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HiPiler

HiPiler an interactive visualization interface for the exploration and visualization of regions-of-interest in large genome interaction matrices. Genome interaction matrices approximate the physical distance of pairs of genomic regions to each other and can contain up to 3 million rows and columns with many sparse regions. Traditional matrix aggregation or pan-and-zoom interfaces largely fail in supporting search, inspection, and comparison of local regions-of-interest (ROIs). ROIs can be defined, e.g., by sets of adjacent rows and columns, or by specific visual patterns in the matrix. ROIs are first-class objects in HiPiler, which represents them as thumbnail-like “snippets”. Snippets can be laid out automatically based on their data and meta attributes. They are linked back to the matrix and can be explored interactively. The design of HiPiler is based on a series of semi-structured interviews with 10 domain experts involved in the analysis and interpretation of genome interaction matrices. In the paper we describe six exploration tasks that are crucial for analysis of interaction matrices and demonstrate how HiPiler supports these tasks. We report on a user study with a series of data exploration sessions with domain experts to assess the usability of HiPiler as well as to demonstrate respective findings in the data.

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Institution: Harvard University

HiPiler is implemented as a web application consisting of a frontend interface for the visualizations and a server-side component that provides the data. The frontend is entirely written in JavaScript utilizing Aurelia as its application framework and Redux for fine-grained, history-aware state management. The matrix snippets are visualized with WebGL using Three.js as a middleware. Finally, HiGlass is integrated as a library for displaying the interaction matrix and genomic tracks. The server-side backend serves data to HiGlass and provides the matrix snippets. The backend is implemented in Python and uses Django as its application framework. The contact matrices are accessed through Cooler, a Python-based service library for storing and querying of Hi-C data. The front and backend are two separate applications that can be decoupled to load different data types. HiPiler is open source and available on GitHub.

Listeriomics

As for many model organisms, the amount of Listeria omics data produced has recently increased exponentially. There are now >80 published complete Listeria genomes, around 350 different transcriptomic data sets, and 25 proteomic data sets available. The analysis of these data sets through a systems biology approach and the generation of tools for biologists to browse these various data are a challenge for bioinformaticians. We have developed a web-based platform, named Listeriomics, that integrates different tools for omics data analyses, i.e., (i) an interactive genome viewer to display gene expression arrays, tiling arrays, and sequencing data sets along with proteomics and genomics data sets; (ii) an expression and protein atlas that connects every gene, small RNA, antisense RNA, or protein with the most relevant omics data; (iii) a specific tool for exploring protein conservation through the Listeria phylogenomic tree; and (iv) a coexpression network tool for the discovery of potential new regulations. Our platform integrates all the complete Listeria species genomes, transcriptomes, and proteomes published to date. This website allows navigation among all these data sets with enriched metadata in a user-friendly format and can be used as a central database for systems biology analysis.

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Institution: Institut Pasteur

Developed in Java using Eclipse RCP/RAP API

 

Supramap

Supramap is a completely new method of generating and sharing knowledge about evolution and biogeography.  A supramap gives people a quick and easy way to integrate genotypic and phenotypic data in a geospatial context. When viewed in a virtual globe (e.g. Google Earth or NASA WorldWind), the user has an interactive map of the spread of various lineages of organisms (e.g. strains of pathogens) over the earth.

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Institution: UNC Charlotte

Epiviz

Visualization is an integral aspect of genomics data analysis. Algorithmic-statistical analysis and interactive visualization are most effective when used iteratively. Epiviz, a web-based genome browser, and the Epivizr Bioconductor package allow interactive, extensible and reproducible visualization within a state-of-the-art data-analysis platform.

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Institution: University of Maryland, USA

expVIP

expVIP is an expression visualization and integration platform, which allows easy analysis of RNA-seq data combined with an intuitive and interactive interface. Users can analyze public and user-specified data sets with minimal bioinformatics knowledge using the expVIP virtual machine. This generates a custom Web browser to visualize, sort, and filter the RNA-seq data and provides outputs for differential gene expression analysis.

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Institution: John Innes Centre, Norwich; Genome Analysis Centre, Norwich

panX

panX is a powerful interactive platform for pan-genome exploration. It provides multiple different views on annotated genomes and allows rapid search by gene name, diversity, duplications, etc. Strain-specific meta data is integrated into the phylogenetic tree viewer such that associations between gene presence and phenotypes can be spotted.

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Institution: Max Planck Institute for Developmental Biology, Tuebingen, Germany

iobio

iobio uses immediate visual feedback to make understanding complex genomic datasets more intuitive, and analysis more interactive.  Applications include:

  • gene.iobio.io: a web app for investigating potential disease-causing variants
  • taxonomer.iobio.io: an ultra fast metagenomics classification and analysis app
  • bam.iobio.io: an alignment data inspector tool that quickly samples bam files and visualizes a series of metrics
  • vcf.iobio.io: a variant data inspector tool that quickly samples vcf files and visualizes a series of metrics
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Institution: Marth lab, USTAR Center for Genetic Discovery, University of Utah

EK3D

The inherent conformation of polysaccharides possess major challenge to determine/predict their 3D structure; despite their importance in various biological processes in all the organisms. Capsular polysaccharides (K antigen) are long-chain polysaccharides that make up the capsules of encapsulated Gram-negative bacteria. They help bacteria to escape from host defense mechanisms. We have developed a manually curated 3D structures’ database for 72 K antigens from various serotypes of Escherichia coli and developed an organized repository namely EK3D, which can be accessed by www.iith.ac.in/EK3D/. Using the Cartesian coordinate’s translation method, multimers of all 72 K antigens of E. coli can be generated of any desired length and torsion angles. Subsequently, generated modelscan be downloaded and used in docking studies or as starting model for NMR structure refinement.

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Institution: Department of Biotechnology, Indian Institute of Technology Hyderabad, Kandi, Telangana, India

Annotools

Vertebrate genome annotation is a core part of the Sanger Institute's work and has a dedicated team of 20 plus annotators with many years of experience. As the volume of genomic data has increased so the sophistication of our software has had to improve with graphical signposts, dynamic filtering and other techniques showing what's important. Annotools comprises programs written in C++ to be fast, efficient and offer a more complex interface than is really possible in a browser. They make good use of screen space supporting multiple screens, multiple windows and both vertical (maximum tracks) and horizontal (maximum sequence) display modes. The amount of data displayed is controllable via dynamic loading to the whole window or parts of the window, zooming thresholds and column compression. Transcripts and alignments are displayed with indications of co-linearity, non-canonical splice sites and missing sequence. Built-in tools allow searching features and sequence, comparing feature splice sites and configurable linking out to other data sources. The software can be run standalone or integrated into other systems via a remote control peer-to-peer communication system.

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Institution: Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire, UK

Phandango

Phandango is a fully interactive tool to allow visualization of population scale bacterial genomic data connected by a phylogeny. Population-scale genomic studies have been incredibly useful at understanding the evolution of bacteria and provided insights into clinically relevant information such as the spread of drug resistance and transmission patterns of infections diseases. The datasets produced by these projects often comprise hundreds of genomes and generate data such as predicted recombination regions, pan-genome contents, various metadata and, recently, genotype-phenotype association data. Currently these data are often explored using static visualizations generated by scripts. Phandango is a tool which allows real-time interactive visualization of these datasets simply by dragging and dropping files onto the browser. It has been found to be extremely useful to quickly interpret and compare the results generated from a number of published bioinformatics software such as GUBBINS, BRAT NextGen, ROARY, LS-BSR, TRADIS, PLINK and Seer, as well as user generated metadata.

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Institution: Wellcome Trust Sanger Institute, Cambridge, UK

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