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Identifying Transcriptional Regulatory Modules Among Different Chromatin States in Mouse Neural Stem Cells
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Gene expression regulation is a complex process involving the interplay between transcription factors and chromatin states. Significant progress has been made toward understanding the impact of chromatin states on gene expression. Nevertheless, the mechanism of transcription factors binding combinatorially in different chromatin states to enable selective regulation of gene expression remains an interesting research area. We introduce a nonparametric Bayesian clustering method for inhomogeneous Poisson processes to detect heterogeneous binding patterns of multiple proteins including transcription factors to form regulatory modules in different chromatin states. We applied this approach on ChIP-seq data for mouse neural stem cells containing 21 proteins and observed different groups or modules of proteins clustered within different chromatin states. These chromatin-state-specific regulatory modules were found to have significant influence on gene expression. We also observed different motif preferences for certain TFs between different chromatin states. Our results reveal a degree of interdependency between chromatin states and combinatorial binding of proteins in the complex transcriptional regulatory process. The software package is available on Github at - https://github.com/BSharmi/DPM-LGCP.
- Scholarly Works, Bradley Department of Electrical and Computer Engineering 
- Scholarly Works, Department of Biological Sciences 
- Scholarly Works, Department of Biomedical Sciences and Pathobiology 
- Scholarly Works, Department of Computer Science 
- Scholarly Works, Department of Statistics 
- Scholarly Works, Fralin Life Sciences Institute 
- Scholarly Works, School of Neuroscience