FlowAtlas: an interactive tool for high-dimensional immunophenotyping analysis bridging FlowJo with computational tools in Julia.
Front Immunol
; 15: 1425488, 2024.
Article
in En
| MEDLINE
| ID: mdl-39086484
ABSTRACT
As the dimensionality, throughput and complexity of cytometry data increases, so does the demand for user-friendly, interactive analysis tools that leverage high-performance machine learning frameworks. Here we introduce FlowAtlas an interactive web application that enables dimensionality reduction of cytometry data without down-sampling and that is compatible with datasets stained with non-identical panels. FlowAtlas bridges the user-friendly environment of FlowJo and computational tools in Julia developed by the scientific machine learning community, eliminating the need for coding and bioinformatics expertise. New population discovery and detection of rare populations in FlowAtlas is intuitive and rapid. We demonstrate the capabilities of FlowAtlas using a human multi-tissue, multi-donor immune cell dataset, highlighting key immunological findings. FlowAtlas is available at https//github.com/gszep/FlowAtlas.jl.git.
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Software
/
Immunophenotyping
/
Computational Biology
/
Flow Cytometry
Limits:
Humans
Language:
En
Journal:
Front Immunol
Year:
2024
Document type:
Article