Welcome to X-META Online Analysis Platform



This platform is an interactive toolbox for meta-analysis. It allows you to use meta-analysis methods written in R programming language to get statistical results from your data. Click on either of the tabs on the side bar to access the corresponding Online Analysis platform or keep scrolling to learn more about how to use the tool and get started.


Here is the pipeline diagram for the platform:

xmeta-flowchart

How to use our ONLINE ANALYSIS platform?


I: Using Our Sample Data

1. Before uploading your own data, you can download our sample datasets to explore the functions of our platform.


UMA:

Univariate Meta-analysis with Continuous Outcomes: sample dataset

Univariate Meta-analysis with Binary Outcomes: sample dataset

Univariate Meta-analysis with Survival Outcomes: under construction


MMA:

Multivariate Meta-analysis with Continuous Outcomes: under construction

Multivariate Meta-analysis with Binary Outcomes: under construction

Multivariate Meta-analysis with Survival Outcomes: under construction


NMA:

Network Meta-analysis with Continuous Outcomes: sample dataset

Network Meta-analysis with Binary Outcomes: under construction

Network Meta-analysis with Survival Outcomes: under construction


2. Once you have the CSV file on your laptop, choose the corresponding method of meta-analysis you would like to conduct. In this example, we selected univariate meta-analysis and reached the following website:

3. Click the 'Browse' button and keep 'Header' checked. Upload 'dataset_umeta.csv'. Once the file is uploaded, the system will automatically display the following screen:

4. On the right side bar, you will see the outputs of the Online Analysis, including various plots and other results. You can also download the analysis report in PDF.


II: Get Started: Using Your Own Data

1. Our online platform requires a fixed format of Excel files. Results cannot be presented if a file with different formatting is uploaded. Please download the following templates and fill them in your own data:


UMA:

Univariate Meta-analysis with Continuous Outcomes: sample template

Univariate Meta-analysis with Binary Outcomes: under construction

Univariate Meta-analysis with Survival Outcomes: under construction


MMA:

Multivariate Meta-analysis with Continuous Outcomes: under construction

Multivariate Meta-analysis with Binary Outcomes: under construction

Multivariate Meta-analysis with Survival Outcomes: under construction


NMA:

Network Meta-analysis with Continuous Outcomes: sample template

Network Meta-analysis with Binary Outcomes: under construction

Network Meta-analysis with Survival Outcomes: under construction


2. Repeat step 2,3,4 from the Tutorial above.

Online Analysis Platform for COVID-19



This platform is specifically designed for high quality evidence synthesis of COVID-19 findings using meta-analysis methods. We aim to account for features in the growing evidence on clinical results related to COVID-19, including the substantial heterogeneity in patient characteristics and interventions across studies, substantial difference in sample sizes across studies, varying quality of the reports, potential selective reporting of outcomes, and many single arm studies (without controls).


under construction

under construction

under construction

under construction

under construction

under construction

About this application

This online analysis platform works with different available methods and a variety of formats of data, enabling users to quickly obtain the meta-analysis results without writing any code.

Frequently asked questions

X-meta is an open-sourced, well-documented and interactive toolbox for meta-analysis. There are three main components to this toolbox: An R package called XMETA, video tutorials and documentation for the package and an online analysis platform. XMETA package offers several functions for performing meta-analysis and visualizing outcomes , allowing users to conduct robust multivariate meta-analysis (mmeta), publication bias test (PB), outcome reporting bias test (ORB) and novel visualization tool (galaxy). Through the tutorials, reference documents and sample code, users can have a comprehensive exploration of the features found in XMETA and how they may apply to analytical work.

X-meta: a toolbox for meta-analysis

This app is written in the R programming language and built with the Shiny web application framework for R. Contact us for details.

Contact information

Yong Chen, Ph.D.
Associate Professor
Department of Biostatistics, Epidemiology and Informatics (DBEI)
The Perelman School of Medicine, University of Pennsylvania

For questions about this application, please email ychen123@mail.med.upenn.edu