Enrichment analysis for spatial and single-cell metabolomics accounting for molecular ambiguity.

IF 2.4 Q2 MATHEMATICAL & COMPUTATIONAL BIOLOGY

Bioinformatics advances Pub Date : 2025-05-21 eCollection Date: 2025-01-01 DOI:10.1093/bioadv/vbaf100

Bishoy Wadie, Martijn R Molenaar, Lucas M Vieira, Theodore Alexandrov

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引用次数: 0

Abstract

Summary: Imaging mass spectrometry (imaging MS) has advanced spatial and single-cell metabolomics, but the reliance on MS1 data complicates the accurate identification of molecular structures, not being able to resolve isomeric and isobar molecules. This prevents application of conventional methods for overrepresentation analysis (ORA) and metabolite set enrichment analysis (MSEA). To address this, we introduce S2IsoMEr R package and a web app for METASPACE, which uses bootstrapping to propagate isomeric/isobaric ambiguities into the enrichment analysis. We demonstrate S2IsoMEr for single-cell metabolomics and the METASPACE web app for spatial metabolomics.

Availability and implementation: METASPACE web app can be used on existing and new datasets submitted to METASPACE (https://metaspace2020.org). The source code for the S2IsoMEr R package is available on GitHub (https://github.com/alexandrovteam/S2IsoMEr).

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空间和单细胞代谢组学的富集分析解释了分子模糊性。

摘要：成像质谱（Imaging MS）具有先进的空间和单细胞代谢组学，但对MS1数据的依赖使分子结构的准确鉴定变得复杂，无法分辨同分异构体和等压分子。这阻止了传统方法的过度代表性分析（ORA）和代谢物集富集分析（MSEA）的应用。为了解决这个问题，我们引入了S2IsoMEr R包和METASPACE的web应用程序，该应用程序使用引导将异构体/等压性模糊传播到富集分析中。我们展示了S2IsoMEr单细胞代谢组学和METASPACE网络应用程序的空间代谢组学。可用性和实现：METASPACE web应用程序可以在提交给METASPACE的现有和新数据集上使用（https://metaspace2020.org）。S2IsoMEr R包的源代码可以在GitHub上获得（https://github.com/alexandrovteam/S2IsoMEr）。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Bioinformatics advances

CiteScore

1.60

自引率

0.00%

发文量