flowAI: automatic and interactive anomaly discerning tools for flow cytometry data
Author:
Affiliation:
1. Singapore Immunology Network (SIgN), Agency for Science Technology and Research (A*STAR), Singapore 138648, Singapore
2. Integrative Genomics of Ageing Group, Institute of Integrative Biology, University of Liverpool, Liverpool L69 7ZB, UK
Abstract
Publisher
Oxford University Press (OUP)
Subject
Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability
Link
http://academic.oup.com/bioinformatics/article-pdf/32/16/2473/39715346/bioinformatics_32_16_2473.pdf
Reference36 articles.
1. Critical assessment of automated flow cytometry data analysis techniques;Aghaeepour;Nat. Methods,2013
2. Quality Control in Flow Cytometry
3. A survey of flow cytometry data analysis methods;Bashashati;Adv. Bioinf,2009
4. High-dimensional analysis of the murine myeloid cell system;Becher;Nat. Immunol,2014
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