Abstract
ChIP-sequencing experiments are routinely used to study genome-wide chromatin marks. Due to the high-cost and complexity associated with this technology, it is of great interest to investigate whether the low-cost option of microarray experiments can be used in combination with ChIP-seq experiments. Most integrative analyses do not consider important features of ChIP-seq data, such as spatial dependencies and ChIP-efficiencies. In this paper, we address these issues by applying a Markov random field model to ChIP-seq data on the protein Brd4, for which both ChIP-seq and microarray data are available on the same biological conditions. We investigate the correlation between the enrichment probabilities around transcription start sites, estimated by the Markov model, and microarray gene expression values. Our preliminary results suggest that binding of the protein is associated with lower gene expression, but differential binding across different conditions does not show an association with differential expression of the associated genes.
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Ferdous, M.M., Vinciotti, V., Liu, X., Wilson, P. (2015). Exploring the Link Between Gene Expression and Protein Binding by Integrating mRNA Microarray and ChIP-Seq Data. In: Gammerman, A., Vovk, V., Papadopoulos, H. (eds) Statistical Learning and Data Sciences. SLDS 2015. Lecture Notes in Computer Science(), vol 9047. Springer, Cham. https://doi.org/10.1007/978-3-319-17091-6_16
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DOI: https://doi.org/10.1007/978-3-319-17091-6_16
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