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Flow cytometry data analysis: Recent tools and algorithms
Author(s) -
Montante Sebastiano,
Brinkman Ryan R.
Publication year - 2019
Publication title -
international journal of laboratory hematology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.705
H-Index - 55
eISSN - 1751-553X
pISSN - 1751-5521
DOI - 10.1111/ijlh.13016
Subject(s) - bottleneck , computer science , algorithm , sample (material) , data mining , data science , chemistry , embedded system , chromatography
Flow cytometry ( FCM ) allows scientists to rapidly quantify up to 50 parameters for millions of cells per sample. The bottleneck in the application of the technology is data analysis, and the high number of parameters measured by the current generation of instruments requires the use of advanced computational algorithms to make full use of their capabilities. This review summarizes the main steps of FCM data analysis, focusing on the use of the most recent bioinformatic tools developed for an R‐based programming environment. In particular, for each stage of the data analysis, libraries and packages currently available are listed, and a brief description of their functioning is included.