DIRMC: a database of immunotherapy-related molecular characteristics.

Cancer immunotherapy has brought about a revolutionary breakthrough in the field of cancer treatment. Immunotherapy has changed the treatment landscape for a variety of solid and hematologic malignancies. To assist researchers in efficiently uncovering valuable information related to cancer immunotherapy, we have presented a manually curated comprehensive database called DIRMC, which focuses on molecular features involved in cancer immunotherapy. All the content was collected manually from published literature, authoritative clinical trial data submitted by clinicians, some databases for drug target prediction such as DrugBank, and some experimentally confirmed high-throughput data sets for the characterization of immune-related molecular interactions in cancer, such as a curated database of T-cell receptor sequences with known antigen specificity (VDJdb), a pathology-associated TCR database (McPAS-TCR) et al. By constructing a fully connected functional network, ranging from cancer-related gene mutations to target genes to translated target proteins to protein regions or sites that may specifically affect protein function, we aim to comprehensively characterize molecular features related to cancer immunotherapy. We have developed the scoring criteria to assess the reliability of each MHC-peptide-T-cell receptor (TCR) interaction item to provide a reference for users. The database provides a user-friendly interface to browse and retrieve data by genes, target proteins, diseases and more. DIRMC also provides a download and submission page for researchers to access data of interest for further investigation or submit new interactions related to cancer immunotherapy targets. Furthermore, DIRMC provides a graphical interface to help users predict the binding affinity between their own peptide of interest and MHC or TCR. This database will provide researchers with a one-stop resource to understand cancer immunotherapy-related targets as well as data on MHC-peptide-TCR interactions. It aims to offer reliable molecular characteristics support for both the analysis of the current status of cancer immunotherapy and the development of new immunotherapy. DIRMC is available at http://www.dirmc.tech/. Database URL: http://www.dirmc.tech/.

Designing for Improved Patient Experiences in Home Dialysis: Usability and User Experience Findings From User-Based Evaluation Study With Patients With Chronic Conditions.

BACKGROUND: Chronic kidney disease affects 10% of the population worldwide, and the number of patients receiving treatment for end-stage kidney disease is forecasted to increase. Therefore, there is a pressing need for innovative digital solutions that increase the efficiency of care and improve patients' quality of life. The aim of the eHealth in Home Dialysis project is to create a novel eHealth solution, called eC4Me, to facilitate predialysis and home dialysis care for patients with chronic kidney disease. OBJECTIVE: Our study aimed to evaluate the usability, user experience (UX), and patient experience (PX) of the first version of the eC4Me solution. METHODS: We used a user-based evaluation approach involving usability testing, questionnaire, and interview methods. The test sessions were conducted remotely with 10 patients with chronic kidney disease, 5 of whom had used the solution in their home environment before the tests, while the rest were using it for the first time. Thematic analysis was used to analyze user test and questionnaire data, and descriptive statistics were calculated for the UMUX (Usability Metric for User Experience) scores. RESULTS: Most usability problems were related to navigation, the use of terminology, and the presentation of health-related data. Despite usability challenges, UMUX ratings of the solution were positive overall. The results showed noteworthy variation in the expected benefits and perceived effort of using the solution. From a PX perspective, it is important that the solution supports patients' own health-related goals and fits with the needs of their everyday lives with the disease. CONCLUSIONS: A user-based evaluation is a useful and necessary part of the eHealth solution development process. Our study findings can be used to improve the usability and UX of the evaluated eC4Me solution. Patients should be actively involved in the solution development process when specifying what information is relevant for them. Traditional usability tests complemented with questionnaire and interview methods can serve as a meaningful methodological approach for gaining insight not only into usability but also into UX- and PX-related aspects of digital health solutions.

Comparative evaluation of the web-based contiguous cartogram generation tool go-cart.io.

Area cartograms are map-based data visualizations in which the area of each map region is proportional to the data value it represents. Long utilized in print media, area cartograms have also become increasingly popular online, often accompanying news articles and blog posts. Despite their popularity, there is a dearth of cartogram generation tools accessible to non-technical users unfamiliar with Geographic Information Systems software. Few tools support the generation of contiguous cartograms (i.e., area cartograms that faithfully represent the spatial adjacency of neighboring regions). We thus reviewed existing contiguous cartogram software and compared two web-based cartogram tools: fBlog and go-cart.io. We experimentally evaluated their usability through a user study comprising cartogram generation and analysis tasks. The System Usability Scale was adopted to quantify how participants perceived the usability of both tools. We also collected written feedback from participants to determine the main challenges faced while using the software. Participants generally rated go-cart.io as being more usable than fBlog. Compared to fBlog, go-cart.io offers a greater variety of built-in maps and allows importing data values by file upload. Still, our results suggest that even go-cart.io suffers from poor usability because the graphical user interface is complex and data can only be imported as a comma-separated-values file. We also propose changes to go-cart.io and make general recommendations for web-based cartogram tools to address these concerns.

The fine line between automation and augmentation in website usability evaluation.

Artificial Intelligence (AI) systems are becoming widespread in all aspects of society, bringing benefits to the whole economy. There is a growing understanding of the potential benefits and risks of this type of technology. While the benefits are more efficient decision processes and industrial productivity, the risks may include a potential progressive disengagement of human beings in crucial aspects of decision-making. In this respect, a new perspective is emerging that aims at reconsidering the centrality of human beings while reaping the benefits of AI systems to augment rather than replace professional skills: Human-Centred AI (HCAI) is a novel framework that posits that high levels of human control do not contradict high levels of computer automation. In this paper, we investigate the two antipodes, automation vs augmentation, in the context of website usability evaluation. Specifically, we have analyzed whether the level of automation provided by a tool for semi-automatic usability evaluation can support evaluators in identifying usability problems. Three different visualizations, each one corresponding to a different level of automation, ranging from a full-automation approach to an augmentation approach, were compared in an experimental study. We found that a fully automated approach could help evaluators detect a significant number of medium and high-severity usability problems, which are the most critical in a software system; however, it also emerged that it was possible to detect more low-severity usability problems using one of the augmented approaches proposed in this paper.

REDCap to Epic interfaces create an efficient hybrid software solution for a public health registry.

A public health registry and intervention was created in response to the Flint water crisis to identify and refer exposed individuals to public health services to ameliorate the deleterious impact of lead exposure. Traditional technology architecture domains, funded scope of work, as well as community input were considered when defining the requirements of the selected solutions. A hybrid software solution was created using Research Electronic Data Capture (REDCap) to deploy an open participant survey and bypass requirements to create user accounts, and Epic to manage deduplication and participant communication and tracking. To bridge the two software systems, REDCap to Epic unidirectional ADT and Documentation Flowsheet interfaces were built to automate creation of subject records in Epic identical to those created in REDCap and to copy key protocol-driving variables from REDCap to Epic. The interfaces were critical to deliver a successful hybrid solution in which the desired features of each software could be leveraged to satisfy specific protocol requirements and community input. Data from the start of survey administration (December 2018) through 31 December 2020 are reported to demonstrate the usefulness of the interfaces.

K-Track-Covid: interactive web-based dashboard for analyzing geographical and temporal spread of COVID-19 in South Korea.

The COVID-19 pandemic has necessitated the development of robust tools for tracking and modeling the spread of the virus. We present 'K-Track-Covid,' an interactive web-based dashboard developed using the R Shiny framework, to offer users an intuitive dashboard for analyzing the geographical and temporal spread of COVID-19 in South Korea. Our dashboard employs dynamic user interface elements, employs validated epidemiological models, and integrates regional data to offer tailored visual displays. The dashboard allows users to customize their data views by selecting specific time frames, geographic regions, and demographic groups. This customization enables the generation of charts and statistical summaries pertinent to both daily fluctuations and cumulative counts of COVID-19 cases, as well as mortality statistics. Additionally, the dashboard offers a simulation model based on mathematical models, enabling users to make predictions under various parameter settings. The dashboard is designed to assist researchers, policymakers, and the public in understanding the spread and impact of COVID-19, thereby facilitating informed decision-making. All data and resources related to this study are publicly available to ensure transparency and facilitate further research.

Implementation and Evaluation of Walk-in-Place Using a Low-Cost Motion-Capture Device for Virtual Reality Applications.

Virtual reality (VR) is used in many fields, including entertainment, education, training, and healthcare, because it allows users to experience challenging and dangerous situations that may be impossible in real life. Advances in head-mounted display technology have enhanced visual immersion, offering content that closely resembles reality. However, several factors can reduce VR immersion, particularly issues with the interactions in the virtual world, such as locomotion. Additionally, the development of locomotion technology is occurring at a moderate pace. Continuous research is being conducted using hardware such as treadmills, and motion tracking using depth cameras, but they are costly and space-intensive. This paper presents a walk-in-place (WIP) algorithm that uses Mocopi, a low-cost motion-capture device, to track user movements in real time. Additionally, its feasibility for VR applications was evaluated by comparing its performance with that of a treadmill using the absolute trajectory error metric and survey data collected from human participants. The proposed WIP algorithm with low-cost Mocopi exhibited performance similar to that of the high-cost treadmill, with significantly positive results for spatial awareness. This study is expected to contribute to solving the issue of spatial constraints when experiencing infinite virtual spaces.

Solvate Suite: A Command-Line Interface for Molecular Simulations and Multiscale Microsolvation Modeling.

In this work, we introduce the Solvate Suite, a comprehensive and modular command-line interface designed for molecular simulation and microsolvation modeling. The suite interfaces with widely used scientific software, streamlining computational experiments for liquid systems through the automated creation of simulation boxes and topology with adjustable simulation parameters. Furthermore, it has features for graphical and statistical analysis of simulated properties and extraction of trajectory configurations with various filters. Additionally, it introduces innovative strategies for microsolvation modeling with a multiscale approach, employing equilibrated dynamics to identify favorable solute-solvent interactions and enabling full cluster optimization for free-energy calculations without imaginary frequency contamination.

AutoDock-SS: AutoDock for Multiconformational Ligand-Based Virtual Screening.

Ligand-based virtual screening (LBVS) can be pivotal for identifying potential drug leads, especially when the target protein's structure is unknown. However, current LBVS methods are limited in their ability to consider the ligand conformational flexibility. This study presents AutoDock-SS (Similarity Searching), which adapts protein-ligand docking for use in LBVS. AutoDock-SS integrates novel ligand-based grid maps and AutoDock-GPU into a novel three-dimensional LBVS workflow. Unlike other approaches based on pregenerated conformer libraries, AutoDock-SS's built-in conformational search optimizes conformations dynamically based on the reference ligand, thus providing a more accurate representation of relevant ligand conformations. AutoDock-SS supports two modes: single and multiple ligand queries, allowing for the seamless consideration of multiple reference ligands. When tested on the Directory of Useful Decoys─Enhanced (DUD-E) data set, AutoDock-SS surpassed alternative 3D LBVS methods, achieving a mean AUROC of 0.775 and an EF1% of 25.72 in single-reference mode. The multireference mode, evaluated on the augmented DUD-E+ data set, demonstrated superior accuracy with a mean AUROC of 0.843 and an EF1% of 34.59. This enhanced performance underscores AutoDock-SS's ability to treat compounds as conformationally flexible while considering the ligand's shape, pharmacophore, and electrostatic potential, expanding the potential of LBVS methods.

Patient and Caregiver Perceptions of an Interface Design to Communicate Artificial Intelligence-Based Prognosis for Patients With Advanced Solid Tumors.

PURPOSE: Use of artificial intelligence (AI) in cancer care is increasing. What remains unclear is how best to design patient-facing systems that communicate AI output. With oncologist input, we designed an interface that presents patient-specific, machine learning-based 6-month survival prognosis information designed to aid oncology providers in preparing for and discussing prognosis with patients with advanced solid tumors and their caregivers. The primary purpose of this study was to assess patient and caregiver perceptions and identify enhancements of the interface for communicating 6-month survival and other prognosis information when making treatment decisions concerning anticancer and supportive therapy. METHODS: This qualitative study included interviews and focus groups conducted between November and December 2022. Purposive sampling was used to recruit former patients with cancer and/or former caregivers of patients with cancer who had participated in cancer treatment decisions from Utah or elsewhere in the United States. Categories and themes related to perceptions of the interface were identified. RESULTS: We received feedback from 20 participants during eight individual interviews and two focus groups, including four cancer survivors, 13 caregivers, and three representing both. Overall, most participants expressed positive perceptions about the tool and identified its value for supporting decision making, feeling less alone, and supporting communication among oncologists, patients, and their caregivers. Participants identified areas for improvement and implementation considerations, particularly that oncologists should share the tool and guide discussions about prognosis with patients who want to receive the information. CONCLUSION: This study revealed important patient and caregiver perceptions of and enhancements for the proposed interface. Originally designed with input from oncology providers, patient and caregiver participants identified additional interface design recommendations and implementation considerations to support communication about prognosis.

A Framework for Real-Time Gestural Recognition and Augmented Reality for Industrial Applications.

In recent decades, technological advancements have transformed the industry, highlighting the efficiency of automation and safety. The integration of augmented reality (AR) and gesture recognition has emerged as an innovative approach to create interactive environments for industrial equipment. Gesture recognition enhances AR applications by allowing intuitive interactions. This study presents a web-based architecture for the integration of AR and gesture recognition, designed to interact with industrial equipment. Emphasizing hardware-agnostic compatibility, the proposed structure offers an intuitive interaction with equipment control systems through natural gestures. Experimental validation, conducted using Google Glass, demonstrated the practical viability and potential of this approach in industrial operations. The development focused on optimizing the system's software and implementing techniques such as normalization, clamping, conversion, and filtering to achieve accurate and reliable gesture recognition under different usage conditions. The proposed approach promotes safer and more efficient industrial operations, contributing to research in AR and gesture recognition. Future work will include improving the gesture recognition accuracy, exploring alternative gestures, and expanding the platform integration to improve the user experience.

Evaluation of power wheelchair driving performance in simulator compared to driving in real-life situations: the SIMADAPT (simulator ADAPT) project-a pilot study.

OBJECTIVE: The objective of this study was to evaluate users' driving performances with a Power Wheelchair (PWC) driving simulator in comparison to the same driving task in real conditions with a standard power wheelchair. METHODS: Three driving circuits of progressive difficulty levels (C1, C2, C3) that were elaborated to assess the driving performances with PWC in indoor situations, were used in this study. These circuits have been modeled in a 3D Virtual Environment to replicate the three driving task scenarios in Virtual Reality (VR). Users were asked to complete the three circuits with respect to two testing conditions during three successive sessions, i.e. in VR and on a real circuit (R). During each session, users completed the two conditions. Driving performances were evaluated using the number of collisions and time to complete the circuit. In addition, driving ability by Wheelchair Skill Test (WST) and mental load were assessed in both conditions. Cybersickness, user satisfaction and sense of presence were measured in VR. The conditions R and VR were randomized. RESULTS: Thirty-one participants with neurological disorders and expert wheelchair drivers were included in the study. The driving performances between VR and R conditions were statistically different for the C3 circuit but were not statistically different for the two easiest circuits C1 and C2. The results of the WST was not statistically different in C1, C2 and C3. The mental load was higher in VR than in R condition. The general sense of presence was reported as acceptable (mean value of 4.6 out of 6) for all the participants, and the cybersickness was reported as acceptable (SSQ mean value of 4.25 on the three circuits in VR condition). CONCLUSION: Driving performances were statistically different in the most complicated circuit C3 with an increased number of collisions in VR, but were not statistically different for the two easiest circuits C1 and C2 in R and VR conditions. In addition, there were no significant adverse effects such as cybersickness. The results show the value of the simulator for driving training applications. Still, the mental load was higher in VR than in R condition, thus mitigating the potential for use with people with cognitive disorders. Further studies should be conducted to assess the quality of skill transfer for novice drivers from the simulator to the real world. Trial registration Ethical approval n ∘ 2019-A001306-51 from Comité de Protection des Personnes Sud Mediterranée IV. Trial registered the 19/11/2019 on ClinicalTrials.gov in ID: NCT04171973.

Usability Comparison Among Healthy Participants of an Anthropomorphic Digital Human and a Text-Based Chatbot as a Responder to Questions on Mental Health: Randomized Controlled Trial.

BACKGROUND: The use of chatbots in mental health support has increased exponentially in recent years, with studies showing that they may be effective in treating mental health problems. More recently, the use of visual avatars called digital humans has been introduced. Digital humans have the capability to use facial expressions as another dimension in human-computer interactions. It is important to study the difference in emotional response and usability preferences between text-based chatbots and digital humans for interacting with mental health services. OBJECTIVE: This study aims to explore to what extent a digital human interface and a text-only chatbot interface differed in usability when tested by healthy participants, using BETSY (Behavior, Emotion, Therapy System, and You) which uses 2 distinct interfaces: a digital human with anthropomorphic features and a text-only user interface. We also set out to explore how chatbot-generated conversations on mental health (specific to each interface) affected self-reported feelings and biometrics. METHODS: We explored to what extent a digital human with anthropomorphic features differed from a traditional text-only chatbot regarding perception of usability through the System Usability Scale, emotional reactions through electroencephalography, and feelings of closeness. Healthy participants (n=45) were randomized to 2 groups that used a digital human with anthropomorphic features (n=25) or a text-only chatbot with no such features (n=20). The groups were compared by linear regression analysis and t tests. RESULTS: No differences were observed between the text-only and digital human groups regarding demographic features. The mean System Usability Scale score was 75.34 (SD 10.01; range 57-90) for the text-only chatbot versus 64.80 (SD 14.14; range 40-90) for the digital human interface. Both groups scored their respective chatbot interfaces as average or above average in usability. Women were more likely to report feeling annoyed by BETSY. CONCLUSIONS: The text-only chatbot was perceived as significantly more user-friendly than the digital human, although there were no significant differences in electroencephalography measurements. Male participants exhibited lower levels of annoyance with both interfaces, contrary to previously reported findings.

MaRGE: A graphical environment for MaRCoS.

The open-source console MaRCoS, which stands for "Magnetic Resonance Control System", combines hardware, firmware and software elements for integral control of Magnetic Resonance Imaging (MRI) scanners. Previous developments have focused on making the system robust and reliable, rather than on users, who have been somewhat overlooked. This work describes a Graphical User Interface (GUI) designed for intuitive control of MaRCoS, as well as compatibility with clinical environments. The GUI is based on an arrangement of tabs and a renewed Application Program Interface (API). Compared to the previous versions, the MaRGE package ("MaRCoS Graphical Environment") includes new functionalities such as the possibility to export images to standard DICOM formats, create and manage clinical protocols, or display and process image reconstructions, among other features conceived to simplify the operation of MRI scanners. All prototypes in our facilities are commanded by MaRCoS and operated with the new GUI. Here we report on its performance on an experimental 0.2 T scanner designed for hard-tissue, as well as a 72 mT portable scanner presently installed in the radiology department of a large hospital. The possibility to customize, adapt and streamline processes has substantially improved our workflows and overall experience.

Evaluating the Usability of an mHealth App for Empowering Cancer Survivors With Disabilities: Heuristic Evaluation and Usability Testing.

BACKGROUND: More than 18 million cancer survivors are living in the United States. The effects of cancer and its treatments can have cognitive, psychological, physical, and social consequences that many survivors find incredibly disabling. Posttreatment support is often unavailable or underused, especially for survivors living with disabilities. This leaves them to deal with new obstacles and struggles on their own, oftentimes feeling lost during this transition. Mobile health (mHealth) interventions have been shown to effectively aid cancer survivors in dealing with many of the aftereffects of cancer and its treatments; these interventions hold immense potential for survivors living with disabilities. We developed a prototype for WeCanManage, an mHealth-delivered self-management intervention to empower cancer survivors living with disabilities through problem-solving, mindfulness, and self-advocacy training. OBJECTIVE: Our study conducted a heuristic evaluation of the WeCanManage high-fidelity prototype and assessed its usability among cancer survivors with known disabilities. METHODS: We evaluated the prototype using Nielsen's 10 principles of heuristic evaluation with 22 human-computer interaction university students. On the basis of the heuristic evaluation findings, we modified the prototype and conducted usability testing on 10 cancer survivors with a variety of known disabilities, examining effectiveness, efficiency, usability, and satisfaction, including a completion of the modified System Usability Scale (SUS). RESULTS: The findings from the heuristic evaluation were mostly favorable, highlighting the need for a help guide, addressing accessibility concerns, and enhancing the navigation experience. After usability testing, the average SUS score was 81, indicating a good-excellent design. The participants in the usability testing sample expressed positive reactions toward the app's design, educational content and videos, and the available means of connecting with others. They identified areas for improvement, such as improving accessibility, simplifying navigation within the community forums, and providing a more convenient method to access the help guide. CONCLUSIONS: Overall, usability testing showed positive results for the design of WeCanManage. The course content and features helped participants feel heard, understood, and less alone.

User Personas for a "Better Design" of Nation-Wide EHRs Based on Thorough Expert Evaluation and Field Analysis: Modeling Users as Individuals Plus Family Members for an Enhanced Mapping of Healthcare Situations.

Electronic Health Records (EHRs) are pivotal in prevention, therapy, and care. Their design necessitates the representation of users, activities, context, and technology. Among various participative and ethnographic design methods, user personas are an effective tool for encapsulating users in the design process. Goals and methods: This research focused on the creation of user personas for the design of a nation-wide EHR, specifically the German "elektronische Patientenakte" (ePA). We employed qualitative methods, such as field analysis and expert workshops, to generate, assess, and refine a set of user personas that can cover the complexity of real-life familial care environments. We used an innovative bottom-up approach applying a whole new process for persona generation especially in the context of family management. Results: The research yielded an initial set of five personas that accurately represent fictional user types. Importantly, at least two of these personas encapsulate the unique challenges inherent in family care work. These results provide a foundation for future work, which can utilize these personas for EHR design, as well as for further evaluation and refinement.

Agile eHealth Usability Evaluation: A Triangulative Approach to Promoting the Usability of eHealth Systems.

BACKGROUND: Usability evaluation is difficult to reconcile with agile software development for eHealth systems, because traditional usability evaluation is often complex and cumbersome to implement. However, obtaining prospective users' feedback during agile software development is crucial for improving the usability of eHealth systems, which is why there is an increasing need for agile eHealth usability evaluation. OBJECTIVE: This study investigates whether agile usability evaluations are suitable to evaluate patient-centered eHealth systems being agile developed in health care and are applicable for prospective users, such as older persons suffering from age-related declines. METHODS: A triangulation study was conducted combining iterative expert interviews with an exploratory case study. RESULTS: The triangulation study revealed that the implementation of an agile eHealth usability evaluation with prospective users such as older persons proved to be possible. CONCLUSION: Established eHealth usability evaluation methods must be further evolved to address age-related impairments of older persons.

PTVR - A software in Python to make virtual reality experiments easier to build and more reproducible.

Researchers increasingly use virtual reality (VR) to perform behavioral experiments, especially in vision science. These experiments are usually programmed directly in so-called game engines that are extremely powerful. However, this process is tricky and time-consuming as it requires solid knowledge of game engines. Consequently, the anticipated prohibitive effort discourages many researchers who want to engage in VR. This paper introduces the Perception Toolbox for Virtual Reality (PTVR) library, allowing visual perception studies in VR to be created using high-level Python script programming. A crucial consequence of using a script is that an experiment can be described by a single, easy-to-read piece of code, thus improving VR studies' transparency, reproducibility, and reusability. We built our library upon a seminal open-source library released in 2018 that we have considerably developed since then. This paper aims to provide a comprehensive overview of the PTVR software for the first time. We introduce the main objects and features of PTVR and some general concepts related to the three-dimensional (3D) world. This new library should dramatically reduce the difficulty of programming experiments in VR and elicit a whole new set of visual perception studies with high ecological validity.

Shaoxia: a web-based interactive analysis platform for single cell RNA sequencing data.

BACKGROUND: In recent years, Single-cell RNA sequencing (scRNA-seq) is increasingly accessible to researchers of many fields. However, interpreting its data demands proficiency in multiple programming languages and bioinformatic skills, which limited researchers, without such expertise, exploring information from scRNA-seq data. Therefore, there is a tremendous need to develop easy-to-use software, covering all the aspects of scRNA-seq data analysis. RESULTS: We proposed a clear analysis framework for scRNA-seq data, which emphasized the fundamental and crucial roles of cell identity annotation, abstracting the analysis process into three stages: upstream analysis, cell annotation and downstream analysis. The framework can equip researchers with a comprehensive understanding of the analysis procedure and facilitate effective data interpretation. Leveraging the developed framework, we engineered Shaoxia, an analysis platform designed to democratize scRNA-seq analysis by accelerating processing through high-performance computing capabilities and offering a user-friendly interface accessible even to wet-lab researchers without programming expertise. CONCLUSION: Shaoxia stands as a powerful and user-friendly open-source software for automated scRNA-seq analysis, offering comprehensive functionality for streamlined functional genomics studies. Shaoxia is freely accessible at http://www.shaoxia.cloud , and its source code is publicly available at https://github.com/WiedenWei/shaoxia .

OmicNavigator: open-source software for the exploration, visualization, and archival of omic studies.

BACKGROUND: The results of high-throughput biology ('omic') experiments provide insight into biological mechanisms but can be challenging to explore, archive and share. The scale of these challenges continues to grow as omic research volume expands and multiple analytical technologies, bioinformatic pipelines, and visualization preferences have emerged. Multiple software applications exist that support omic study exploration and/or archival. However, an opportunity remains for open-source software that can archive and present the results of omic analyses with broad accommodation of study-specific analytical approaches and visualizations with useful exploration features. RESULTS: We present OmicNavigator, an R package for the archival, visualization and interactive exploration of omic studies. OmicNavigator enables bioinformaticians to create web applications that interactively display their custom visualizations and analysis results linked with app-derived analytical tools, graphics, and tables. Studies created with OmicNavigator can be viewed within an interactive R session or hosted on a server for shared access. CONCLUSIONS: OmicNavigator can be found at https://github.com/abbvie-external/OmicNavigator.