UniversalEPI Hi-C Predictions Composite Track
This composite track displays Hi-C interaction predictions generated by UniversalEPI, using normalized ATAC-seq data from ENCODE cell lines and primary cells as input. Two tracks are provided for each input ATAC-seq dataset: a log-transformed ICE-normalized Hi-C track and a z-score Hi-C track.
Data Description
UniversalEPI leverages chromatin accessibility data (ATAC-seq) to predict Hi-C interactions, capturing 3D genome organization across various cell types. The predictions are processed into two formats:
- Raw Hi-C: Interaction frequencies normalized using the Iterative Correction and Eigenvector decomposition (ICE) method, followed by log-transformation to enhance visualization of interaction strengths.
- Z-score Hi-C: Interaction frequencies converted to z-scores, highlighting significant interactions relative to the background distribution.
Each track corresponds to a specific cell line or primary cell type, allowing for comparative analysis of predicted 3D genome structures.
Track Details
- Data Type: Predicted Hi-C interaction matrices
- Normalization: ICE normalization (log-transformed) and z-score transformation
- Input Data: Normalized ATAC-seq from ENCODE cell lines and primary cells
- Visualization: Interaction matrices displayed as heatmaps or arcs in the UCSC Genome Browser
- Track Format: bigInteract
Usage
Users can explore these predicted Hi-C interaction tracks to investigate the 3D organization of the genome in different cell types. The log-transformed ICE-normalized tracks provide a clear view of overall interaction patterns, while the z-score tracks emphasize long-range interactions that may be biologically significant. These predictions can be used to generate hypotheses about gene regulation, chromatin architecture, and cellular function.
Contact
For questions or feedback about this track hub, please contact Prof. Dr. Valentina Boeva.
References
- Grover, A., et al. (2024). UniversalEPI: a generalized attention-based deep ensemble model to accurately predict enhancer-promoter interactions across diverse cell types and conditions. bioRxiv. https://doi.org/10.1101/2024.11.22.624813
- ENCODE Project Consortium. (2012). An integrated encyclopedia of DNA elements in the human genome. Nature, 489(7414), 57-74. https://doi.org/10.1038/nature11247
- Imakaev, M., et al. (2012). Iterative correction of Hi-C data reveals hallmarks of chromosome organization. Nature Methods, 9(10), 999-1003. https://doi.org/10.1038/nmeth.2148