SUMMARY: As the use of single-cell technologies has grown, so has the need for tools to explore these large, complicated datasets. The UCSC Cell Browser is a tool that allows scientists to visualize gene expression and metadata annotation distribution throughout a single-cell dataset or multiple datasets. AVAILABILITY AND IMPLEMENTATION: We provide the UCSC Cell Browser as a free website where scientists can explore a growing collection of single-cell datasets and a freely available python package for scientists to create stable, self-contained visualizations for their own single-cell datasets. Learn more at https://cells.ucsc.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

UNLABELLED: Two new tools on the UCSC Genome Browser web site provide improved ways of combining information from multiple datasets, optionally including the user's own custom track data and/or data from track hubs. The Data Integrator combines columns from multiple data tracks, showing all items from the first track along with overlapping items from the other tracks. The Variant Annotation Integrator is tailored to adding functional annotations to variant calls; it offers a more restricted set of underlying data tracks but adds predictions of each variant's consequences for any overlapping or nearby gene transcript. When available, it optionally adds additional annotations including effect prediction scores from dbNSFP for missense mutations, ENCODE regulatory summary tracks and conservation scores. AVAILABILITY AND IMPLEMENTATION: The web tools are freely available at http://genome.ucsc.edu/ and the underlying database is available for download at http://hgdownload.cse.ucsc.edu/ The software (written in C and Javascript) is available from https://genome-store.ucsc.edu/ and is freely available for academic and non-profit usage; commercial users must obtain a license. CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

UNLABELLED: Genome Browser in a Box (GBiB) is a small virtual machine version of the popular University of California Santa Cruz (UCSC) Genome Browser that can be run on a researcher's own computer. Once GBiB is installed, a standard web browser is used to access the virtual server and add personal data files from the local hard disk. Annotation data are loaded on demand through the Internet from UCSC or can be downloaded to the local computer for faster access. AVAILABILITY AND IMPLEMENTATION: Software downloads and installation instructions are freely available for non-commercial use at https://genome-store.ucsc.edu/. GBiB requires the installation of open-source software VirtualBox, available for all major operating systems, and the UCSC Genome Browser, which is open source and free for non-commercial use. Commercial use of GBiB and the Genome Browser requires a license (http://genome.ucsc.edu/license/).

The world's genomics data will never be stored in a single repository - rather, it will be distributed among many sites in many countries. No one site will have enough data to explain genotype to phenotype relationships in rare diseases; therefore, sites must share data. To accomplish this, the genetics community must forge common standards and protocols to make sharing and computing data among many sites a seamless activity. Through the Global Alliance for Genomics and Health, we are pioneering the development of shared application programming interfaces (APIs) to connect the world's genome repositories. In parallel, we are developing an open source software stack (ADAM) that uses these APIs. This combination will create a cohesive genome informatics ecosystem. Using containers, we are facilitating the deployment of this software in a diverse array of environments. Through benchmarking efforts and big data driver projects, we are ensuring ADAM's performance and utility.

MOTIVATION: Researchers now have access to large volumes of genome sequences for comparative analysis, some generated by the plethora of public sequencing projects and, increasingly, from individual efforts. It is not possible, or necessarily desirable, that the public genome browsers attempt to curate all these data. Instead, a wealth of powerful tools is emerging to empower users to create their own visualizations and browsers. RESULTS: We introduce a pipeline to easily generate collections of Web-accessible UCSC Genome Browsers interrelated by an alignment. It is intended to democratize our comparative genomic browser resources, serving the broad and growing community of evolutionary genomicists and facilitating easy public sharing via the Internet. Using the alignment, all annotations and the alignment itself can be efficiently viewed with reference to any genome in the collection, symmetrically. A new, intelligently scaled alignment display makes it simple to view all changes between the genomes at all levels of resolution, from substitutions to complex structural rearrangements, including duplications. To demonstrate this work, we create a comparative assembly hub containing 57 Escherichia coli and 9 Shigella genomes and show examples that highlight their unique biology. AVAILABILITY AND IMPLEMENTATION: The source code is available as open source at: https://github.com/glennhickey/progressiveCactus The E.coli and Shigella genome hub is now a public hub listed on the UCSC browser public hubs Web page.

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.

The UCSC Genome Browser (http://genome.ucsc.edu) is a graphical viewer for genomic data now in its 13th year. Since the early days of the Human Genome Project, it has presented an integrated view of genomic data of many kinds. Now home to assemblies for 58 organisms, the Browser presents visualization of annotations mapped to genomic coordinates. The ability to juxtapose annotations of many types facilitates inquiry-driven data mining. Gene predictions, mRNA alignments, epigenomic data from the ENCODE project, conservation scores from vertebrate whole-genome alignments and variation data may be viewed at any scale from a single base to an entire chromosome. The Browser also includes many other widely used tools, including BLAT, which is useful for alignments from high-throughput sequencing experiments. Private data uploaded as Custom Tracks and Data Hubs in many formats may be displayed alongside the rich compendium of precomputed data in the UCSC database. The Table Browser is a full-featured graphical interface, which allows querying, filtering and intersection of data tables. The Saved Session feature allows users to store and share customized views, enhancing the utility of the system for organizing multiple trains of thought. Binary Alignment/Map (BAM), Variant Call Format and the Personal Genome Single Nucleotide Polymorphisms (SNPs) data formats are useful for visualizing a large sequencing experiment (whole-genome or whole-exome), where the differences between the data set and the reference assembly may be displayed graphically. Support for high-throughput sequencing extends to compact, indexed data formats, such as BAM, bigBed and bigWig, allowing rapid visualization of large datasets from RNA-seq and ChIP-seq experiments via local hosting.

Abstract Summary: BigWig and BigBed files are compressed binary indexed files containing data at several resolutions that allow the high-performance display of next-generation sequencing experiment results in the UCSC Genome Browser. The visualization is implemented using a multi-layered software approach that takes advantage of specific capabilities of web-based protocols and Linux and UNIX operating systems files, R trees and various indexing and compression tricks. As a result, only the data needed to support the current browser view is transmitted rather than the entire file, enabling fast remote access to large distributed data sets. Availability and implementation: Binaries for the BigWig and BigBed creation and parsing utilities may be downloaded at http://hgdownload.cse.ucsc.edu/admin/exe/linux.x86_64/. Source code for the creation and visualization software is freely available for non-commercial use at http://hgdownload.cse.ucsc.edu/admin/jksrc.zip, implemented in C and supported on Linux. The UCSC Genome Browser is available at http://genome.ucsc.edu Contact: [email protected] Supplementary information: Supplementary byte-level details of the BigWig and BigBed file formats are available at Bioinformatics online. For an in-depth description of UCSC data file formats and custom tracks, see http://genome.ucsc.edu/FAQ/FAQformat.html and http://genome.ucsc.edu/goldenPath/help/hgTracksHelp.html

The University of California Santa Cruz (UCSC) Known Genes dataset is constructed by a fully automated process, based on protein data from Swiss-Prot/TrEMBL (UniProt) and the associated mRNA data from Genbank. The detailed steps of this process are described. Extensive cross-references from this dataset to other genomic and proteomic data were constructed. For each known gene, a details page is provided containing rich information about the gene, together with extensive links to other relevant genomic, proteomic and pathway data. As of July 2005, the UCSC Known Genes are available for human, mouse and rat genomes. The Known Genes serves as a foundation to support several key programs: the Genome Browser, Proteome Browser, Gene Sorter and Table Browser offered at the UCSC website. All the associated data files and program source code are also available. They can be accessed at http://genome.ucsc.edu. The genomic coverage of UCSC Known Genes, RefSeq, Ensembl Genes, H-Invitational and CCDS is analyzed. Although UCSC Known Genes offers the highest genomic and CDS coverage among major human and mouse gene sets, more detailed analysis suggests all of them could be further improved.