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The UCSC genome browser and associated tools

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TLDR
The UCSC Genome Browser is a graphical viewer for genomic data that presents visualization of annotations mapped to genomic coordinates, and the ability to juxtapose annotations of many types facilitates inquiry-driven data mining.
Abstract
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.

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Integrative Genomics Viewer

TL;DR: The sheer volume and scope of data posed by this flood of data pose a significant challenge to the development of efficient and intuitive visualization tools able to scale to very large data sets and to flexibly integrate multiple data types, including clinical data.
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Comprehensive Molecular Characterization of Muscle-Invasive Bladder Cancer

A. Gordon Robertson, +170 more
- 19 Oct 2017 - 
TL;DR: An analysis of 412 muscle-invasive bladder cancers characterized by multiple TCGA analytical platforms identified 5 expression subtypes that may stratify response to different treatments and identified a poor-survival "neuronal" subtype in which the majority of tumors lacked small cell or neuroendocrine histology.
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Comprehensive and Integrative Genomic Characterization of Hepatocellular Carcinoma

Adrian Ally, +235 more
- 15 Jun 2017 - 
TL;DR: Integrative molecular HCC subtyping incorporating unsupervised clustering of five data platforms identified three subtypes, one of which was associated with poorer prognosis in three HCC cohorts and development of a p53 target gene expression signature correlating with poor survival was enabled.
Journal ArticleDOI

The UCSC Genome Browser database: 2016 update.

TL;DR: The UCSC Genome Browser has greatly expanded the data sets available on the most recent human assembly, hg38/GRCh38, to include updated gene prediction sets from GENCODE, more phenotype- and disease-associated variants from ClinVar and ClinGen, more genomic regulatory data, and a new multiple genome alignment.
References
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Journal ArticleDOI

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Integrative genomics viewer

TL;DR: In this article, the authors present an approach for efficient and intuitive visualization tools able to scale to very large data sets and to flexibly integrate multiple data types, including clinical data.
Journal ArticleDOI

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Journal ArticleDOI

The Human Genome Browser at UCSC

TL;DR: A mature web tool for rapid and reliable display of any requested portion of the genome at any scale, together with several dozen aligned annotation tracks, is provided at http://genome.ucsc.edu.
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