flowDensity: reproducing manual gating of flow cytometry data by automated density-based cell population identification.

Bioinformatics

Terry 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.

Published: February 2015

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.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4325545PMC
http://dx.doi.org/10.1093/bioinformatics/btu677DOI Listing

Publication Analysis

Top Keywords

manual gating
8
flow cytometry
8
cytometry data
8
gating approach
8
flowdensity reproducing
4
reproducing manual
4
gating flow
4
data
4
data automated
4
automated density-based
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!