PICAFlow: a complete R workflow dedicated to flow/mass cytometry data, from pre-processing to deep and comprehensive analysis

被引:2
作者
Regnier, Paul [1 ,2 ,5 ]
Marques, Cindy [1 ,2 ,3 ,4 ]
Saadoun, David [1 ,2 ,3 ,4 ]
机构
[1] Sorbonne Univ, INSERM UMR S 959, Immunol Immunopathol Immunotherapy Lab I3, F-75005 Paris, France
[2] Assistance Publ Hop Paris AP HP, Inflammat Immunopathol Biotherapy Dept DHU I2B, Biotherapy Unit CIC BTi, Grp Hosp Pitie Salpetriere, F-75013 Paris, France
[3] Sorbonne Univ, Grp Hosp Pitie Salpetriere, AP HP, Dept Med Interne & Immunol Clin, F-75013 Paris, France
[4] Ctr Natl Reference Malad Autoinflammatoires & Amyl, Ctr Natl Reference Malad Autoimmunes Syst Rares, Inflammat Immunopathol Biotherapy Dept DMU 3iD, F-75013 Paris, France
[5] Hop La Pitie Salpetriere, ILab I3, Batiment CERVI 2eme Etage, 47-83 Blvd Hop, F-75013 Paris, France
来源
BIOINFORMATICS ADVANCES | 2023年 / 3卷 / 01期
关键词
CELLS;
D O I
10.1093/bioadv/vbad177
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
PICAFlow is a R-written integrative workflow dedicated to flow/mass cytometry data handling, from pre-processing to deep and comprehensive analysis. It is designed as a powerful all-in-one tool which contains all the necessary functions and packages presented in a user-friendly and ease-to-use fashion. PICAFlow also includes important features that are very frequently lacking in other close software, such as interactive R Shiny applications for real-time data transformation and compensation as well as normalization methods aiming to remove batch effects and unwanted inter- and intra-group heterogeneity. It also allows to perform dimensionality reduction, cell clustering (using different available approaches), as well as complementary statistical analyses and export different support for data interpretation and visualization. Availability PICAFlow is available as a R-written package hosted at the following GitHub repository: https://github.com/PaulRegnier/PICAFlow and is complemented by a fully detailed tutorial available at the following URL: https://paul-regnier.fr/tutoriel-picaflow/.
引用
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页数:6
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