STAR: an integrated solution to management and visualization of sequencing data.
BACKGROUND
Easily visualization of complex data features is a necessary step to conduct studies on next-generation sequencing (NGS) data. We developed STAR, an integrated web application that enables online management, visualization and track-based analysis of NGS data.


RESULTS
STAR is a multilayer web service system. On the client side, STAR leverages JavaScript, HTML5 Canvas and asynchronous communications to deliver a smoothly scrolling desktop-like graphical user interface with a suite of in-browser analysis tools that range from providing simple track configuration controls to sophisticated feature detection within datasets. On the server side, STAR supports private session state retention via an account management system and provides data management modules that enable collection, visualization and analysis of third-party sequencing data from the public domain with over thousands of tracks hosted to date. Overall, STAR represents a next-generation data exploration solution to match the requirements of NGS data, enabling both intuitive visualization and dynamic analysis of data.


METHODS
STAR browser system is freely available on the web at http://wanglab.ucsd.edu/star/browser and https://github.com/angell1117/STAR-genome-browser.
Department of Chemistry and Biochemistry, University of California, San Diego, CA 92093, USA, Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA, The ARC Centre of Excellence in Plant Energy Biology, The University of Western Australia, Crawley, Western Australia 6009, Australia, Key Laboratory for Symbolic Computation and Knowledge Engineering of Ministry of Education, College of Computer Science and Technology, Jilin University, Changchun 130012, China, Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA, Department of Cellular and Molecular Medicine, University of California, San Diego, CA 92093, USA and Ludwig Institute for Cancer Research, La Jolla, CA 92093, USA.
Tao
T
Wang
Jie
J
Liu
Li
L
Shen
Julian
J
Tonti-Filippini
Yun
Y
Zhu
Haiyang
H
Jia
Ryan
R
Lister
John W
JW
Whitaker
Joseph R
JR
Ecker
A Harvey
AH
Millar
Bing
B
Ren
Wei
W
Wang
D003196:Computer Graphics; D030541:Databases, Genetic; D015894:Genome, Human; D023281:Genomics / Q000379:methods*; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods*; D006801:Humans; D020407:Internet; D012984:Software; D014584:User-Computer Interface