Dear SEQanswers members,
we have developed a web app, DEIVA, for interactive visual analysis of differential gene expression results, such as you typically get from DESeq2 and edgeR.
The core functionality of DEIVA is the ability to identify and locate genes in density or scatter plot representations in a way that meets user expectations, with minimal effort, virtually no learning curve, and no dependencies on any browser plug-ins or need for the end user to install anything. Almost all processing is done client side, so DEIVA scales very well with increasing numbers of users and datasets. We found it useful for exploring differential gene expression plots in the context of several research projects.
Typical scenarios why you might want to deploy DEIVA:
Features
A running live instance with data to play around with is at
No sign up needed!
Th green "Show me!" button in the upper right corner starts a quick tour.
I am posting this here in SEQanswers because we are very interested in getting feedback on DEIVA. Either here on the SEQanswers forum, or in the form of GitHub issues, or by email. I believe and hope some of you might find it useful - please let us know what you think!
The project homepage is
Thank you,
Anton
we have developed a web app, DEIVA, for interactive visual analysis of differential gene expression results, such as you typically get from DESeq2 and edgeR.
The core functionality of DEIVA is the ability to identify and locate genes in density or scatter plot representations in a way that meets user expectations, with minimal effort, virtually no learning curve, and no dependencies on any browser plug-ins or need for the end user to install anything. Almost all processing is done client side, so DEIVA scales very well with increasing numbers of users and datasets. We found it useful for exploring differential gene expression plots in the context of several research projects.
Typical scenarios why you might want to deploy DEIVA:
- Sharing results with others, especially colleagues who are not inclined or do not have the time to use R/Bioconductor, and enabling them to do some analysis in a very immediate manner
- Discussing differential gene expression results in meetings, looking up things "live"
Features
- Identify genes by brushing.
- Locate genes by searching for their name. Multiple genes can be located at the same time (separated by a space), and are automatically highlighted in different colors.
- Search for genes in the data table.
- Zoom: use the toolbar to zoom into the selected rectangle (home button zooms out).
- Filter: two different cut-off sliders which are linked by logical "and". Number of genes passing the filter, up and down, is shown.
- Mobile device support. The user interface adapts to desktop as well as mobile environment devices.
- Just select pre-loaded data from a dropdown, or:
- User data. Drag and drop formatted differential gene expression results files onto the plot area to view them in DEIVA.
- MIT license
A running live instance with data to play around with is at
No sign up needed!
Th green "Show me!" button in the upper right corner starts a quick tour.
I am posting this here in SEQanswers because we are very interested in getting feedback on DEIVA. Either here on the SEQanswers forum, or in the form of GitHub issues, or by email. I believe and hope some of you might find it useful - please let us know what you think!
The project homepage is
Thank you,
Anton
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