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

DNA histogram interpretation based on statistical approaches

G Haroske1, V Dimmer, W Meyer

  • 1Institute of Pathology, University of Technology, Dresden, Germany. haroske@rcs.urz.tu-dresden.de

Analytical Cellular Pathology : the Journal of the European Society for Analytical Cellular Pathology
|January 1, 1997
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

[Document standards for pathology reports in digital medicine].

Der Pathologe·2020
Same author

["Digital Pathology in Diagnostics-reporting on digital images" guideline of the Professional Association of German Pathologists].

Der Pathologe·2018
Same author

[Annual report 2017/18 of the working group on informatics, digital pathology and biobanks].

Der Pathologe·2018
Same author

["Digital Pathology in Diagnostics" guideline : Reporting on digital images].

Der Pathologe·2018
Same author

[Erratum to: Annual report of the working group on informatics, innovative imaging, and biobanking of the German society for pathology].

Der Pathologe·2017
Same author

[Annual report of the working group on informatics, innovative imaging, and biobanking of the German society for pathology].

Der Pathologe·2016

This study introduces objective statistical methods for interpreting DNA cytometry histograms, ensuring reliable ploidy analysis. These techniques improve accuracy in recognizing stemlines and rare events in cell cycle studies.

Area of Science:

  • Biomedical Engineering
  • Quantitative Biology
  • Cell Biology

Background:

  • Image cytometric DNA measurements are often equated with chromosomal ploidy, though they are distinct.
  • The cell cycle is the critical link connecting chromosomal and DNA ploidy.
  • Current interpretation of DNA cytometry data can be subjective and lack objective validation.

Purpose of the Study:

  • To develop and validate objective statistical methods for interpreting DNA histograms derived from image cytometry.
  • To enable population-oriented stochastic analysis of DNA ploidy data.
  • To provide a framework for reliable and automated interpretation of DNA cytometry measurements.

Main Methods:

  • Application of stochastic sampling and stochastic processes for data interpretation.

Related Experiment Videos

  • Development of a statistical method set for objective DNA histogram analysis.
  • Evaluation of measurement precision, accuracy, and error probabilities.
  • Analysis of stemline recognition, stemline aneuploidy, and rare events.

    • Main Results:

    • Demonstrated efficiency of statistical methods on nearly 300 image cytometric DNA measurements from breast cancers and rat liver imprints.
    • Objective interpretation of DNA histograms without human interaction is achievable.
    • Statistical methods provide error probabilities for measurement reliability, stemline recognition, and rare event evaluation.

    Conclusions:

    • The proposed statistical framework allows for objective and reliable interpretation of DNA ploidy from image cytometry.
    • Stochastic sampling and analysis are crucial for accurate DNA ploidy assessment.
    • These methods enhance the precision and accuracy of DNA cytometry, particularly for complex data and rare events.