{"id":24528955,"url":"https://github.com/saezlab/lipyd","last_synced_at":"2025-06-17T08:05:55.236Z","repository":{"id":77872773,"uuid":"43946333","full_name":"saezlab/lipyd","owner":"saezlab","description":"Python module for lipidomics LC MS/MS data analysis","archived":false,"fork":false,"pushed_at":"2024-06-27T11:31:30.000Z","size":18767,"stargazers_count":15,"open_issues_count":1,"forks_count":3,"subscribers_count":4,"default_branch":"master","last_synced_at":"2025-04-14T17:11:24.025Z","etag":null,"topics":["lc-msms","lipidomics","openms","python"],"latest_commit_sha":null,"homepage":"https://saezlab.github.io/lipyd","language":"Python","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.rst","changelog":"HISTORY.rst","contributing":null,"funding":null,"license":"LICENSE.txt","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":"2015-10-09T09:35:30.000Z","updated_at":"2025-04-09T10:10:38.000Z","dependencies_parsed_at":"2025-01-22T07:44:20.139Z","dependency_job_id":null,"html_url":"https://github.com/saezlab/lipyd","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/saezlab/lipyd","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/saezlab%2Flipyd","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/saezlab%2Flipyd/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/saezlab%2Flipyd/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/saezlab%2Flipyd/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/saezlab","download_url":"https://codeload.github.com/saezlab/lipyd/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/saezlab%2Flipyd/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":260318656,"owners_count":22991118,"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":["lc-msms","lipidomics","openms","python"],"created_at":"2025-01-22T07:34:11.692Z","updated_at":"2025-06-17T08:05:55.211Z","avatar_url":"https://github.com/saezlab.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"*lipyd* – A Python module for lipidomics LC MS/MS data analysis\n===============================================================\n\nThis module implements methods and workflows for MS/MS lipidomics data\nanalysis. Runs primarily in Python 3 but also in Python 2.7.x.\n\nInput and preprocessing\n-----------------------\n\nAt reading raw mass spec data from mzML files, peak picking and feature\ndetection we rely on the `OpenMS \u003chttp://openms.de/\u003e`_ library. This ensures\ncomputationally efficient processing by well established methods. As our\nOpenMS integration is not yet complete we provide a temporary solution to\nread already preprocessed features from CSV files exported by the\n`PEAKS \u003chttp://www.bioinfor.com/peaks-studio/\u003e`_ software. We are not\ncomfortable with the idea of building on expensive proprietary software and\nin the near future we will provide complete integration with OpenMS.\n\nMetabolite database lookup\n--------------------------\n\nThe ``lipyd.modb`` module provides an unified interface to standard\ndatabases like `SwissLipids \u003chttps://swisslipids.org/\u003e`_ and\n`LipidMaps \u003chttp://lipidmaps.org/\u003e`_ In addition it is able to generate\ncustom metabolite masses.\nWith the default settings the database consists of more than\n100 thousands of lipid species. The ``lipyd.lipid`` module\ncontains more than 150 predefined lipid classes and it's easy to define\nnew ones. The ``Sample`` and ``SampleSet`` objects in\n``lipyd.sample``, which represent a series of features, support\nthe automatic lookup in the databases.\n\nMS2 spectrum identification\n---------------------------\n\nThe ``lipyd.ms2`` module contains generic classes to support the\nanalysis and identification of MS2 spectra. Based on around 50 standards\nrun by our group and reviewing many spectra from publications and\ndatabases we created bult in rules for identification of more than 80\nlipid classes. You can modify the methods or create new ones by writing\nPython methods. However we are working on\n`MFQL \u003chttps://wiki.mpi-cbg.de/lipidx/LipidXplorer_MFQL\u003e`_ integration to\nprovide a more standard way of defining rules. Also we will introduce\nsimilarity search against spectrum databases.\n\nFeature filtering, post-processing\n----------------------------------\n\nThe ``lipyd.sample`` and ``lipyd.feature`` modules provide\nclasses for analysis of features optionally in relation to other variables\nand filter them. Analysis and filtering of the features can be done\nbefore or after the lipid identification. Doing it before reduces the\nnumber of MS2 spectra to be analyzed this way saving time. In the future\nwe will add more utilities to build arrays of features and also MS2\nfragments across arbitrary number of experiments to provide opportunities\nfor higher level analysis.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsaezlab%2Flipyd","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsaezlab%2Flipyd","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsaezlab%2Flipyd/lists"}