Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Flow cytometry histograms: transformations, resolution, and display.

David Novo1, James Wood

  • 1De Novo Software, 3250 Wilshire Blvd. Suite 803, Los Angeles, California 90010, USA. david.novo@denovosoftware.com

Cytometry. Part a : the Journal of the International Society for Analytical Cytology
|July 11, 2008
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

A Graph-Theoretic Approach to Minimizing Union Operations for Optimal FMO Construction.

Cytometry. Part A : the journal of the International Society for Analytical Cytology·2026
Same author

Associations between area-level socioeconomic disadvantage and COVID-19 disease consequences in Sydney, Australia: A retrospective cohort analysis.

PloS one·2026
Same author

Temporal analysis of respiratory virus epidemics in Victoria over winter 2024.

Communicable diseases intelligence (2018)·2026
Same author

New-onset diabetes following SARS-CoV-2 infection in the Omicron era: a matched cohort study.

International journal of epidemiology·2026
Same author

Fostering learning among the next generation of veterinarians: incorporating one health and antimicrobial stewardship into veterinary medicine training curricula in Ethiopia.

Frontiers in veterinary science·2026
Same author

Matrix Recovery Algorithm for Reconstructing Mixing Matrices From Raw Observations and Ordinary Least Squares Unmixed Abundance Values.

Cytometry. Part A : the journal of the International Society for Analytical Cytology·2026
Same journal

A Modular High-Parameter Flow Cytometry Framework: Pre-Analytical Optimization and Validation for Clinical Research.

Cytometry. Part A : the journal of the International Society for Analytical Cytology·2026
Same journal

Quantitative Detection of Entotic Cell-In-Cell Structures Using Deformable Segmentation and Deep Learning.

Cytometry. Part A : the journal of the International Society for Analytical Cytology·2026
Same journal

Comparison of Tissue Preparations to Identify and Phenotype T Cells in Human Colorectal Tumor Tissue.

Cytometry. Part A : the journal of the International Society for Analytical Cytology·2026
Same journal

Refractive Index-Correlated Pseudocoloring for Adaptive Color Fusion in Holotomographic Cytology.

Cytometry. Part A : the journal of the International Society for Analytical Cytology·2026
Same journal

Ensembling Unets for Rare Chromosomal Aberration Detection in Metaphase Images, Uncertainty Quantification, and Ionizing Radiation Dose Estimation.

Cytometry. Part A : the journal of the International Society for Analytical Cytology·2026
Same journal

OMIP-121: Immune Phenotyping of Canine Peripheral Leukocytes by Mass Cytometry.

Cytometry. Part A : the journal of the International Society for Analytical Cytology·2026
See all related articles

This review explains how to improve flow cytometry data visualization by addressing limitations in traditional logarithmic histogram scaling. New binning transformations offer better dynamic range and artifact reduction for clearer data presentation.

Area of Science:

  • Biotechnology
  • Data Visualization
  • Quantitative Biology

Background:

  • Flow cytometry data analysis commonly uses histograms with linear or logarithmic scales.
  • Software-based logarithmic conversion reveals limitations in traditional histogram presentations.
  • Artifacts like 'valley' and 'picket fencing' can obscure flow cytometry data.

Purpose of the Study:

  • To review the mathematics of histogram data presentation.
  • To introduce the concept of effective resolution and its impact on histogram artifacts.
  • To discuss newer binning transformations for improved flow cytometry data visualization.

Main Methods:

  • Mathematical analysis of histogram scaling and binning.
  • Introduction of 'effective resolution' to characterize variable bin-width histograms.

Related Experiment Videos

  • Comparison of traditional and novel binning transformations for flow cytometry data.

    • Main Results:

    • Traditional logarithmic scaling can lead to artifacts due to high effective resolution.
    • Newer binning transformations logarithmically bin high channel values and linearly bin low values.
    • These transformations effectively reduce artifacts and display a larger dynamic range, including negative values.

    Conclusions:

    • Understanding effective resolution is key to interpreting histogram artifacts.
    • Newer binning transformations offer significant advantages for visualizing flow cytometry data with large dynamic ranges.
    • Recommendations are provided for appropriate use of these advanced transformations in flow cytometry analysis.