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1. JBrowse Jupyter: a Python interface to JBrowse 2

   https://doi.org/10.1093/bioinformatics/btad032  

   De Jesus Martinez, Teresa; Hershberg, Elliot A; Guo, Emma; Stevens, Garrett J; Diesh, Colin; Xie, Peter; Bridge, Caroline; Cain, Scott; Haw, Robin; Buels, Robert M; et al (January 2023, Bioinformatics)

   Marschall, Tobias (Ed.)

   Abstract MotivationJBrowse Jupyter is a package that aims to close the gap between Python programming and genomic visualization. Web-based genome browsers are routinely used for publishing and inspecting genome annotations. Historically they have been deployed at the end of bioinformatics pipelines, typically decoupled from the analysis itself. However, emerging technologies such as Jupyter notebooks enable a more rapid iterative cycle of development, analysis and visualization. ResultsWe have developed a package that provides a Python interface to JBrowse 2’s suite of embeddable components, including the primary Linear Genome View. The package enables users to quickly set up, launch and customize JBrowse views from Jupyter notebooks. In addition, users can share their data via Google’s Colab notebooks, providing reproducible interactive views. Availability and implementationJBrowse Jupyter is released under the Apache License and is available for download on PyPI. Source code and demos are available on GitHub at https://github.com/GMOD/jbrowse-jupyter. 

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2. JBrowseR: an R interface to the JBrowse 2 genome browser

   https://doi.org/10.1093/bioinformatics/btab459  

   Hershberg, Elliot A; Stevens, Garrett; Diesh, Colin; Xie, Peter; De Jesus Martinez, Teresa; Buels, Robert; Stein, Lincoln; Holmes, Ian (November 2021, Bioinformatics)

   Alkan, Can (Ed.)

   Abstract MotivationGenome browsers are an essential tool in genome analysis. Modern genome browsers enable complex and interactive visualization of a wide variety of genomic data modalities. While such browsers are very powerful, they can be challenging to configure and program for bioinformaticians lacking expertise in web development. ResultsWe have developed an R package that provides an interface to the JBrowse 2 genome browser. The package can be used to configure and customize the browser entirely with R code. The browser can be deployed from the R console, or embedded in Shiny applications or R Markdown documents. Availability and implementationJBrowseR is available for download from CRAN, and the source code is openly available from the Github repository at https://github.com/GMOD/JBrowseR/. 

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3. HiCube: interactive visualization of multiscale and multimodal Hi-C and 3D genome data

   https://doi.org/10.1093/bioinformatics/btad154  

   Ye, Tiantian; Hu, Yangyang; Pun, Sydney; Ma, Wenxiu; Alkan, ed., Can (March 2023, Bioinformatics)

   Abstract SummaryHiCube is a lightweight web application for interactive visualization and exploration of diverse types of genomics data at multiscale resolutions. Especially, HiCube displays synchronized views of Hi-C contact maps and 3D genome structures with user-friendly annotation and configuration tools, thereby facilitating the study of 3D genome organization and function. Availability and implementationHiCube is implemented in Javascript and can be installed via NPM. The source code is freely available at GitHub (https://github.com/wmalab/HiCube). 

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4. Joint association and classification analysis of multi‐view data

   https://doi.org/10.1111/biom.13536  

   Zhang, Yunfeng; Gaynanova, Irina (August 2021, Biometrics)

   Abstract Multi‐view data, which is matched sets of measurements on the same subjects, have become increasingly common with advances in multi‐omics technology. Often, it is of interest to find associations between the views that are related to the intrinsic class memberships. Existing association methods cannot directly incorporate class information, while existing classification methods do not take into account between‐views associations. In this work, we propose a framework for Joint Association and Classification Analysis of multi‐view data (JACA). Our goal is not to merely improve the misclassification rates, but to provide a latent representation of high‐dimensional data that is both relevant for the subtype discrimination and coherent across the views. We motivate the methodology by establishing a connection between canonical correlation analysis and discriminant analysis. We also establish the estimation consistency of JACA in high‐dimensional settings. A distinct advantage of JACA is that it can be applied to the multi‐view data with block‐missing structure, that is to cases where a subset of views or class labels is missing for some subjects. The application of JACA to quantify the associations between RNAseq and miRNA views with respect to consensus molecular subtypes in colorectal cancer data from The Cancer Genome Atlas project leads to improved misclassification rates and stronger found associations compared to existing methods. 

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5. Rapid Prototyping for Coordinated Views of Multi-scale Spatial and Abstract Data: A Grammar-based Approach

   Harth, P; Bast, A; Troidl, J; Meulemeester, B; Pfister, H; Beyer, J; Oberlaender, M; Hege, HC; Baum, D (October 2023, Eurographics)

   Visualization grammars are gaining popularity as they allow visualization specialists and experienced users to quickly create static and interactive views. Existing grammars, however, mostly focus on abstract views, ignoring three-dimensional (3D) views, which are very important in fields such as natural sciences. We propose a generalized interaction grammar for the problem of coordinating heterogeneous view types, such as standard charts (e.g., based on Vega-Lite) and 3D anatomical views. An important aspect of our web-based framework is that user interactions with data items at various levels of detail can be systematically integrated and used to control the overall layout of the application workspace. With the help of a concise JSON-based specification of the intended workflow, we can handle complex interactive visual analysis scenarios. This enables rapid prototyping and iterative refinement of the visual analysis tool in collaboration with domain experts. We illustrate the usefulness of our framework in two real-world case studies from the field of neuroscience. Since the logic of the presented grammar-based approach for handling interactions between heterogeneous web-based views is free of any application specifics, it can also serve as a template for applications beyond biological research. 

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