rIDIMS: A novel tool for processing direct-infusion mass spectrometry data

被引:0
|
作者
Mansoldo, Felipe R. P. [1 ]
Lima, Iasmim Lopes de [2 ,3 ]
Carvalho, Caroline Pais de [2 ,3 ]
Silva, Adriano R. J. da [2 ,3 ]
Eberlin, Marcos Nogueira [2 ,3 ]
Vermelho, Alane Beatriz [1 ]
机构
[1] Fed Univ Rio Janeiro UFRJ, Inst Microbiol Paulo Goes, BIOINOVAR Biotechnol Labs Biocatalysis Bioprod & B, BR-21941902 Rio De Janeiro, Brazil
[2] Univ Prebiteriana Mackenzie, Sch Engn, MackMass Lab Mass Spectrometry, PPGEMN, Sao Paulo, Brazil
[3] Mackenzie Inst Res Graphene & Nanotechnol, Sao Paulo, Brazil
关键词
Metabolomics; Direct infusion mass spectrometry; MasSpec pen; Ambient ionization; Graphical user interface for mass spectrometry; data processing; COFFEE VARIETIES; ROBUSTA COFFEES; R-PACKAGE; ELECTROSPRAY; ARABICA; METABOLOMICS; ACID; MS; QUANTIFICATION; DISCRIMINATION;
D O I
10.1016/j.talanta.2024.127273
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Metabolomics using mass spectrometry-only (MS) analysis either by continuous or intermittent direct infusion (DIMS) and ambient ionization techniques (AMS) has grown in popularity due to their rapid, high-throughput nature and the advantage of performing fast analysis with minimal or no sample pretreatments. But currently, end-users without programming knowledge do not find applications with Graphical User Interface (GUI) specialized in processing DIMS or AMS data. Specifically, there is a lack of standardized workflow for processing data from limited sample sizes and scans from different total ion chronograms (TIC).To address this gap, we present rIDIMS, a browser-based application that offers a straightforward and fast workflow focusing on highquality scan selection, grouping of isotopologues and adducts, data alignment, binning, and filtering. We also introduce a novel function for selecting TIC scans that is reproducible and statistically reliable, which is a feature particularly useful for studies with limited sample sizes. After processing in rIDIMS, the result is exported in an HTML report document that presents publication-quality figures, statistical data and tables, ready to be customized and exported. We demonstrate rIDIMS functionality in three cases: (i) Classification of coffee bean species through the chemical profile obtained with Mass Spec Pen; (ii) Public repository DIMS data from lipid profiling in monogenic insulin resistance syndromes, and (iii) Lipids for lung cancer classification. We show that our implementation facilitates the processing of AMS and DIMS data through an easy and intuitive interface, contributing to reproducible and reliable metabolomic investigations. Indeed, rIDIMS function asa user-friendly GUI based Shiny web application for intuitive use by end-users (available at https://github.com/BioinovarLab/ rIDIMS).
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页数:13
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