Daniel S Hitchcock, Jesse N Krejci, Chloe E Sturgeon, Courtney A Dennis, Sarah T Jeanfavre, Julian R Avila-Pacheco, Clary B Clish
{"title":"Eclipse: A Python package for alignment of two or more nontargeted LC-MS metabolomics datasets.","authors":"Daniel S Hitchcock, Jesse N Krejci, Chloe E Sturgeon, Courtney A Dennis, Sarah T Jeanfavre, Julian R Avila-Pacheco, Clary B Clish","doi":"10.1093/bioinformatics/btaf290","DOIUrl":null,"url":null,"abstract":"<p><p>Nontargeted LC-MS metabolomics datasets contain a wealth of information but present many challenges during analysis and processing. Often, two or more independently processed datasets must be aligned to form a complete dataset, but existing software does not fully meet our needs. For this, we have created an open-source Python package called Eclipse. Eclipse uses a novel graph-based approach to handle complex matching scenarios that arise from n > 2 datasets.</p><p><strong>Availability and implementation: </strong>Eclipse is open source (https://github.com/broadinstitute/bmxp) and can be installed via \"pip install bmxp\".</p><p><strong>Supplementary information: </strong>Supplementary data are available at Bioinformatics online.</p>","PeriodicalId":93899,"journal":{"name":"Bioinformatics (Oxford, England)","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Bioinformatics (Oxford, England)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/bioinformatics/btaf290","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Nontargeted LC-MS metabolomics datasets contain a wealth of information but present many challenges during analysis and processing. Often, two or more independently processed datasets must be aligned to form a complete dataset, but existing software does not fully meet our needs. For this, we have created an open-source Python package called Eclipse. Eclipse uses a novel graph-based approach to handle complex matching scenarios that arise from n > 2 datasets.
Availability and implementation: Eclipse is open source (https://github.com/broadinstitute/bmxp) and can be installed via "pip install bmxp".
Supplementary information: Supplementary data are available at Bioinformatics online.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
