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We present JBrowse 2, a general-purpose genome annotation browser offering enhanced visualization of complex structural variation and evolutionary relationships. It retains core features of JBrowse while adding new views for synteny, dotplots, breakpoints, gene fusions, and whole-genome overviews. It allows users to share sessions, open multiple genomes, and navigate between views. It can be embedded in a web page, used as a standalone application, or run from Jupyter notebooks or R sessions. These improvements are enabled by a ground-up redesign using modern web technology. We describe application functionality, use cases, performance benchmarks, and implementation notes for web administrators and developers.

Background JBrowse is a fast and full-featured genome browser built with JavaScript and HTML5. It is easily embedded into websites or apps but can also be served as a standalone web page. Results Overall improvements to speed and scalability are accompanied by specific enhancements that support complex interactive queries on large track sets. Analysis functions can readily be added using the plugin framework; most visual aspects of tracks can also be customized, along with clicks, mouseovers, menus, and popup boxes. JBrowse can also be used to browse local annotation files offline and to generate high-resolution figures for publication. Conclusions JBrowse is a mature web application suitable for genome visualization and analysis.

Here, we introduce the 3D Genome Browser, http://3dgenome.org , which allows users to conveniently explore both their own and over 300 publicly available chromatin interaction data of different types. We design a new binary data format for Hi-C data that reduces the file size by at least a magnitude and allows users to visualize chromatin interactions over millions of base pairs within seconds. Our browser provides multiple methods linking distal cis -regulatory elements with their potential target genes. Users can seamlessly integrate thousands of other omics data to gain a comprehensive view of both regulatory landscape and 3D genome structure.

The Middle East respiratory syndrome coronavirus (MERS-CoV) was exported to Korea in 2015, resulting in a threat to neighboring nations. We evaluated the possibility of using a digital surveillance system based on web searches and social media data to monitor this MERS outbreak. We collected the number of daily laboratory-confirmed MERS cases and quarantined cases from May 11, 2015 to June 26, 2015 using the Korean government MERS portal. The daily trends observed via Google search and Twitter during the same time period were also ascertained using Google Trends and Topsy. Correlations among the data were then examined using Spearman correlation analysis. We found high correlations (>0.7) between Google search and Twitter results and the number of confirmed MERS cases for the previous three days using only four simple keywords: “MERS”, “ ” (“MERS (in Korean)”), “ ” (“MERS symptoms (in Korean)”), and “ ” (“MERS hospital (in Korean)”). Additionally, we found high correlations between the Google search and Twitter results and the number of quarantined cases using the above keywords. This study demonstrates the possibility of using a digital surveillance system to monitor the outbreak of MERS.

Background Cluster and transmission analysis utilising pairwise SNP distance are increasingly used in genomic epidemiological studies. However, current methods are often challenging to install and use, and lack interactive functionalities for easy data exploration. Results GraphSNP is an interactive visualisation tool running in a web browser that allows users to rapidly generate pairwise SNP distance networks, investigate SNP distance distributions, identify clusters of related organisms, and reconstruct transmission routes. The functionality of GraphSNP is demonstrated using examples from recent multi-drug resistant bacterial outbreaks in healthcare settings. Conclusions GraphSNP is freely available at https://github.com/nalarbp/graphsnp . An online version of GraphSNP, including demonstration datasets, input templates, and quick start guide is available for use at https://graphsnp.fordelab.com .

We here outline the importance of open-source, accessible tools for computer-aided drug discovery (CADD). We begin with a discussion of drug discovery in general to provide context for a subsequent discussion of structure-based CADD applied to small-molecule ligand discovery. Next, we identify usability challenges common to many open-source CADD tools. To address these challenges, we propose a browser-based approach to CADD tool deployment in which CADD calculations run in modern web browsers on users’ local computers. The browser app approach eliminates the need for user-initiated download and installation, ensures broad operating system compatibility, enables easy updates, and provides a user-friendly graphical user interface. Unlike server apps—which run calculations “in the cloud” rather than on users’ local computers—browser apps do not require users to upload proprietary information to a third-party (remote) server. They also eliminate the need for the difficult-to-maintain computer infrastructure required to run user-initiated calculations remotely. We conclude by describing some CADD browser apps developed in our lab, which illustrate the utility of this approach. Aside from introducing readers to these specific tools, we are hopeful that this review highlights the need for additional browser-compatible, user-friendly CADD software.

While many languages are used for data manipulation, it is unusual to see JavaScript put to this task. This paper describes a novel application built to manipulate catalog patron data using only JavaScript running in a browser. Further, it describes the approach of building and deploying “strongly single page web applications,” a more extreme version of single page applications that have been condensed into a single HTML file. The paper discusses the application itself, how it is used, and the way that possessing web development and coding skills in an organization’s systems department can help it flexibly respond to challenges using such novel solutions.

Online language and literacy assessments have become prevalent in research and practice across settings. However, a notable exception is the assessment of handwriting and spelling, which has traditionally been conducted in person with paper and pencil. In light of this, we developed an automated, browser-based handwriting test application ( Online Assessment of Handwriting and Spelling: OAHaS ) for Japanese Kanji (Study 1 ) and examined its psychometric properties (Study 2 ). The automated scoring function using convolutional neural network (CNN) models achieved high recall (98.7%) and specificity (84.4%), as well as high agreement with manual scoring (95.4%). Additionally, behavioral validation with data from primary school children ( N = 261, 49.0% female, age range = 6–12 years) indicated the high reliability and validity of our online test application, with a strong correlation between children’s scores on the online and paper-based tests ( r = .86). Moreover, our analysis indicated the potential utility of writing fluency measures (latency and duration) that are automatically recorded by OAHaS. Taken together, our browser-based application demonstrated the feasibility and viability of remote and automated assessment of handwriting skills, providing a streamlined approach to research and practice on handwriting. The source code of the application and supporting materials are available on Open Science Framework ( https://osf.io/gver2/ ).

Graph-based pangenome is gaining more popularity than linear pangenome because it stores more comprehensive information of variations. However, traditional linear genome browser has its own advantages, especially the tremendous resources accumulated historically. With the fast-growing number of individual genomes and their annotations available, the demand for a genome browser to visualize genome annotation for many individuals together with a graph-based pangenome is getting higher and higher. Here we report a new pangenome browser PPanG, a precise pangenome browser enabling nucleotide-level comparison of individual genome annotations together with a graph-based pangenome. Nine rice genomes with annotations were provided by default as potential references, and any individual genome can be selected as the reference. Our pangenome browser provides unprecedented insights on genome variations at different levels from base to gene, and reveals how the structures of a gene could differ for individuals. PPanG can be applied to any species with multiple individual genomes available and it is available at https://cgm.sjtu.edu.cn/PPanG .

Conducting research via the Internet is a formidable and ever-increasingly popular option for behavioral scientists. However, it is widely acknowledged that web-browsers are not optimized for research: In particular, the timing of display changes (e.g., a stimulus appearing on the screen), still leaves room for improvement. So far, the typically recommended best (or least bad) timing method has been a single requestAnimationFrame  (RAF) JavaScript function call within which one would give the display command and obtain the time of that display change. In our Study 1, we assessed two alternatives: Calling the RAF twice consecutively, or calling the RAF during a continually ongoing independent loop of recursive RAF calls. While the former has shown little or no improvement as compared to single RAF calls, with the latter we significantly and substantially improved overall precision, and achieved practically faultless precision in most practical cases. Our two basic methods for effecting display changes, plain text change and canvas  color filling, proved equally efficient. In Study 2, we reassessed the “RAF loop” timing method with image elements in combination with three different display methods: We found that the precision remained high when using either visibility  or opacity  changes – while drawing on a canvas  element consistently led to comparatively lower precision. We recommend the “RAF loop” display timing method for improved precision in future studies, and visibility  or opacity  changes when using image stimuli. We publicly share the easy-to-use code for this method, exactly as employed in our studies.