flowQ

flowQ performs automated quality control and assessment of flow cytometry (FCM) data to improve standardization and reproducibility of clinical and research analyses.


Key Features:

  • Automated quality control and assessment: Performs automated quality control and assessment of flow cytometry (FCM) data to streamline QC processes.
  • Systematic pipeline reporting: Reports each component of the data analysis pipeline to ensure transparency and standardization across analyses.
  • Standardization: Enforces standardized processing to enable consistent re-evaluation of FCM datasets.
  • Reproducibility enhancement: Reduces human error and enhances reproducibility of FCM data analysis compared with manual workflows.
  • Automation of manual workflows: Replaces time-consuming, manual FCM data analysis steps with automated procedures.

Scientific Applications:

  • Leukemia and lymphoma diagnosis and monitoring: Supports quality-controlled analysis of FCM data used in diagnosing and monitoring leukemia and lymphoma.
  • Hematopoietic stem cell graft evaluation: Supports evaluation of peripheral blood hematopoietic stem cell grafts using standardized FCM analysis.
  • HIV treatment management: Supports assessment of helper-T lymphocyte counts relevant to HIV treatment management.
  • Clinical and research flow cytometry studies: Enables reproducible and standardized FCM data analysis across clinical and research settings.

Methodology:

Performs automated quality control and assessment and systematically reports each component of the flow cytometry data analysis pipeline.

Topics

Collections

Details

License:
Artistic-2.0
Tool Type:
command-line tool, library
Operating Systems:
Linux, Windows, Mac
Programming Languages:
R
Added:
1/17/2017
Last Updated:
11/25/2024

Operations

Data Inputs & Outputs

Publications

Bashashati A, Brinkman RR. A Survey of Flow Cytometry Data Analysis Methods. Advances in Bioinformatics. 2009;2009:1-19. doi:10.1155/2009/584603. PMID:20049163. PMCID:PMC2798157.

PMID: 20049163
PMCID: PMC2798157
Funding: - Natural Sciences and Engineering Research Council of Canada: R01 EB008400 - National Institutes of Health: R01 EB008400 - Michael Smith Foundation for Health Research: R01 EB008400

Documentation

Downloads