pipeline for running searches with Sage\n- [OpenMS](https://github.com/OpenMS/OpenMS): Sage is included as a \"TOPP\" tool in OpenMS\n- [sager](https://github.com/UCLouvain-CBIO/sager): R package for analyzing results from Sage searches\n- [Sage results to mzIdentML](https://github.com/magnuspalmblad/shic/blob/main/shims/Peptide_identification_in_TSV_to_Peptide_identification_in_mzIdentML.sh): Bash script to convert `results.sage.tsv` files to mzIdentML\n- [i2MassChroQ](http://pappso.inrae.fr/bioinfo/i2masschroq/): a graphical user interface for proteomics analysis\n- [annotator](https://github.com/snijderlab/annotator): a graphical user interface for visualizing peptide-spectrum matches\n- [rustyms](https://gtihub.com/snijderlab/rustyme): a Rust library (with Python bindings) to handle peptides and identified peptide files\n- If your project supports Sage and it's not listed, please open a pull request! If you need help integrating or interfacing with Sage in some way, please reach out.\n\nCheck out the (now outdated) [blog post introducing the first version of Sage](https://lazear.github.io/sage/) for more information and full benchmarks!\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flazear%2Fsage","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Flazear%2Fsage","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flazear%2Fsage/lists"}