Related Experiment Video
Updated: Apr 21, 2026
Simultaneous Assessment of Kinship, Division Number, and Phenotype via Flow Cytometry for Hematopoietic Stem and Progenitor Cells
Published on: March 24, 2023
flowDensity: reproducing manual gating of flow cytometry data by automated density-based cell population
Mehrnoush Malek1, Mohammad Jafar Taghiyar1, Lauren Chong1
1Terry Fox Laboratory, BC Cancer Agency Research Centre, Vancouver, BC V5Z 1L3, Canada, Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109-1024, USA and Bioinformatics Training Program, University of British Columbia, Vancouver, BC V5Z 4S6, Canada.
Summary:
flowDensity facilitates reproducible, high-throughput analysis of flow cytometry data by automating a predefined manual gating approach. The algorithm is based on a sequential bivariate gating approach that generates a set of predefined cell populations. It chooses the best cut-off for individual markers using characteristics of the density distribution. The Supplementary Material is linked to the online version of the manuscript.
Availability And Implementation:
R source code freely available through BioConductor (http://master.bioconductor.org/packages/devel/bioc/html/flowDensity.html.). Data available from FlowRepository.org (dataset FR-FCM-ZZBW).
Contact:
rbrinkman@bccrc.ca
Supplementary Information:
Supplementary data are available at Bioinformatics online.
More Related Videos
05:19Author Spotlight: Advancing Research in Microbial Autoaggregation Using Imaging Flow Cytometry
Published on: September 29, 2023
14:01Far-Red Fluorescent Senescence-Associated β-Galactosidase Probe for Identification and Enrichment of Senescent Tumor Cells by Flow Cytometry
Published on: September 13, 2022
