Cyto-Feature Engineering: A Pipeline for Flow Cytometry Analysis to Uncover Immune Populations and Associations with Disease

ABSTRACT:Flow cytometers can now analyze up to 50 parameters per cell and millions of cells per sample; however, conventional methods to analyze data are subjective and time-consuming. To address these issues, we have developed a novel flow cytometry analysis pipeline to identify a plethora of cell...

Full description

Autores:

Rojas López, Mauricio
Henao Tamayo, Marcela Isabel
Obregón Henao, Andrés
Karger, Burton
Fox, Amy
Dutt, Taru S.

Tipo de recurso:

Article of investigation

Fecha de publicación:

2020

Institución:

Universidad de Antioquia

Repositorio:

Repositorio UdeA

Idioma:

eng

OAI Identifier:

oai:bibliotecadigital.udea.edu.co:10495/42032

Acceso en línea:

https://hdl.handle.net/10495/42032

Palabra clave:

Biomarcadores
Biomarkers
Células Sanguíneas
Blood Cells
Citodiagnóstico
Cytodiagnosis
Susceptibilidad a Enfermedades
Disease Susceptibility
Citometría de Flujo
Flow Cytometry
Inmunofenotipificación
Immunophenotyping
Mycobacterium tuberculosis
Tuberculosis
Ratones
Ratones
https://id.nlm.nih.gov/mesh/D015415
https://id.nlm.nih.gov/mesh/D001773
https://id.nlm.nih.gov/mesh/D003581
https://id.nlm.nih.gov/mesh/D004198
https://id.nlm.nih.gov/mesh/D005434
https://id.nlm.nih.gov/mesh/D016130
https://id.nlm.nih.gov/mesh/D009169
Fenotipo
Phenotype
https://id.nlm.nih.gov/mesh/D010641
https://id.nlm.nih.gov/mesh/D051379

Rights

openAccess

License

https://creativecommons.org/licenses/by/4.0/