Abstract
Comprehensive, accurate and detailed maps of transcription factor binding sites (TFBS) help to unravel the transcriptional regulatory relationship between genes and transcription factors. The recently developed sequencing-based genome-wide approach ChIP-PET (Chromatin ImmunoPrecipitation coupled with Paired-End diTag analysis) permits accurate and unbiased mapping of TF-DNA interactions. In this paper we outline a methodical framework to analyze ChIP-PET sequence data to identify most likely binding regions. Mathematical formulations were derived to streamline and strengthen the analysis. We established a more faithful noise distribution estimation that leads to the adaptive threshold scheme. The algorithms were evaluated using three real-world datasets. Using motif enrichment as indirect evidence and additional ChIP-qPCR validations, the overall performance was consistently satisfactory.
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Vega, V.B., Ruan, Y., Sung, WK. (2008). A Streamlined and Generalized Analysis of Chromatin ImmunoPrecipitation Paired-End diTag Data. In: Bubak, M., van Albada, G.D., Dongarra, J., Sloot, P.M.A. (eds) Computational Science – ICCS 2008. ICCS 2008. Lecture Notes in Computer Science, vol 5103. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69389-5_16
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DOI: https://doi.org/10.1007/978-3-540-69389-5_16
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