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代谢组学学习笔记：从基础原理到 MetaboAnalystR 实践

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TL;DR — A WeChat study-notes post (生信技能树) walking from metabolomics fundamentals (NMR/GC-MS/LC-MS principles, sampling and QC design) to hands-on installation and use of the R packages MetaboAnalystR and OptiLCMS. It matters as a practical, reproducible-pipeline guide for researchers moving metabolomics analysis off the web GUI into scripted, server-side workflows.

  • Method framing: Untargeted LC-HRMS "casts a wide net" to find differential features defined by m/z + retention time (relative/semi-quantitative), then targeted LC-MS/MS with isotope internal standards and calibration curves gives absolute quantification; NMR adds high-confidence structure elucidation (¹H/¹³C, COSY/HSQC/HMBC) without database matching, but needs higher concentration and cost.
  • Experimental design/QC: Metabolites of interest are ~50–1500 Da; samples must be snap-frozen at −80 °C, run in one batch, randomized by generator, with pooled QC samples (e.g., one per 10-sample block) randomly interspersed — never running in group order.
  • Separation tech: HPLC (3.5–5 μm particles, ~5000 psi) vs UPLC (1.7–2 μm, >25000 psi); LC-MS is the default, GC-MS reserved for volatiles since sublimation degrades structure and accuracy.
  • Tooling practicalities: MetaboAnalyst covers normalization, PCA/PLS-DA/OPLS-DA, KEGG/SMPDB pathway and joint transcriptome–metabolite analysis; the post gives concrete workarounds — pacman Bioconductor deps, install_github("xia-lab/MetaboAnalystR"), manual OptiLCMS source install with a missing #include patch in mzClust.cpp, and a recommendation to pin R 4.2 for dependency compatibility.

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代谢组学学习笔记：从基础原理到 MetaboAnalystR 实践

WeChat: 生信技能树 2026-08-09 doi:10.1021/acs.analchem.6c00361
Public signals OpenAlex citations 4
Providers: Hugging Face · N/A OpenAlex · Citations 4 Publisher · N/A Semantic Scholar · N/A X · N/A Fetched 2026-09-09 08:18:24.776697 UTC

TL;DR — A WeChat study-notes post (生信技能树) walking from metabolomics fundamentals (NMR/GC-MS/LC-MS principles, sampling and QC design) to hands-on installation and use of the R packages MetaboAnalystR and OptiLCMS. It matters as a practical, reproducible-pipeline guide for researchers moving metabolomics analysis off the web GUI into scripted, server-side workflows.

  • Method framing: Untargeted LC-HRMS "casts a wide net" to find differential features defined by m/z + retention time (relative/semi-quantitative), then targeted LC-MS/MS with isotope internal standards and calibration curves gives absolute quantification; NMR adds high-confidence structure elucidation (¹H/¹³C, COSY/HSQC/HMBC) without database matching, but needs higher concentration and cost.
  • Experimental design/QC: Metabolites of interest are ~50–1500 Da; samples must be snap-frozen at −80 °C, run in one batch, randomized by generator, with pooled QC samples (e.g., one per 10-sample block) randomly interspersed — never running in group order.
  • Separation tech: HPLC (3.5–5 μm particles, ~5000 psi) vs UPLC (1.7–2 μm, >25000 psi); LC-MS is the default, GC-MS reserved for volatiles since sublimation degrades structure and accuracy.
  • Tooling practicalities: MetaboAnalyst covers normalization, PCA/PLS-DA/OPLS-DA, KEGG/SMPDB pathway and joint transcriptome–metabolite analysis; the post gives concrete workarounds — pacman Bioconductor deps, install_github("xia-lab/MetaboAnalystR"), manual OptiLCMS source install with a missing #include patch in mzClust.cpp, and a recommendation to pin R 4.2 for dependency compatibility.
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