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BigWig and BigBed: enabling browsing of large distributed datasets
W J Kent1, A S Zweig, G Barber
1Center for Biomolecular Science and Engineering, School of Engineering, University of California, Santa Cruz (UCSC), Santa Cruz, CA 95064, USA.
Bioinformatics (Oxford, England)
|July 20, 2010
Summary
BigWig and BigBed files enable efficient visualization of next-generation sequencing data in the UCSC Genome Browser. This approach transmits only necessary data for fast remote access to large datasets.
Area of Science:
- Bioinformatics
- Computational Biology
Background:
- Next-generation sequencing (NGS) experiments generate large datasets.
- Efficient visualization and remote access to this data are crucial for analysis.
Purpose of the Study:
- To describe the BigWig and BigBed file formats for high-performance display of NGS data.
- To detail the software implementation enabling efficient data transmission and visualization.
Main Methods:
- Utilized compressed binary indexed files (BigWig and BigBed) at multiple resolutions.
- Implemented a multi-layered software approach leveraging web protocols, Linux/UNIX systems, R-trees, indexing, and compression.
- Developed utilities for BigWig and BigBed creation and parsing.
Main Results:
- BigWig and BigBed files facilitate high-performance display of NGS experiment results.
- The software approach ensures only required data is transmitted, enabling fast remote access.
- Data is accessible at various resolutions for detailed or overview views.
Conclusions:
- BigWig and BigBed formats provide an efficient solution for managing and visualizing large-scale NGS data.
- The implemented software architecture optimizes data transfer, enhancing usability of the UCSC Genome Browser.
- Freely available source code and binaries support non-commercial use and further development.
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