Track data hubs enable visualization of user-defined genome-wide annotations on the UCSC Genome Browser

B J Raney,A S Zweig,G P Barber,D Karolchik,W J Kent,T R Dreszer,B Paten,N Nguyen,H Clawson,T Wang,P A Fujita

doi:10.1093/bioinformatics/btt637

B J Raney, A S Zweig + Show 9 more

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https://doi.org/10.1093/bioinformatics/btt637

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Journal: Bioinformatics	Publication Date: Nov 13, 2013
Citations: 399	License type: CC BY 3.0

Affiliation: University of California, Santa Cruz

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Summary: Track data hubs provide an efficient mechanism for visualizing remotely hosted Internet-accessible collections of genome annotations. Hub datasets can be organized, configured and fully integrated into the University of California Santa Cruz (UCSC) Genome Browser and accessed through the familiar browser interface. For the first time, individuals can use the complete browser feature set to view custom datasets without the overhead of setting up and maintaining a mirror.Availability and implementation: Source code for the BigWig, BigBed and Genome Browser software is freely available for non-commercial use at http://hgdownload.cse.ucsc.edu/admin/jksrc.zip, implemented in C and supported on Linux. Binaries for the BigWig and BigBed creation and parsing utilities may be downloaded at http://hgdownload.cse.ucsc.edu/admin/exe/. Binary Alignment/Map (BAM) and Variant Call Format (VCF)/tabix utilities are available from http://samtools.sourceforge.net/ and http://vcftools.sourceforge.net/. The UCSC Genome Browser is publicly accessible at http://genome.ucsc.edu.Contact: donnak@soe.ucsc.edu

Highlights

The widespread use of high-throughput sequencing technology has challenged the capabilities of genomic data visualization tools as the volume and size of genome-wide datasets outpace the capacity of existing browsing technology
University of California Santa Cruz (UCSC) added browser support for four compressed binary indexed data formats: BigBed and BigWig (Kent et al, 2010), both developed at UCSC, Binary Alignment/Map (BAM) (Li et al, 2009) and Variant Call Format (VCF)/tabix (Danacek et al, 2011)
The limited configuration and organization options imposed by custom tracks presented a barrier to full integration of large datasets into the browser, leading many research groups to set up mirrors to visualize their tracks in a full local instance of the browser

Summary

INTRODUCTION

The widespread use of high-throughput sequencing technology has challenged the capabilities of genomic data visualization tools as the volume and size of genome-wide datasets outpace the capacity of existing browsing technology. The limited configuration and organization options imposed by custom tracks presented a barrier to full integration of large datasets into the browser, leading many research groups to set up mirrors to visualize their tracks in a full local instance of the browser. Mirrors pose their own drawbacks: they tend to have limited visibility and distribution within the research community and incur a local maintenance overhead. Browser sessions and custom tracks in the same manner as other tracks, and the underlying data can be viewed, manipulated and downloaded using the UCSC Table Browser (Karolchik et al, 2004)

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