SCMeTA: a pipeline for single-cell metabolic analysis data processing

被引：1
|
作者：
Pan, Xingyu [1 ]
Pan, Siyuan [1 ]
Du, Murong [1 ]
Yang, Jinlei [1 ]
Yao, Huan [2 ]
Zhang, Xinrong [1 ]
Zhang, Sichun [1 ]
机构：
[1] Tsinghua Univ, Dept Chem, Beijing 100084, Peoples R China
[2] Natl Inst Metrol China, Div Chem Metrol & Analyt Sci, Beijing 100029, Peoples R China
来源：
BIOINFORMATICS | 2024年 / 40卷 / 09期
基金：
中国国家自然科学基金;
关键词：
MASS-SPECTROMETRY;
D O I：
10.1093/bioinformatics/btae545
中图分类号：
Q5 [生物化学];
学科分类号：
071010 ; 081704 ;
摘要：
To address the challenges in single-cell metabolomics (SCM) research, we have developed an open-source Python-based modular library, named SCMeTA, for SCM data processing. We designed standardized pipeline and inter-container communication format and have developed modular components to adapt to the diverse needs of SCM studies. The validation was carried out on multiple SCM experiment data. The results demonstrated significant improvements in batch effects, accuracy of results, metabolic extraction rate, cell matching rate, as well as processing speed. This library is of great significance in advancing the practical application of SCM analysis and makes a foundation for wide-scale adoption in biological studies.Availability and implementation SCMeTA is freely available on https://github.com/SCMeTA/SCMeTA and https://doi.org/10.5281/zenodo.13569643.
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收藏
页数：4
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