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bio-metabolomics-targeted-analysis

维护者 FreedomIntelligence · 最近更新 2026年4月1日

Targeted metabolomics analysis using MRM/SRM with standard curves. Covers absolute quantification, method validation, and quality assessment. Use when quantifying specific metabolites using calibration curves and internal standards.

OpenClawNanoClaw分析处理复现实验bio-metabolomics-targeted-analysis🧬 bioinformatics (gptomics bio-* suite)bioinformatics — proteomics & metabolomicstargeted

原始来源

FreedomIntelligence/OpenClaw-Medical-Skills

https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/bio-metabolomics-targeted-analysis

维护者
FreedomIntelligence
许可
MIT
最近更新
2026年4月1日

技能摘要

来自 SKILL.md 的关键信息

2 min

核心说明

  • CLI：Skyline ，用于 peak integration 、 export。
  • Python/R：calibration curve fitting 、 sample quantification。
  • Quantify specific metabolites ，面向 my MRM data" → Perform absolute quantification ，使用 calibration curves，internal standards，、 quality assessment ，用于 targeted metabolomics. CLI：Skyline ，用于 peak integration 、 export Python/R：calibration curve fitting 、 sample quantification。
  • skyline_data <- read.csv('skyline_export.csv')。

原始文档

SKILL.md 摘录

Filter to quantifier transitions

quant_data <- skyline_data %>% filter(Quantitative == TRUE | is.na(Quantitative))

Pivot to matrix format

intensity_matrix <- quant_data %>% select(Replicate, Molecule, Area) %>% pivot_wider(names_from = Replicate, values_from = Area)


## Standard curve data

standards <- data.frame(
    concentration = c(0, 1, 5, 10, 50, 100, 500, 1000),  # nM
    area = c(100, 5000, 25000, 50000, 240000, 480000, 2300000, 4500000)
)

适用场景

  • 适合在quantifying specific metabolites ，使用 calibration curves 、 internal standards时使用。

不适用场景

  • Do not rely on this catalog entry alone ，用于 installation 或 maintenance details。

上游相关技能

  • xcms-preprocessing - Peak detection for targeted features
  • normalization-qc - QC-based normalization
  • statistical-analysis - Group comparisons

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