Abstract
Epigenetic landscapes represent how cells regulate gene activity. To understand their effect on gene regulation, it is important to detect their occupancy in the genome. Unlike transcription factors whose binding regions are limited to narrow regions, histone modification marks are enriched over broader areas. The stochastic characteristics unique to each mark make it hard to detect their enrichment. Classically, a predefined window has been used to detect their enrichment. However, these approaches heavily rely on the predetermined parameters. Also, the window-based approaches cannot handle the enrichment of multiple marks. We propose a novel algorithm, called SeqW, to detect enrichment of multiple histone modification marks. SeqW applies a zooming approach to detect a broadly enriched domain. The zooming approach helps domain detection by increasing signal-to-noise ratio. The borders of the domains are detected by studying the characteristics of signals in the wavelet domain. We show that SeqW outperformed previous predictors in detecting broad peaks. Also, we applied SeqW in studying spatial combinations of histone modification patterns.
| Original language | English |
|---|---|
| Journal | Journal of computational biology : a journal of computational molecular cell biology |
| Volume | 21 |
| Issue number | 11 |
| Pages (from-to) | 846-54 |
| Number of pages | 9 |
| ISSN | 1066-5277 |
| DOIs | |
| Publication status | Published - 1 Nov 2014 |
| Externally published | Yes |
Keywords
- Adipocytes/metabolism
- Algorithms
- Animals
- Binding Sites
- Computational Biology/methods
- Epigenomics
- Gene Expression Regulation
- Histones/metabolism
- Mice
- Protein Binding