上海交通大学学报（医学版）

上海交通大学学报（医学版）

• 技术与方法 • 上一篇    

代谢物批量定量工具的开发与应用

卫润民1，黄凤杰1,2，谢 燮1，池 逸2，郑晓皎2，赵爱华2，陈天璐2   

  1. 1.上海交通大学 药学院， 上海 200240； 2.上海交通大学附属第六人民医院转化医学中心， 上海 200233
  • 出版日期:2015-01-28 发布日期:2015-01-29
  • 作者简介:卫润民(1989—)， 男， 硕士生; 电子信箱: wander1021@gmail.com。

Development and application of metabolite batch quantitative tool

WEI Run-min1, HUANG Feng-jie1,2, XIE Xie1, CHI Yi2, ZHENG Xiao-jiao2, ZHAO Ai-hua2, CHEN Tian-lu2   

  1. 1.Shanghai Jiao Tong University School of Pharmacy, Shanghai 200240, China; 2.Center for Translational Medicine, the Sixth People's Hospital, Shanghai Jiao Tong University, Shanghai 200233, China
  • Online:2015-01-28 Published:2015-01-29

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摘要：

目的 针对代谢组学研究中的定量分析需求，开发一款可以自动绘制标准曲线和定量计算的软件工具，并采用该工具对一批临床血清样本进行定量计算。方法 使用代谢物批量定量工具对临床血清样本的代谢组学检测结果进行定量计算，包括建立标准曲线、自动拟合和手动拟合及样本中代谢物的定量。结果 建立40个代谢物的标准曲线，对90例临床血清样本进行定量计算，获得绝对浓度。结论 代谢物批量定量工具可以对代谢组学研究中批量样本的大量代谢产物进行快速定量计算。软件具备数据变换和缺失值补充等基本数据预处理功能。该软件的应用有助于提升代谢组学物质定量环节的自动化和标准化程度，有效降低人为因素导致的误差，提高数据分析的效率和准确性。

关键词: 代谢组学, 定量, 自动化

Abstract:

Objective To develop a software that can automatically draw standard curves and perform quantitative computations according to the requirements of quantitative analysis in metabolomics researches and to perform quantitative computations for clinical serum samples. Methods Quantitative computations were performed by the metabolite batch quantitative tool based on the results of metabolomics detections of clinical serum samples, including establishing standard curves, automatic and manual fitting, and quantifying metabolites in samples. Results A total of 40 standard curves of metabolites were established. Ninety clinical serum samples were quantified and their absolute concentrations were obtained. Conclusion The metabolite batch quantitative tool can perform quick quantitative computations for a large number of metabolites in batch samples during the course of metabolomics researches and can provide basic data pre-processing functions, such as data transformation and missing data filling, etc. The software is helpful for improving the automation and standardization levels of metabolite quantification, efficiently reducing human errors, and increasing the efficiency and accuracy of data analysis.

Key words: metabolomics, quantification, automatic