Generalizing Moving Averages for Tiling Arrays Using Combined P-Value Statistics

Kechris Katerina J, Biehs Brian and Kornberg Thomas B
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Kechris Katerina J: University of Colorado Denver
Biehs Brian: University of California, San Francisco
Kornberg Thomas B: University of California, San Francisco

Statistical Applications in Genetics and Molecular Biology, 2010, vol. 9, issue 1, 31

Abstract: High density tiling arrays are an effective strategy for genome-wide identification of transcription factor binding regions. Sliding window methods that calculate moving averages of log ratios or t-statistics have been useful for the analysis of tiling array data. Here, we present a method that generalizes the moving average approach to evaluate sliding windows of p-values by using combined p-value statistics. In particular, the combined p-value framework can be useful in situations when taking averages of the corresponding test-statistic for the hypothesis may not be appropriate or when it is difficult to assess the significance of these averages. We exhibit the strengths of the combined p-values methods on Drosophila tiling array data and assess their ability to predict genomic regions enriched for transcription factor binding. The predictions are evaluated based on their proximity to target genes and their enrichment of known transcription factor binding sites. We also present an application for the generalization of the moving average based on integrating two different tiling array experiments.

Keywords: transcription factor; binding sequence; tiling array; combined p-value (search for similar items in EconPapers)
Date: 2010
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DOI: 10.2202/1544-6115.1434

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