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Statistical Applications in Genetics and Molecular Biology

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In This Section
Volume 4, Issue 1 (Mar 2005)


Comparing Automatic and Manual Image Processing in FLARE Assay Analysis for Colon Carcinogenesis

Malgorzata Leyk
  • Texas A&M University
/ Danh V Nguyen
  • University of California, Davis
/ Sanju N Attoor
  • Texas A&M University
/ Edward R Dougherty
  • Texas A&M University
/ Nancy D Turner
  • Texas A&M University
/ Laura K Bancroft
  • Albert Einstein Cancer Center
/ Robert S Chapkin
  • Texas A&M University
/ Joanne R Lupton
  • Texas A&M University
/ Raymond J Carroll
  • Texas A&M University
Published Online: 2005-03-14 | DOI: https://doi.org/10.2202/1544-6115.1102

Measurement of the amount of oxidative damage to DNA is one tool that can be used to estimate the beneficial effect of diet on the prevention of colon carcinogenesis. The FLARE assay is a modification of the single-cell gel electrophoresis (Comet) assay, and provides a measure of the 8OHdG adduct in the cells. In this paper, we present two innovations to the existing methods of analysis. The first one is related to the FLARE assay itself. We describe automated image analysis techniques that can be expected to measure oxidative damage faster, reproducibly, with less noise, and hence achieve greater statistical power. The proposed technique is compared to an existing technique, which was more manual and thus slower. The second innovation is our statistical analysis: we exploit the shape of FLARE intensity histograms, and show statistically significant diet effects in the duodenum. Previous analyses of this data concentrated on simple summary statistics, and found only marginally statistically significant diet effects. With the new imaging method and measure of oxidative damage, we show cells in the duodenum exposed to fish oil as having more oxidative damage than cells exposed to corn oil.

Keywords: colon carcinogenesis; comet assay; corn oil; fish oil; FLARE assay; hierarchical models; image analysis; single-cell gel electrophoresis.

About the article

Published Online: 2005-03-14

Citation Information: Statistical Applications in Genetics and Molecular Biology, ISSN (Online) 1544-6115, ISSN (Print) 2194-6302, DOI: https://doi.org/10.2202/1544-6115.1102. Export Citation

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