scholarly journals metaCOVID: An R-Shiny application for living meta-analyses of COVID-19 trials

2021 ◽  
Author(s):  
Theodoros Evrenoglou ◽  
Isabelle Boutron ◽  
Anna Chaimani
Keyword(s):  
Evidence Synthesis ◽  
Source Code ◽  
Decision Makers ◽  
Sensitivity Analyses ◽  
Preventive Interventions ◽  
Primary Interest ◽  
Link Type ◽  
R Shiny ◽  
Meta Analyses ◽  
Shiny Application

Abstract“Living” evidence synthesis is of primary interest for decision-makers to overcome the COVID-19 pandemic. The COVID-NMA provides open-access living meta-analyses assessing different therapeutic and preventive interventions. Data are posted on a platform (https://covid-nma.com/) and analyses are updated every week. However, guideline developers and other stakeholders also need to investigate the data and perform their own analyses. This requires resources, time, statistical expertise, and software knowledge. To assist them, we created the “metaCOVID” application which, based on automation processes, facilitates the fast exploration of the data and the conduct of analyses tailored to end-users needs. metaCOVID has been created in R and is freely available as an R-Shiny application. The application conducts living meta-analyses for every outcome. Several options are available for subgroup and sensitivity analyses. The results are presented in downloadable forest plots. metaCOVID is freely available from https://covid-nma.com/metacovid/ and the source code from https://github.com/TEvrenoglou/metaCovid.

scholarly journals Single Cell Viewer (SCV): An interactive visualization data portal for single cell RNA sequence data

2019 ◽  
Author(s):  
Shuoguo Wang ◽  
Constance Brett ◽  
Mohan Bolisetty ◽  
Ryan Golhar ◽  
Isaac Neuhaus ◽  
...  
Keyword(s):  
Single Cell ◽  
Sequence Data ◽  
Single Cells ◽  
Link Type ◽  
Technological Advances ◽  
R Shiny ◽  
Data Volume ◽  
Exploratory Data ◽  
Cell Data ◽  
Shiny Application

AbstractMotivationThanks to technological advances made in the last few years, we are now able to study transcriptomes from thousands of single cells. These have been applied widely to study various aspects of Biology. Nevertheless, comprehending and inferring meaningful biological insights from these large datasets is still a challenge. Although tools are being developed to deal with the data complexity and data volume, we do not have yet an effective visualizations and comparative analysis tools to realize the full value of these datasets.ResultsIn order to address this gap, we implemented a single cell data visualization portal called Single Cell Viewer (SCV). SCV is an R shiny application that offers users rich visualization and exploratory data analysis options for single cell datasets.AvailabilitySource code for the application is available online at GitHub (http://www.github.com/neuhausi/single-cell-viewer) and there is a hosted exploration application using the same example dataset as this publication at http://periscopeapps.org/[email protected]; [email protected]

scholarly journals Ten simple rules for conducting umbrella reviews

2018 ◽  
Vol 21 (3) ◽  
pp. 95-100 ◽  
Author(s):  
Paolo Fusar-Poli ◽  
Joaquim Radua
Keyword(s):  
Systematic Reviews ◽  
Evidence Synthesis ◽  
Biomedical Literature ◽  
Sensitivity Analyses ◽  
Basic Unit ◽  
Policy Makers ◽  
Common Effect ◽  
Key Points ◽  
Practical Guidance ◽  
Meta Analyses

ObjectiveEvidence syntheses such as systematic reviews and meta-analyses provide a rigorous and transparent knowledge base for translating clinical research into decisions, and thus they represent the basic unit of knowledge in medicine. Umbrella reviews are reviews of previously published systematic reviews or meta-analyses. Therefore, they represent one of the highest levels of evidence synthesis currently available, and are becoming increasingly influential in biomedical literature. However, practical guidance on how to conduct umbrella reviews is relatively limited.MethodsWe present a critical educational review of published umbrella reviews, focusing on the essential practical steps required to produce robust umbrella reviews in the medical field.ResultsThe current manuscript discusses 10 key points to consider for conducting robust umbrella reviews. The points are: ensure that the umbrella review is really needed, prespecify the protocol, clearly define the variables of interest, estimate a common effect size, report the heterogeneity and potential biases, perform a stratification of the evidence, conduct sensitivity analyses, report transparent results, use appropriate software and acknowledge the limitations. We illustrate these points through recent examples from umbrella reviews and suggest specific practical recommendations.ConclusionsThe current manuscript provides a practical guidance for conducting umbrella reviews in medical areas. Researchers, clinicians and policy makers might use the key points illustrated here to inform the planning, conduction and reporting of umbrella reviews in medicine.

scholarly journals Matchathon: A guide to student-faculty connections in PhD programs

2020 ◽  
Author(s):  
Haley Amemiya ◽  
Zena Lapp ◽  
Cathy Smith ◽  
Margaret Durdan ◽  
Michelle DiMondo ◽  
...  
Keyword(s):  
Open Source ◽  
Source Code ◽  
Faculty Members ◽  
Retention Rates ◽  
Link Type ◽  
Shiny App ◽  
R Shiny ◽  
Web App ◽  
Phd Programs ◽  
The Web

AbstractRelevant and impactful mentors are essential to a graduate student’s career. Finding mentors can be challenging in umbrella programs with hundreds of faculty members. To foster connections between potential mentors and students with similar research interests, we created a Matchathon event, which has successfully enabled students to find mentors. We developed an easy-to-use R Shiny app (https://github.com/UM-OGPS/matchathon/) to facilitate matching and organizing the event that can be used at any institution. It is our hope that this resource will improve the environment and retention rates for students in the academy.The open source app is publicly available on the web (app: https://UM-OGPS.shinyapps.io/matchathon/; source code: https://github.com/UM-OGPS/matchathon/).

scholarly journals UROPA GUI: A web platform for genomic region annotation

2018 ◽  
Author(s):  
Hendrik Schultheis ◽  
Jens Preussner ◽  
Annika Fust ◽  
Mette Bentsen ◽  
Carsten Kuenne ◽  
...  
Keyword(s):  
Graphical User Interface ◽  
Bioinformatics Analysis ◽  
Source Code ◽  
Genomic Region ◽  
Command Line ◽  
Web Based ◽  
Link Type ◽  
R Shiny ◽  
Considerable Impact ◽  
Web Platform

AbstractThe annotation of genomic ranges such as peaks resulting from ChIP-seq/ATAC-seq or other techniques represents a fundamental task of bioinformatics analysis with considerable impact on many downstream analyses. In our previous work, we introduced the Universal Robust Peak Annotator (UROPA), a flexible command line based tool which improves upon the functionality of existing annotation software. In order to reduce the complexity for biologists and clinicians, we have implemented an intuitive web-based graphical user interface (GUI) and fully functional service platform for UROPA. This extension will empower all users to generate annotations for regions of interest interactively.Availability and ImplementationThe open source UROPA GUI server was implemented in R Shiny and Python and is available from http://loosolab.mpi-bn.mpg.de. The source code of our App can be downloaded at https://github.molgen.mpg.de/loosolab/UROPA_GUI under the MIT license.

VP04 The Influence Of Sponsorship On The Treatment Effects Of Trials

2019 ◽  
Vol 35 (S1) ◽  
pp. 76-76
Author(s):  
Chiara Arienti ◽  
Negrini Stefano ◽  
Bruno Da costa ◽  
Susan Armijo-Olivo
Keyword(s):  
Effect Size ◽  
Treatment Effects ◽  
Conflicts Of Interest ◽  
Data Extraction ◽  
Research Process ◽  
Decision Makers ◽  
Sensitivity Analyses ◽  
Significant Difference ◽  
Public Money ◽  
Meta Analyses

IntroductionLimited public money is available for funding research and the majority of clinical research undertaken is funded by industry. Mechanisms to regulate conflicts of interest within the research process have been implemented. However, these policies by themselves do not protect against potential sponsorship bias that would affect research results to inform decision makers when using the results of these trials. Therefore, the main aim of this study was to evaluate the influence of sponsorship bias on the treatment effects of RCTs.MethodsThis was a meta-epidemiological study. A random sample of RCTs included in meta-analyses of physical therapy (PT) area were identified. Data extraction including assessments of appropriate influence of funders was conducted independently by two reviewers. To determine the association between biases related to sponsorship biases and effect sizes, a two-level analysis was conducted using a meta-meta-analytic approach.ResultsWe analysed 393 trials included in forty-three meta-analyses. The most common sources of sponsorship for this sample of PT trials were government (n = 205, 52.16 percent) followed by academic (n = 44, 11.2 percent), and industry (n = 39, 10 percent). The funding was not declared in a high percentage of the trials (n = 85, 22 percent). The influence of the trial sponsor was assessed as being appropriate in 246 trials (63 percent) and considered inappropriate/unclear in 147 (37 percent) of them. There was a significant difference in effects estimates between trials with appropriate and inappropriate influence of funders (ES= 0.15; 95% CI -0.03, 0.33;). Trials with inappropriate/unclear influence of funders tended to have on average a larger effect size than those with appropriate influence of fundingConclusionsTreatment effect size estimates were 0.15 larger in trials with lack of appropriate influence of funders. Systematic reviewers should perform sensitivity analyses based on appropriateness of influence of sponsorship in included trials.

scholarly journals DrawAlignR: An interactive tool for across run chromatogram alignment visualization

2020 ◽  
Author(s):  
Shubham Gupta ◽  
Justin Sing ◽  
Arshia Mahmoodi ◽  
Hannes Röst
Keyword(s):  
Open Source ◽  
Web Application ◽  
Source Code ◽  
Link Type ◽  
Interactive Tool ◽  
Cumulative Score ◽  
Alignment Algorithms ◽  
R Shiny ◽  
Software Platforms

AbstractMulti-run alignment is widely used in proteomics to establish analyte correspondence across runs. Generally alignment algorithms return a cumulative score, which may not be easily interpretable for each peptide. Here we present a novel tool, DrawAlignR, to visualize each chromatographic alignment for DIA/SWATH data. Furthermore, we have developed a novel C++ based implementation of raw chromatogram alignment which is 35 times faster than the previously published algorithm. This not only enables users to plot alignment interactively by DrawAlignR, but also allows other software platforms to use the algorithm. DrawAlignR is an open-source web application using R Shiny that can be hosted using the source-code available at https://github.com/Roestlab/DrawAlignR.

scholarly journals Chainchecker: An application to visualise and explore transmission chains for Ebola virus disease

PLoS ONE ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. e0247002
Author(s):  
Katy Gaythorpe ◽  
Aaron Morris ◽  
Natsuko Imai ◽  
Miles Stewart ◽  
Jeffrey Freeman ◽  
...  
Keyword(s):  
Ebola Virus ◽  
Virus Disease ◽  
Data Entry ◽  
Hemorrhagic Fever ◽  
Ebola Virus Disease ◽  
Viral Hemorrhagic Fever ◽  
Link Type ◽  
R Shiny ◽  
Exposure Windows ◽  
Shiny Application

2020 saw the continuation of the second largest outbreak of Ebola virus disease (EVD) in history. Determining epidemiological links between cases is a key part of outbreak control. However, due to the large quantity of data and subsequent data entry errors, inconsistencies in potential epidemiological links are difficult to identify. We present chainchecker, an online and offline shiny application which visualises, curates and verifies transmission chain data. The application includes the calculation of exposure windows for individual cases of EVD based on user defined incubation periods and user specified symptom profiles. It has an upload function for viral hemorrhagic fever data and utility for additional entries. This data may then be visualised as a transmission tree with inconsistent links highlighted. Finally, there is utility for cluster analysis and the ability to highlight nosocomial transmission. chainchecker is a R shiny application which has an offline version for use with VHF (viral hemorrhagic fever) databases or linelists. The software is available at https://shiny.dide.imperial.ac.uk/chainchecker which is a web-based application that links to the desktop application available for download and the github repository, https://github.com/imperialebola2018/chainchecker.

scholarly journals FlexDotPlot: a universal and modular dot plot visualization tool for complex multifaceted data

2020 ◽  
Author(s):  
Simon Leonard ◽  
Antoine Rolland ◽  
Karin Tarte ◽  
Frédéric Chalmel ◽  
Aurélie Lardenois
Keyword(s):  
Single Cell ◽  
Source Code ◽  
R Package ◽  
Quantitative Information ◽  
Visualization Tool ◽  
Visualization Method ◽  
Rna Seq ◽  
Shiny App ◽  
R Shiny ◽  
Shiny Application

AbstractMotivationDot plots are heatmap-like charts that provide a compact way to simultaneously display two quantitative information by means of dots of different sizes and colours. Despite the popularity of this visualization method, particularly in single-cell RNA-seq studies, existing tools used to make dot plots are limited in terms of functionality and usability.ResultsWe developed FlexDotPlot, an R package for generating dot plots from any type of multifaceted data, including single-cell RNA-seq data. FlexDotPlot provides a universal and easy-to-use solution with a high versatility. An interactive R Shiny application is also available in the FlexDotPlot package allowing non-R users to easily generate dot plots with several tunable parameters.Availability and implementationSource code and detailed manual are available at https://github.com/Simon-Leonard/FlexDotPlot. The Shiny app is available as a stand-alone application within the package.

scholarly journals The development of a faecal incontinence core outcome set: an international Delphi study protocol

2021 ◽  
Vol 36 (3) ◽  
pp. 617-622
Author(s):  
Sadé Assmann ◽  
Daniel Keszthelyi ◽  
Jos Kleijnen ◽  
Merel Kimman ◽  
Foteini Anastasiou ◽  
...  
Keyword(s):  
Systematic Review ◽  
Study Protocol ◽  
Faecal Incontinence ◽  
Delphi Study ◽  
Evidence Synthesis ◽  
Core Outcome Set ◽  
Core Outcome ◽  
Delphi Consensus ◽  
Link Type ◽  
Outcome Set

Abstract Purpose Faecal incontinence (FI) is estimated to affect around 7.7% of people. There is a lack of uniformity in outcome definitions, measurement and reporting in FI studies. Until now, there is no general consensus on which outcomes should be assessed and reported in FI research. This complicates comparison between studies and evidence synthesis, potentially leading to recommendations not evidence-based enough to guide physicians in selecting an FI therapy. A solution for this lack of uniformity in reporting of outcomes is the development of a Core Outcome Set (COS) for FI. This paper describes the protocol for the development of a European COS for FI. Methods Patient interviews and a systematic review of the literature will be performed to identify patient-, physician- and researcher-oriented outcomes. The outcomes will be categorised using the COMET taxonomy and put forward to a group of patients, physicians (i.e. colorectal surgeons, gastroenterologists and general practitioners) and researchers in a Delphi consensus exercise. This exercise will consist of up to three web-based rounds in which participants will prioritise and condense the list of outcomes, which is expected to result in consensus. A consensus meeting with participants from all stakeholder groups will take place to reach a final agreement on the COS. Discussion This study protocol describes the development of a European COS to improve reliability and consistency of outcome reporting in FI studies, thereby improving evidence synthesis and patient care. Trial registration This project has been registered in the COMET database on the 1st of April 2020, available at http://www.comet-initiative.org/Studies/Details/1554. The systematic review has been registered on the PROSPERO database on the 31st of August 2020, available at https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=202020&VersionID=1381336.

scholarly journals Creation of a database to assess effects of omega-3, omega-6 and total polyunsaturated fats on health: methodology for a set of systematic reviews

BMJ Open ◽  
2019 ◽  
Vol 9 (5) ◽  
pp. e029554 ◽  
Author(s):  
Lee Hooper ◽  
Asmaa Abdelhamid ◽  
Julii Brainard ◽  
Katherine H O Deane ◽  
Fujian Song
Keyword(s):  
Health Outcomes ◽  
Systematic Reviews ◽  
Sensitivity Analyses ◽  
Omega 3 ◽  
Alpha Linolenic Acid ◽  
Trial Duration ◽  
Omega 6 ◽  
3 Omega ◽  
Meta Analyses ◽  
Total Pufa

ObjectiveTo create a database of long-term randomised controlled trials (RCTs) comparing higher with lower omega-3, omega-6 or total polyunsaturated fatty acid (PUFA), regardless of reported outcomes, and to develop methods to assess effects of increasing omega-6, alpha-linolenic acid (ALA), long-chain omega-3 (LCn3) and total PUFA on health outcomes.DesignSystematic review search, methodology and meta-analyses.Data sourcesMedline, Embase, CENTRAL, WHO International Clinical Trials Registry Platform, Clinicaltrials.gov and trials in relevant systematic reviews.Eligibility criteriaRCTs of ≥24 weeks' duration assessing effects of increasing ALA, LCn3, omega-6 or total PUFAs, regardless of outcomes reported.Data synthesisMethods included random-effects meta-analyses and sensitivity analyses. Funnel plots were examined, and subgrouping assessed effects of intervention type, replacement, baseline diabetes risk and use of diabetic medications, trial duration and dose. Quality of evidence was assessed using Grading of Recommendations Assessment, Development and Evaluation (GRADE).ResultsElectronic searches generated 37 810 hits, de-duplicated to 19 772 titles and abstracts. We assessed 2155 full-text papers, conference abstracts and trials registry entries independently in duplicate. Included studies were grouped into 363 RCTs comparing higher with lower omega-3, omega-6 and/or total PUFA intake of at least 6 months’ duration—the Database.Of these 363 included RCTs, 216 RCTs were included in at least one of our reviews of health outcomes, data extracted and risk of bias assessed in duplicate. Ninety five RCTs were included in the Database but not included in our current reviews. Of these 311 completed trials, 27 altered ALA intake, 221 altered LCn3 intake and 16 trials altered omega-3 intake without specifying whether ALA or LCn3. Forty one trials altered omega-6 and 59 total PUFA.The remaining 52 trials are ongoing though 13 (25%) appear to be outstanding, or constitute missing data.ConclusionsThis extensive database of trials is available to allow assessment of further health outcomes.

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