ABrowse - a customizable next-generation genome browser framework

<p>Abstract</p> <p>Background</p> <p>With the rapid growth of genome sequencing projects, genome browser is becoming indispensable, not only as a visualization system but also as an interactive platform to support open data access and collaborative work. Thus a customizable genome browser framework with rich functions and flexible configuration is needed to facilitate various genome research projects.</p> <p>Results</p> <p>Based on next-generation web technologies, we have developed a general-purpose genome browser framework ABrowse which provides interactive browsing experience, open data access and collaborative work support. By supporting Google-map-like smooth navigation, ABrowse offers end users highly interactive browsing experience. To facilitate further data analysis, multiple data access approaches are supported for external platforms to retrieve data from ABrowse. To promote collaborative work, an online user-space is provided for end users to create, store and share comments, annotations and landmarks. For data providers, ABrowse is highly customizable and configurable. The framework provides a set of utilities to import annotation data conveniently. To build ABrowse on existing annotation databases, data providers could specify SQL statements according to database schema. And customized pages for detailed information display of annotation entries could be easily plugged in. For developers, new drawing strategies could be integrated into ABrowse for new types of annotation data. In addition, standard web service is provided for data retrieval remotely, providing underlying machine-oriented programming interface for open data access.</p> <p>Conclusions</p> <p>ABrowse framework is valuable for end users, data providers and developers by providing rich user functions and flexible customization approaches. The source code is published under GNU Lesser General Public License v3.0 and is accessible at <url>http://www.abrowse.org/</url>. To demonstrate all the features of ABrowse, a live demo for <it>Arabidopsis thaliana </it>genome has been built at <url>http://arabidopsis.cbi.edu.cn/</url>.</p

Visualizing genome and systems biology: technologies, tools, implementation techniques and trends, past, present and future.

"Α picture is worth a thousand words." This widely used adage sums up in a few words the notion that a successful visual representation of a concept should enable easy and rapid absorption of large amounts of information. Although, in general, the notion of capturing complex ideas using images is very appealing, would 1000 words be enough to describe the unknown in a research field such as the life sciences? Life sciences is one of the biggest generators of enormous datasets, mainly as a result of recent and rapid technological advances; their complexity can make these datasets incomprehensible without effective visualization methods. Here we discuss the past, present and future of genomic and systems biology visualization. We briefly comment on many visualization and analysis tools and the purposes that they serve. We focus on the latest libraries and programming languages that enable more effective, efficient and faster approaches for visualizing biological concepts, and also comment on the future human-computer interaction trends that would enable for enhancing visualization further

Requirements of Modern Genome Browsers

Genome browsers are widely used tools for the visualization of a genome and related data. The demands placed on genome browsers due to the size, variety, and complexity of the data produced by modern biotechnology is increasing. These demands are poorly understood, and are not documented. Our study is establishing and documenting a clear set of requirements for genome browsers. Our study reviewed all widely used genome browsers, as well as notable research prototypes of genome browsers. This involved a review of the literature, executing typical uses of the genome browsers, program comprehension, reverse engineering, and code analysis. The key outcome of the study is a clear set of requirements in the form of a requirement document which conforms to the IEEE Std 830-1998 Standard of a Software Requirement Specification. This contains a domain model of concepts, the functional requirements as use cases, a definition of visualizations as metaphors, glyphs, or icons, formal specification of the system in Z notation and a specification of all widely used file formats. Genome browsers share a set of basic features like display, scroll, zoom, and search. However, they differ in their performance, maturity level and the implementation technologies. Our requirements also document the major non-functional requirements. The outcome of our study can be used in several ways: it can be used as a guide for future developers of Genome Browsers; it can form the basis of future enhancements of features in existing genome browsers; and it can motivate the invention of new algorithms, data structures, or file formats for implementations

Epiviz: Integrative Visual Analysis Software for Genomics

Computational and visual data analysis for genomics has traditionally involved a combination of tools and resources, of which the most ubiquitous consist of genome browsers, focused mainly on integrative visualization of large numbers of big datasets, and computational environments, focused on data modeling of a small number of moderately sized datasets. Workflows that involve the integration and exploration of multiple heterogeneous data sources, small and large, public and user specific have been poorly addressed by these tools. Commonly, the data visualized in these tools is the output of analyses performed in powerful computing environments like R/Bioconductor or Python. Two essential aspects of data analysis are usually treated as distinct, in spite of being part of the same exploratory process: algorithmic analysis and interactive visualization. In current technologies these are not integrated within one tool, but rather, one precedes the other. Recent technological advances in web-based data visualization have made it possible for interactive visualization tools to tightly integrate with powerful algorithmic tools, without being restricted to one such tool in particular. We introduce Epiviz (http://epiviz.cbcb.umd.edu), an integrative visualization tool that bridges the gap between the two types of tools, simplifying genomic data analysis workflows. Epiviz is the first genomics interactive visualization tool to provide tight-knit integration with computational and statistical modeling and data analysis. We discuss three ways in which Epiviz advances the field of genomic data analysis: 1) it brings code to interactive visualizations at various different levels; 2) takes the first steps in the direction of collaborative data analysis by incorporating user plugins from source control providers, as well as by allowing analysis states to be shared among the scientific community; 3) combines established analysis features that have never before been available simultaneously in a visualization tool for genomics. Epiviz can be used in multiple branches of genomics data analysis for various types of datasets, of which we detail two: functional genomics data, aligned to a continuous coordinate such as the genome, and metagenomics, organized according to volatile hierarchical coordinate spaces. We also present security implications of the current design, performance benchmarks, a series of limitations and future research steps