Data integration in multi-dimensional data sets: Informational asymmetry in the valid correlation of subdivided samples

Qing T. Zeng, Juan Pablo Pratt, Jane Pak, Eun Young Kim, Dino Ravnic, Harold Huss, Steven J. Mentzer

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Background: Flow cytometry is the only currently available high throughput technology that can measure multiple physical and molecular characteristics of individual cells. It is common in flow cytometry to measure a relatively large number of characteristics or features by performing separate experiments on subdivided samples. Correlating data from multiple experiments using certain shared features (e.g. cell size) could provide useful information on the combination pattern of the not shared features. Such correlation, however, are not always reliable. Methods: We developed a method to assess the correlation reliability by estimating the percentage of cells that can be unambiguously correlated between two samples. This method was evaluated using 81 pairs of subdivided samples of microspheres (artificial cells) with known molecular characteristics. Results: Strong correlation (R=0.85) was found between the estimated and actual percentage of unambiguous correlation. Conclusion: The correlation reliability we developed can be used to support data integration of experiments on subdivided samples.

Original languageEnglish (US)
Title of host publicationBiological and Medical Data Analysis - 7th International Symposium, ISBMDA 2006, Proceedings
PublisherSpringer Verlag
Pages423-432
Number of pages10
ISBN (Print)3540680632, 9783540680635
DOIs
StatePublished - 2006
Event7th International Symposium on Biological and Medical Data Analysis, ISBMDA 2006 - Thessaloniki, Greece
Duration: Dec 7 2006Dec 8 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4345 LNBI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other7th International Symposium on Biological and Medical Data Analysis, ISBMDA 2006
CountryGreece
CityThessaloniki
Period12/7/0612/8/06

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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    Zeng, Q. T., Pratt, J. P., Pak, J., Kim, E. Y., Ravnic, D., Huss, H., & Mentzer, S. J. (2006). Data integration in multi-dimensional data sets: Informational asymmetry in the valid correlation of subdivided samples. In Biological and Medical Data Analysis - 7th International Symposium, ISBMDA 2006, Proceedings (pp. 423-432). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4345 LNBI). Springer Verlag. https://doi.org/10.1007/11946465_38