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Related Experiment Videos

Receiver operating characteristic analysis: a general tool for DNA array data filtration and performance estimation.

Nikolai N Khodarev1, James Park, Yasushi Kataoka

  • 1Department of Radiation and Cellular Oncology, The University of Chicago, IL 60637, USA.

Genomics
|March 7, 2003
PubMed
Summary
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Data filtration in DNA array analysis is crucial. Receiver operating characteristic (ROC) analysis provides an optimal method for setting intensity thresholds, improving gene selection accuracy.

Area of Science:

  • Genomics
  • Bioinformatics
  • Molecular Biology

Background:

  • DNA array analysis generates thousands of signals requiring data filtration.
  • Standardized rules for effective data filtration are currently lacking.

Purpose of the Study:

  • To present a rational approach for DNA array data filtration using receiver operating characteristic (ROC) analysis.
  • To establish optimal intensity thresholding for accurate gene signal selection.

Main Methods:

  • Utilized receiver operating characteristic (ROC) analysis to estimate optimal cutoff levels for intensity thresholding.
  • Applied the ROC-based method to various DNA array platforms including Atlas cDNA, GeneFilters, and Affymetrix GeneChip.
  • Compared the distribution of true and false positive signals across different array systems.

Related Experiment Videos

Main Results:

  • ROC analysis revealed similar distributions of false and true positive data across tested DNA array systems.
  • An optimal intensity cutoff level was estimated to maximize the true to false signal ratio.
  • Derived filtration thresholds for GeneChip arrays consistent with replicate hybridization data.

Conclusions:

  • Intensity-based filtration optimized with ROC analysis enhances DNA array data quality.
  • Combining ROC-optimized filtration with other methods improves gene selection accuracy.
  • ROC methodology is effective for comparing performance across different array technologies and analysis tools.