CellexalVR: A virtual reality platform to visualize and analyze single-cell omics data

Single-cell omics: experimental workflow, data analyses and applications

Cells are the fundamental units of biological systems and exhibit unique development trajectories and molecular features. Our exploration of how the genomes orchestrate the formation and maintenance of each cell, and control the cellular phenotypes of various organismsis, is both captivating and intricate. Since the inception of the first single-cell RNA technology, technologies related to single-cell sequencing have experienced rapid advancements in recent years. These technologies have expanded horizontally to include single-cell genome, epigenome, proteome, and metabolome, while vertically, they have progressed to integrate multiple omics data and incorporate additional information such as spatial scRNA-seq and CRISPR screening. Single-cell omics represent a groundbreaking advancement in the biomedical field, offering profound insights into the understanding of complex diseases, including cancers. Here, we comprehensively summarize recent advances in single-cell omics technologies, with a specific focus on the methodology section. This overview aims to guide researchers in selecting appropriate methods for single-cell sequencing and related data analysis.

QuickVol: A lightweight browser tool for immersive visualizations of volumetric data

Volumetric layouts of data are becoming increasingly common in a number of fields. Visualizing these data often requires downloading a large suite of dedicated tools with a significant learning curve. This process can be overwhelming for students or new researchers looking to quickly visualize and showcase a volumetric dataset. QuickVol was developed as a system to allow for rapid viewing of volumetric data without requiring extra setup. Built on WebGL, our system can run on any modern web browser, including mobile browsers, and can work completely offline. Additionally, an experimental immersive hand-tracking feature is included, which allows for hands-free manipulation of the imported volume, along with a showcase mode for viewing with a virtual reality headset.

An architecture for collaboration in systems biology at the age of the Metaverse

As the current state of the Metaverse is largely driven by corporate interests, which may not align with scientific goals and values, academia should play a more active role in its development. Here, we present the challenges and solutions for building a Metaverse that supports systems biology research and collaboration. Our solution consists of two components: Kosmogora, a server ensuring biological data access, traceability, and integrity in the context of a highly collaborative environment such as a metaverse; and ECellDive, a virtual reality application to explore, interact, and build upon the data managed by Kosmogora. We illustrate the synergy between the two components by visualizing a metabolic network and its flux balance analysis. We also argue that the Metaverse of systems biology will foster closer communication and cooperation between experimentalists and modelers in the field.

Exocentric and Egocentric Views for Biomedical Data Analytics in Virtual Environments-A Usability Study

Biomedical datasets are usually large and complex, containing biological information about a disease. Computational analytics and the interactive visualisation of such data are essential decision-making tools for disease diagnosis and treatment. Oncology data models were observed in a virtual reality environment to analyse gene expression and clinical data from a cohort of cancer patients. The technology enables a new way to view information from the outside in (exocentric view) and the inside out (egocentric view), which is otherwise not possible on ordinary displays. This paper presents a usability study on the exocentric and egocentric views of biomedical data visualisation in virtual reality and their impact on usability on human behaviour and perception. Our study revealed that the performance time was faster in the exocentric view than in the egocentric view. The exocentric view also received higher ease-of-use scores than the egocentric view. However, the influence of usability on time performance was only evident in the egocentric view. The findings of this study could be used to guide future development and refinement of visualisation tools in virtual reality.

Technologies for whole-cell modeling: Genome-wide reconstruction of a cell in silico

With advances in high-throughput, large-scale in vivo measurement and genome modification techniques at the single-nucleotide level, there is an increasing demand for the development of new technologies for the flexible design and control of cellular systems. Computer-aided design is a powerful tool to design new cells. Whole-cell modeling aims to integrate various cellular subsystems, determine their interactions and cooperative mechanisms, and predict comprehensive cellular behaviors by computational simulations on a genome-wide scale. It has been applied to prokaryotes, yeasts, and higher eukaryotic cells, and utilized in a wide range of applications, including production of valuable substances, drug discovery, and controlled differentiation. Whole-cell modeling, consisting of several thousand elements with diverse scales and properties, requires innovative model construction, simulation, and analysis techniques. Furthermore, whole-cell modeling has been extended to multiple scales, including high-resolution modeling at the single-nucleotide and single-amino acid levels and multicellular modeling of tissues and organs. This review presents an overview of the current state of whole-cell modeling, discusses the novel computational and experimental technologies driving it, and introduces further developments toward multihierarchical modeling on a whole-genome scale.

Digital Phenotyping: A Game Changer for the Broiler Industry

In response to escalating global demand for poultry, the industry grapples with an array of intricate challenges, from enhancing productivity to improving animal welfare and attenuating environmental impacts. This comprehensive review explores the transformative potential of digital phenotyping, an emergent technological innovation at the cusp of dramatically reshaping broiler production. The central aim of this study is to critically examine digital phenotyping as a pivotal solution to these multidimensional industry conundrums. Our investigation spotlights the profound implications of 'digital twins' in the burgeoning field of broiler genomics, where the production of exact digital counterparts of physical entities accelerates genomics research and its practical applications. Further, this review probes into the ongoing advancements in the research and development of a context-sensitive, multimodal digital phenotyping platform, custom-built to monitor broiler health. This paper critically evaluates this platform's potential in revolutionizing health monitoring, fortifying the resilience of broiler production, and fostering a harmonious balance between productivity and sustainability. Subsequently, the paper provides a rigorous assessment of the unique challenges that may surface during the integration of digital phenotyping within the industry. These span from technical and economic impediments to ethical deliberations, thus offering a comprehensive perspective. The paper concludes by highlighting the game-changing potential of digital phenotyping in the broiler industry and identifying potential future directions for the field, underlining the significance of continued research and development in unlocking digital phenotyping's full potential. In doing so, it charts a course towards a more robust, sustainable, and productive broiler industry. The insights garnered from this study hold substantial value for a broad spectrum of stakeholders in the broiler industry, setting the stage for an imminent technological evolution in poultry production.

Developing virtual and augmented reality applications for science, technology, engineering and math education

The Rhode Island IDeA Network of Biomedical Research Excellence Molecular Informatics Core at the University of Rhode Island Information Technology Services Innovative Learning Technologies developed virtual and augmented reality applications to teach concepts in biomedical science, including pharmacology, medicinal chemistry, cell culture and nanotechnology. The apps were developed as full virtual reality/augmented reality and 3D gaming versions, which do not require virtual reality headsets. Development challenges included creating intuitive user interfaces, text-to-voice functionality, visualization of molecules and implementing complex science concepts. In-app quizzes are used to assess the user's understanding of topics, and user feedback was collected for several apps to improve the experience. The apps were positively reviewed by users and are being implemented into the curriculum at the University of Rhode Island.

scViewer: An Interactive Single-Cell Gene Expression Visualization Tool

Single-cell RNA sequencing (scRNA-seq) is an attractive technology for researchers to gain valuable insights into the cellular processes and cell type diversity present in all tissues. The data generated by the scRNA-seq experiment are high-dimensional and complex in nature. Several tools are now available to analyze the raw scRNA-seq data from public databases; however, simple and easy-to-explore single-cell gene expression visualization tools focusing on differential expression and co-expression are lacking. Here, we present scViewer, an interactive graphical user interface (GUI) R/Shiny application designed to facilitate the visualization of scRNA-seq gene expression data. With the processed Seurat RDS object as input, scViewer utilizes several statistical approaches to provide detailed information on the loaded scRNA-seq experiment and generates publication-ready plots. The major functionalities of scViewer include exploring cell-type-specific gene expression, co-expression analysis of two genes, and differential expression analysis with different biological conditions considering both cell-level and subject-level variations using negative binomial mixed modeling. We utilized a publicly available dataset (brain cells from a study of Alzheimer's disease to demonstrate the utility of our tool. scViewer can be downloaded from GitHub as a Shiny app with local installation. Overall, scViewer is a user-friendly application that will allow researchers to visualize and interpret the scRNA-seq data efficiently for multi-condition comparison by performing gene-level differential expression and co-expression analysis on the fly. Considering the functionalities of this Shiny app, scViewer can be a great resource for collaboration between bioinformaticians and wet lab scientists for faster data visualizations.

StarmapVis: An interactive and narrative visualisation tool for single-cell and spatial data

Current single-cell visualisation techniques project high dimensional data into 'map' views to identify high-level structures such as cell clusters and trajectories. New tools are needed to allow the transversal through the high dimensionality of single-cell data to explore the single-cell local neighbourhood. StarmapVis is a convenient web application displaying an interactive downstream analysis of single-cell expression or spatial transcriptomic data. The concise user interface is powered by modern web browsers to explore the variety of viewing angles unavailable to 2D media. Interactive scatter plots display clustering information, while the trajectory and cross-comparison among different coordinates are displayed in connectivity networks. Automated animation of camera view is a unique feature of our tool. StarmapVis also offers a useful animated transition between two-dimensional spatial omic data to three-dimensional single cell coordinates. The usability of StarmapVis is demonstrated by four data sets, showcasing its practical usability. StarmapVis is available at: https://holab-hku.github.io/starmapVis.

Extended reality gives digital agricultural biotechnology a new dimension

Facing up to the global challenges of designing climate-resilient biotech crops involves a great deal of out-of-the-box thinking. Extended reality is coming of age in digital agricultural biotechnology. Here, we seek to stimulate technological innovation by empowering future innovators, researchers, academics, and startups to think and partner creatively.

Bioinformatics and the Metaverse: Are We Ready?

COVID-19 forced humanity to think about new ways of working globally without physically being present with other people, and eXtended Reality (XR) systems (defined as Virtual Reality, Augmented Reality and Mixed Reality) offer a potentially elegant solution. Previously seen as mainly for gaming, commercial and research institutions are investigating XR solutions to solve real world problems from training, simulation, mental health, data analysis, and studying disease progression. More recently large corporations such as Microsoft and Meta have announced they are developing the Metaverse as a new paradigm to interact with the digital world. This article will look at how visualization can leverage the Metaverse in bioinformatics research, the pros and cons of this technology, and what the future may hold.

A Brave New World: Virtual Reality and Augmented Reality in Systems Biology

How we interact with computer graphics has not changed significantly from viewing 2D text and images on a flatscreen since their invention. Yet, recent advances in computing technology, internetworked devices and gaming are driving the design and development of new ideas in other modes of human-computer interfaces (HCIs). Virtual Reality (VR) technology uses computers and HCIs to create the feeling of immersion in a three-dimensional (3D) environment that contains interactive objects with a sense of spatial presence, where objects have a spatial location relative to, and independent of the users. While this virtual environment does not necessarily match the real world, by creating the illusion of reality, it helps users leverage the full range of human sensory capabilities. Similarly, Augmented Reality (AR), superimposes virtual images to the real world. Because humans learn the physical world through a gradual sensory familiarization, these immersive visualizations enable gaining familiarity with biological systems not realizable in the physical world (e.g., allosteric regulatory networks within a protein or biomolecular pathways inside a cell). As VR/AR interfaces are anticipated to be explosive in consumer markets, systems biologists will be more immersed into their world. Here we introduce a brief history of VR/AR, their current roles in systems biology, and advantages and disadvantages in augmenting user abilities. We next argue that in systems biology, VR/AR technologies will be most useful in visually exploring and communicating data; performing virtual experiments; and education/teaching. Finally, we discuss our perspective on future directions for VR/AR in systems biology.

Spatially resolved transcriptomics in immersive environments

Spatially resolved transcriptomics is an emerging class of high-throughput technologies that enable biologists to systematically investigate the expression of genes along with spatial information. Upon data acquisition, one major hurdle is the subsequent interpretation and visualization of the datasets acquired. To address this challenge, VR-Cardiomics is presented, which is a novel data visualization system with interactive functionalities designed to help biologists interpret spatially resolved transcriptomic datasets. By implementing the system in two separate immersive environments, fish tank virtual reality (FTVR) and head-mounted display virtual reality (HMD-VR), biologists can interact with the data in novel ways not previously possible, such as visually exploring the gene expression patterns of an organ, and comparing genes based on their 3D expression profiles. Further, a biologist-driven use-case is presented, in which immersive environments facilitate biologists to explore and compare the heart expression profiles of different genes.

A Novel Gesture-Based Control System for Fluorescence Volumetric Data in Virtual Reality

With the development of light microscopy, it is becoming increasingly easy to obtain detailed multicolor fluorescence volumetric data. The need for their appropriate visualization has become an integral part of fluorescence imaging. Virtual reality (VR) technology provides a new way of visualizing multidimensional image data or models so that the entire 3D structure can be intuitively observed, together with different object features or details on or within the object. With the need for imaging advanced volumetric data, demands for the control of virtual object properties are increasing; this happens especially for multicolor objects obtained by fluorescent microscopy. Existing solutions with universal VR controllers or software-based controllers with the need to define sufficient space for the user to manipulate data in VR are not usable in many practical applications. Therefore, we developed a custom gesture-based VR control system with a custom controller connected to the FluoRender visualization environment. A multitouch sensor disk was used for this purpose. Our control system may be a good choice for easier and more comfortable manipulation of virtual objects and their properties, especially using confocal microscopy, which is the most widely used technique for acquiring volumetric fluorescence data so far.