Open-source Web Tool Research Articles

EndoGeneAnalyzer: A tool for selection and validation of reference genes.

The selection of proper reference genes is critical for accurate gene expression analysis in all fields of biological and medical research, mainly because there are many distinctions between different tissues and specimens. Given this variability, even in known classic reference genes, demands of a comprehensive analysis platform is needed to identify the most suitable genes for each study. For this purpose, we present an analysis tool for assisting in decision-making in the analysis of reverse transcription-quantitative polymerase chain reaction (RT-qPCR) data. EndoGeneAnalyzer, an open-source web tool for reference gene analysis in RT-qPCR studies, was used to compare the groups/conditions under investigation. This interactive application offers an easy-to-use interface that allows efficient exploration of datasets. Through statistical and stability analyses, EndoGeneAnalyzer assists in the select of the most appropriate reference gene or set of genes for each condition. It also allows researchers to identify and remove unwanted outliers. Moreover, EndoGeneAnalyzer provides a graphical interface to compare the evaluated groups, providing a visually informative differential analysis.

Plantorganelle Hunter is an effective deep-learning-based method for plant organelle phenotyping in electron microscopy.

Accurate delineation of plant cell organelles from electron microscope images is essential for understanding subcellular behaviour and function. Here we develop a deep-learning pipeline, called the organelle segmentation network (OrgSegNet), for pixel-wise segmentation to identify chloroplasts, mitochondria, nuclei and vacuoles. OrgSegNet was evaluated on a large manually annotated dataset collected from 19 plant species and achieved state-of-the-art segmentation performance. We defined three digital traits (shape complexity, electron density and cross-sectional area) to track the quantitative features of individual organelles in 2D images and released an open-source web tool called Plantorganelle Hunter for quantitatively profiling subcellular morphology. In addition, the automatic segmentation method was successfully applied to a serial-sectioning scanning microscope technique to create a 3D cell model that offers unique views of the morphology and distribution of these organelles. The functionalities of Plantorganelle Hunter can be easily operated, which will increase efficiency and productivity for the plant science community, and enhance understanding of subcellular biology.

Interpreting Image-based Profiles using Similarity Clustering and Single-Cell Visualization.

Image-based profiling quantitatively assesses the effects of perturbations on cells by capturing a breadth of changes via microscopy. Here, we provide two complementary protocols to help explore and interpret data from image-based profiling experiments. In the first protocol, we examine the similarity among perturbed cell samples using data from compounds that cluster by their mechanisms of action. The protocol includes steps to examine feature-driving differences between samples and to visualize correlations between features and treatments to create interpretable heatmaps using the open-source web tool Morpheus. In the second protocol, we show how to interactively explore images together with the numerical data, and we provide scripts to create visualizations of representative single cells and image sites to understand how changes in features are reflected in the images. Together, these two tutorials help researchers interpret image-based data to speed up research. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Exploratory analysis of profile similarities and driving features Basic Protocol 2: Image and single-cell visualization following profile interpretation.

Automated Inventory of Broadleaf Tree Plantations with UAS Imagery

With the increased availability of unmanned aerial systems (UAS) imagery, digitalized forest inventory has gained prominence in recent years. This paper presents a methodology for automated measurement of tree height and crown area in two broadleaf tree plantations of different species and ages using two different UAS platforms. Using structure from motion (SfM), we generated canopy height models (CHMs) for each broadleaf plantation in Indiana, USA. From the CHMs, we calculated individual tree parameters automatically through an open-source web tool developed using the Shiny R package and assessed the accuracy against field measurements. Our analysis shows higher tree measurement accuracy with the datasets derived from multi-rotor platform (M600) than with the fixed wing platform (Bramor). The results show that our automated method could identify individual trees (F-score > 90%) and tree biometrics (root mean square error < 1.2 m for height and <1 m2 for the crown area) with reasonably good accuracy. Moreover, our automated tool can efficiently calculate tree-level biometric estimations for 4600 trees within 30 min based on a CHM from UAS-SfM derived images. This automated UAS imagery approach for tree-level forest measurements will be beneficial to landowners and forest managers by streamlining their broadleaf forest measurement and monitoring effort.

On the Potential for Remote Observations of Coastal Morphodynamics from Surf-Cameras

Recreational surf-cameras (surfcams) are ubiquitous along many coastlines, and yet are a largely untapped source of coastal morphodynamic observations. Surfcams offer broad spatial coverage and flexibility in data collection, but a method to remotely acquire ground control points (GCPs) and initial camera parameter approximations is necessary to better leverage this existing infrastructure to make quantitative measurements. This study examines the efficacy of remotely monitoring coastal morphodynamics from surfcams at two sites on the Atlantic coast of Florida, U.S.A., by leveraging freely available airborne lidar observations to acquire remote-GCPs and open-source web tools for camera parameter approximations, ignoring lens distortion. Intrinsic and extrinsic camera parameters are determined using a modified space resection procedure, wherein parameters are determined using iterative adjustment while fitting to remote-GCPs and initial camera parameter approximations derived from justified assumptions and Google Earth. This procedure is completed using the open-source Surf-Camera Remote Calibration Tool (SurfRCaT). The results indicate root mean squared horizontal reprojection errors at the two cameras of 3.43 m and 6.48 m. Only immobile hard structures such as piers, jetties, and boulders are suitable as remote-GCPs, and the spatial distribution of available points is a likely reason for the higher accuracy at one camera relative to the other. Additionally, lens distortion is not considered in this work. This is another important source of error and including it in the methodology is highlighted as a useful avenue for future work. Additional factors, such as initial camera parameter approximation accuracy, likely play a role as well. This work illustrates that, provided there is sufficient remote-GCP availability and small lens distortion, remote video monitoring of coastal areas with existing surfcams could provide a usable source of coastal morphodynamic observations. This is further explored with a shoreline change analysis from the higher-accuracy camera. It was found that only the largest (>6 m) magnitude shoreline changes exceed the observational uncertainty driven by shoreline mapping error and reprojection error, indicating that remotely calibrated surfcams can provide observations of seasonal or storm-driven signals.

The Role and Views of Ophthalmologists During the COVID-19 Pandemic.

PurposeThe severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic forced ophthalmologists to adjust their working conditions to ensure patient and staff safety, while still providing effective and timely treatment. This international survey among ophthalmologists was initiated to capture what actions ophthalmologists were taking and what their opinions were on the risks of infection in their workplace, the delay in treatment, the use of telemedicine and telephone for appointments, and the regional specifications and measures implemented by the respective authorities.MethodsAn open-source web tool was used to develop an online survey, to which ophthalmologists worldwide were invited via e-mail using international mailing lists (Media Mice, Singapore; Texere Publishing Inc, USA; CGO Gerling) and incentivized using a lottery. The physicians provided their level of agreement relating to the offered statements and gave free answers to the questions regarding the actions taken (conducted November 5th 2020 to December 20th 2020).ResultsAfter 91,000 invitations, responses were collected from 1122 ophthalmologists. Despite the use of large international mailing lists, mainly doctors from Europe participated. Half of the participants expressed great concern about possible SARS-CoV-2 infection in their patients. A significant number of younger ophthalmologists (≤50 years: 76.9%, n = 313; >50 years: 69.6%, n = 181) feared the delays that COVID-19 could cause to treatment. Reductions in patient numbers were broadly observed, with more ophthalmologists of younger age reporting greater declines. Nearly all ophthalmologists indicated that they provided disinfectant and the majority also used masks and questionnaires for screening. For 60.3% (n = 412) of ophthalmologists, telephone calls reduced the risk of ‘no-shows’; 71.6% (n = 497) disagreed that telemedical evaluation is possible without slit lamp findings and fundus photos; and 57.0% of participants felt content with the governmental measures during the COVID-19 pandemic.ConclusionThe COVID-19 pandemic has significantly influenced the work of ophthalmologists. Based on the limited response rate, certain statements were only possible to evaluate for the European Union: with a noticeable reduction in patient numbers, delay in treatment was a major worry. Measures to protect and reassure patients should be undertaken, especially regarding those with vision-threatening diseases requiring treatment.

The Usability Testing of SSAAT, a Bioinformatic Web Application for DNA Analysis at a Nucleotide Level

Sanger sequencing remains the cornerstone method for Deoxyribonucleic Acid (DNA) sequencing due to its high accuracy in targeting smaller genomic regions in a larger number of samples. The analysis of Sanger sequence DNA data requires powerful and intelligent software tools. Most of the preferred tools are proprietary licensed tools that offer a user-friendly interface and have many features, however, their affordability, especially to individual scientists or students, is limited. On the other hand, a few free and open-source licensed tools are available but have limited features. This study focuses on the usability testing of the developed Sanger Sequence Automatic Analysis Tool (SSAAT), a free and open-source web tool for Sanger sequence analysis. Usability tests were conducted with potential users and the results demonstrate that the participants were able to use the tool easily and accomplish the test tasks at the given time. Moreover, the participants were excited with the easy-to-use interface and agreed that most users could use the tool with no need for technical assistance. However, the participants also identified some issues that require more development effort.

WebFRIS: An efficient web-based decision support tool to disseminate end-to-end risk information for flood management

The present study describes the development of a web-based flood risk information system ‘WebFRIS’ for Jagatsinghpur district, a severely flood-prone region in Eastern India. The WebFRIS is designed by using various readily available open-source web tools and packages such as Google Map, PHP, MySQL, and JSON. Special emphasis is directed towards designing the layout and architecture, to be easily accessible by any end-user irrespective of any technical know-how. The WebFRIS illustrates spatial maps of flood hazard, socio-economic vulnerability, and flood risk at the village level for two-time scenarios. While analyzing a set of graphical statistics depicting the changes in flood risk components, a significant increase in high and very-high categories of both flood hazard (~140%) and socio-economically vulnerable villages (~68%) is noticed during Scenario-I. The number of villages facing compound risk (contributed equally by flood hazard and socio-economic vulnerability) nearly doubled in Scenario-I. A spatial analysis of diametric changes in flood risk shows that a large proportion of villages in Balikuda, Ersama, and Tirtol tehsils have undergone radical changes. Following these observations, a set of possible engineering, social, and policy measures are proposed, whose implementation in the near future is expected to reinforce flood management in the study area. The WebFRIS architecture is flexible, easy-to-use; it is expected to provide crucial lessons to the local bodies, town-planners, water professionals, flood experts, and also the citizens, a precious knowledge on flood risk management. The WebFRIS may be considered as a precious cartographic product for environmental management. The proposed web platform is generic, as it can be applied to study other inter-related systems such as environmental protection, land-use planning, coastal habitat restoration, and community resilience building.Software and data availabilityName: Web Flood Risk Information System -WebFRISDeveloper: Indian Institute of Technology Bombay, MumbaiContact Information: (1) Mohit P. Mohanty: mohit2012.env@gmail.com; Environmental Science and Engineering Department, Indian Institute of Technology Bombay, India, and (2) Subhankar Karmakar: skarmakar@iitb.ac.in; Environmental Science and Engineering Department (http://www.esed.iitb.ac.in/), Indian Institute of Technology Bombay, India.Software(s) required: Internet browser (latest versions are recommended), and MIKE FLOOD 2018 or higher (https://www.mikepoweredbydhi.com/products/mike-flood).Programming languages: HTML, PhP, MySQL, JSONAvailability and cost: Any user can access WebFRIS for no cost at https://webfrisiitb.com/. The login credentials for entering WebFRIS are available with reasonable requests to the authors. The flood model set-up and input data are not available freely due to data confidentiality.

Coastal Analyst System from Space Imagery Engine (CASSIE): Shoreline management module

CASSIE is an open-source web tool for automatic shoreline mapping and analysis using satellite imagery (www.cassiengine.com). This tool was built in JavaScript, using Google Earth Engine (GEE) API, and can be applied to any coastal region on Earth where a boundary between water and land exists. CASSIE use the Landsat and Sentinel-2 satellite imagery, freely available from GEE, and implements an automatic shoreline detection using the normalized difference water index (NDWI) together with Otsu image segmentation algorithm. The satellite-derived shorelines are analysed for a set of user-defined cross-shore transects along which several statistical analyses are performed. Comparisons of the CASSIE-derived shorelines and rate of changes with state-of-the art methods show that the products from this tool have sub-pixel accuracy. The new concept of big-data cloud-based computing and storage platform (GEE), together with a user-friendly interface and high level of automation makes of CASSIE a complete tool to support a wide variety of studies and applications where the knowledge of the shoreline behaviour is fundamental.

VolcaNoseR is a web app for creating, exploring, labeling and sharing volcano plots

Comparative genome- and proteome-wide screens yield large amounts of data. To efficiently present such datasets and to simplify the identification of hits, the results are often presented in a type of scatterplot known as a volcano plot, which shows a measure of effect size versus a measure of significance. The data points with the largest effect size and a statistical significance beyond a user-defined threshold are considered as hits. Such hits are usually annotated in the plot by a label with their name. Volcano plots can represent ten thousands of data points, of which typically only a handful is annotated. The information of data that is not annotated is hardly or not accessible. To simplify access to the data and enable its re-use, we have developed an open source and online web tool with R/Shiny. The web app is named VolcaNoseR and it can be used to create, explore, label and share volcano plots (https://huygens.science.uva.nl/VolcaNoseR). When the data is stored in an online data repository, the web app can retrieve that data together with user-defined settings to generate a customized, interactive volcano plot. Users can interact with the data, adjust the plot and share their modified plot together with the underlying data. Therefore, VolcaNoseR increases the transparency and re-use of large comparative genome- and proteome-wide datasets.

BIAFLOWS: A Collaborative Framework to Reproducibly Deploy and Benchmark Bioimage Analysis Workflows

SummaryImage analysis is key to extracting quantitative information from scientific microscopy images, but the methods involved are now often so refined that they can no longer be unambiguously described by written protocols. We introduce BIAFLOWS, an open-source web tool enabling to reproducibly deploy and benchmark bioimage analysis workflows coming from any software ecosystem. A curated instance of BIAFLOWS populated with 34 image analysis workflows and 15 microscopy image datasets recapitulating common bioimage analysis problems is available online. The workflows can be launched and assessed remotely by comparing their performance visually and according to standard benchmark metrics. We illustrated these features by comparing seven nuclei segmentation workflows, including deep-learning methods. BIAFLOWS enables to benchmark and share bioimage analysis workflows, hence safeguarding research results and promoting high-quality standards in image analysis. The platform is thoroughly documented and ready to gather annotated microscopy datasets and workflows contributed by the bioimaging community.

Consensus Finder web tool to predict stabilizing substitutions in proteins.

The consensus sequence approach to predicting stabilizing substitutions in proteins rests on the notion that conserved amino acids are more likely to contribute to the stability of a protein fold than non-conserved amino acids. To implement a prediction for a target protein sequence, one finds homologous sequences and aligns them in a multiple sequence alignment. The sequence of the most frequently occurring amino acid at each position is the consensus sequence. Replacement of a rarely occurring amino acid in the target with a frequently occurring amino acid from the consensus sequence is predicted to be stabilizing. Consensus Finder is an open-source web tool that automates this prediction. This chapter reviews the rationale for the consensus sequence approach and explains the options for fine-tuning this approach using Staphylococcus nuclease A as an example.

Genepanel.iobio - an easy to use web tool for generating disease- and phenotype-associated gene lists

When ordering genetic testing or triaging candidate variants in exome and genome sequencing studies, it is critical to generate and test a comprehensive list of candidate genes that succinctly describe the complete and objective phenotypic features of disease. Significant efforts have been made to curate gene:disease associations both in academic research and commercial genetic testing laboratory settings. However, many of these valuable resources exist as islands and must be used independently, generating static, single-resource gene:disease association lists. Here we describe genepanel.iobio (https://genepanel.iobio.io) an easy to use, free and open-source web tool for generating disease- and phenotype-associated gene lists from multiple gene:disease association resources, including the NCBI Genetic Testing Registry (GTR), Phenolyzer, and the Human Phenotype Ontology (HPO). We demonstrate the utility of genepanel.iobio by applying it to complex, rare and undiagnosed disease cases that had reached a diagnostic conclusion. We find that genepanel.iobio is able to correctly prioritize the gene containing the diagnostic variant in roughly half of these challenging cases. Importantly, each component resource contributed diagnostic value, showing the benefits of this aggregate approach. We expect genepanel.iobio will improve the ease and diagnostic value of generating gene:disease association lists for genetic test ordering and whole genome or exome sequencing variant prioritization.

Interactive visual analysis of drug-target interaction networks using Drug Target Profiler, with applications to precision medicine and drug repurposing.

Knowledge of the full target space of drugs (or drug-like compounds) provides important insights into the potential therapeutic use of the agents to modulate or avoid their various on- and off-targets in drug discovery and precision medicine. However, there is a lack of consolidated databases and associated data exploration tools that allow for systematic profiling of drug target-binding potencies of both approved and investigational agents using a network-centric approach. We recently initiated a community-driven platform, Drug Target Commons (DTC), which is an open-data crowdsourcing platform designed to improve the management, reproducibility and extended use of compound-target bioactivity data for drug discovery and repurposing, as well as target identification applications. In this work, we demonstrate an integrated use of the rich bioactivity data from DTC and related drug databases using Drug Target Profiler (DTP), an open-source software and web tool for interactive exploration of drug-target interaction networks. DTP was designed for network-centric modeling of mode-of-action of multi-targeting anticancer compounds, especially for precision oncology applications. DTP enables users to construct an interaction network based on integrated bioactivity data across selected chemical compounds and their protein targets, further customizable using various visualization and filtering options, as well as cross-links to several drug and protein databases to provide comprehensive information of the network nodes and interactions. We demonstrate here the operation of the DTP tool and its unique features by several use cases related to both drug discovery and drug repurposing applications, using examples of anticancer drugs with shared target profiles. DTP is freely accessible at http://drugtargetprofiler.fimm.fi/.

FuncExplorer: a tool for fast data-driven functional characterisation of high-throughput expression data

BackgroundA widely applied approach to extract knowledge from high-throughput genomic data is clustering of gene expression profiles followed by functional enrichment analysis. This type of analysis, when done manually, is highly subjective and has limited reproducibility. Moreover, this pipeline can be very time-consuming and resource-demanding as enrichment analysis is done for tens to hundreds of clusters at a time. Thus, the task often needs programming skills to form a pipeline of different software tools or R packages to enable an automated approach. Furthermore, visualising the results can be challenging.ResultsWe developed a web tool, funcExplorer, which automatically combines hierarchical clustering and enrichment analysis to detect functionally related gene clusters. The functional characterisation is achieved using structured knowledge from data sources such as Gene Ontology, KEGG and Reactome pathways, Human Protein Atlas, and Human Phenotype Ontology. funcExplorer includes various measures for finding biologically meaningful clusters, provides a modern graphical user interface, and has wide-ranging data export and sharing options as well as software transparency by open-source code. The results are presented in a visually compact and interactive format, enabling users to explore the biological essence of the data. We compared our results with previously published gene clusters to demonstrate that funcExplorer can perform the data characterisation equally well, but without requiring labour-intensive manual interference.ConclusionsThe open-source web tool funcExplorer enables scientists with high-throughput genomic data to obtain a preliminary interactive overview of the expression patterns, gene names, and shared functionalities in their dataset in a visually pleasing format. funcExplorer is publicly available at https://biit.cs.ut.ee/funcexplorer

Making Open Data Work for Civic Advocacy

The value of data in supporting citizen participation in processes of place-making and community building is widely recognised. While the open data movement now permits citizens to acquire governmental data relating to their communities, little to no effort is made to ensure that these datasets are accessible and interpretable by non-professionals. Through a series of community engagements spanning an 18-month period, we co-designed Data:In Place, an open source web tool which supports citizens in accessing, interpreting and making sense of open data. Leveraging visual map-based querying, citizens can access official statistics about their community, interrogate the data, and map their own data sources to create data visualisations. Reflecting on the participatory design process and the designed technology, we provide a framing to make open data work for civic advocacy.

Why Jupyter is data scientists' computational notebook of choice.

An improved architecture and enthusiastic user base are driving uptake of the open-source web tool. An improved architecture and enthusiastic user base are driving uptake of the open-source web tool.

CrossCheck: an open-source web tool for high-throughput screen data analysis

Modern high-throughput screening methods allow researchers to generate large datasets that potentially contain important biological information. However, oftentimes, picking relevant hits from such screens and generating testable hypotheses requires training in bioinformatics and the skills to efficiently perform database mining. There are currently no tools available to general public that allow users to cross-reference their screen datasets with published screen datasets. To this end, we developed CrossCheck, an online platform for high-throughput screen data analysis. CrossCheck is a centralized database that allows effortless comparison of the user-entered list of gene symbols with 16,231 published datasets. These datasets include published data from genome-wide RNAi and CRISPR screens, interactome proteomics and phosphoproteomics screens, cancer mutation databases, low-throughput studies of major cell signaling mediators, such as kinases, E3 ubiquitin ligases and phosphatases, and gene ontological information. Moreover, CrossCheck includes a novel database of predicted protein kinase substrates, which was developed using proteome-wide consensus motif searches. CrossCheck dramatically simplifies high-throughput screen data analysis and enables researchers to dig deep into the published literature and streamline data-driven hypothesis generation. CrossCheck is freely accessible as a web-based application at http://proteinguru.com/crosscheck.

Mendel,MD: A user-friendly open-source web tool for analyzing WES and WGS in the diagnosis of patients with Mendelian disorders.

Whole exome and whole genome sequencing have both become widely adopted methods for investigating and diagnosing human Mendelian disorders. As pangenomic agnostic tests, they are capable of more accurate and agile diagnosis compared to traditional sequencing methods. This article describes new software called Mendel,MD, which combines multiple types of filter options and makes use of regularly updated databases to facilitate exome and genome annotation, the filtering process and the selection of candidate genes and variants for experimental validation and possible diagnosis. This tool offers a user-friendly interface, and leads clinicians through simple steps by limiting the number of candidates to achieve a final diagnosis of a medical genetics case. A useful innovation is the “1-click” method, which enables listing all the relevant variants in genes present at OMIM for perusal by clinicians. Mendel,MD was experimentally validated using clinical cases from the literature and was tested by students at the Universidade Federal de Minas Gerais, at GENE–Núcleo de Genética Médica in Brazil and at the Children’s University Hospital in Dublin, Ireland. We show in this article how it can simplify and increase the speed of identifying the culprit mutation in each of the clinical cases that were received for further investigation. Mendel,MD proved to be a reliable web-based tool, being open-source and time efficient for identifying the culprit mutation in different clinical cases of patients with Mendelian Disorders. It is also freely accessible for academic users on the following URL: https://mendelmd.org.

An offline–online Web-GIS Android application for fast data acquisition of landslide hazard and risk

Abstract. Regional landslide assessments and mapping have been effectively pursued by research institutions, national and local governments, non-governmental organizations (NGOs), and different stakeholders for some time, and a wide range of methodologies and technologies have consequently been proposed. Land-use mapping and hazard event inventories are mostly created by remote-sensing data, subject to difficulties, such as accessibility and terrain, which need to be overcome. Likewise, landslide data acquisition for the field navigation can magnify the accuracy of databases and analysis. Open-source Web and mobile GIS tools can be used for improved ground-truthing of critical areas to improve the analysis of hazard patterns and triggering factors. This paper reviews the implementation and selected results of a secure mobile-map application called ROOMA (Rapid Offline–Online Mapping Application) for the rapid data collection of landslide hazard and risk. This prototype assists the quick creation of landslide inventory maps (LIMs) by collecting information on the type, feature, volume, date, and patterns of landslides using open-source Web-GIS technologies such as Leaflet maps, Cordova, GeoServer, PostgreSQL as the real DBMS (database management system), and PostGIS as its plug-in for spatial database management. This application comprises Leaflet maps coupled with satellite images as a base layer, drawing tools, geolocation (using GPS and the Internet), photo mapping, and event clustering. All the features and information are recorded into a GeoJSON text file in an offline version (Android) and subsequently uploaded to the online mode (using all browsers) with the availability of Internet. Finally, the events can be accessed and edited after approval by an administrator and then be visualized by the general public.