Cooler: scalable storage for Hi-C data and other genomically labeled arrays
Massachusetts Institute of Technology
Abstract
Abstract Motivation Most existing coverage-based (epi)genomic datasets are one-dimensional, but newer technologies probing interactions (physical, genetic, etc.) produce quantitative maps with two-dimensional genomic coordinate systems. Storage and computational costs mount sharply with data resolution when such maps are stored in dense form. Hence, there is a pressing need to develop data storage strategies that handle the full range of useful resolutions in multidimensional genomic datasets by taking advantage of their sparse nature, while supporting efficient compression and providing fast random access to facilitate development of scalable algorithms for data analysis. Results We developed a file format…
Citation impact
- FWCI
- 40.48
- Percentile
- 100%
- References
- 26
Authors
2Topics & keywords
- Scalability
- Computer science
- Computer data storage
- Operating system
- Database