SCMeTA: a pipeline for single-cell metabolic analysis data processing.
Bioinformatics
; 40(9)2024 Sep 02.
Article
em En
| MEDLINE
| ID: mdl-39240328
ABSTRACT
SUMMARY:
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.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Software
/
Metabolômica
/
Análise de Célula Única
Limite:
Humans
Idioma:
En
Ano de publicação:
2024
Tipo de documento:
Article