FDR-controlled metabolite annotation for high-resolution imaging mass spectrometry
FDR-controlled metabolite annotation for high-resolution imaging mass spectrometry
复制标题
DOI：
10.1038/nmeth.4072
复制
发表时间：
2017-01-01
期刊：
影响因子：
48
通讯作者：
Alexandrov, Theodore
中科院分区：
文献类型：
--
作者：
Palmer, Andrew;Phapale, Prasad;Alexandrov, Theodore
高质量分辨率成像质谱法有望定位组织，细胞培养物和琼脂平板中的数百种代谢物，具有细胞分辨率，但由于缺乏用于自动代谢物鉴定的生物信息学工具而受到阻碍。我们报告了pySM，这是一个在分子总和公式水平上进行错误发现率（FDR）控制的代谢物注释的框架，用于高质量分辨率成像质谱（https：//github.com/alexandrovteam/pySM）。我们引入了一个代谢信号匹配分数和目标诱饵FDR估计空间代谢组学。
High-mass-resolution imaging mass spectrometry promises to localize hundreds of metabolites in tissues, cell cultures, and agar plates with cellular resolution, but it is hampered by the lack of bioinformatics tools for automated metabolite identification. We report pySM, a framework for false discovery rate (FDR)-controlled metabolite annotation at the level of the molecular sum formula, for high-mass-resolution imaging mass spectrometry (https://github.com/alexandrovteam/pySM). We introduce a metabolite-signal match score and a target decoy FDR estimate for spatial metabolomics.