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Thread | Thread Starter | Forum | Replies | Last Post |
ContigScape for visual interactive gap closure | hard998 | Bioinformatics | 1 | 10-15-2013 04:36 AM |
GobyWeb web application for alignment and differential expression analysis | Fabien Campagne | Core Facilities | 0 | 11-04-2010 03:43 PM |
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#1 |
Junior Member
Location: San Diego, CA, USA Join Date: Jun 2016
Posts: 7
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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
http://hypercubed.github.io/DEIVA/ 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 https://github.com/Hypercubed/DEIVA Thank you, Anton Last edited by anton.kratz; 06-05-2016 at 08:59 PM. Reason: Added info on "Show me!" button |
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#2 |
Senior Member
Location: Germany Join Date: Oct 2008
Posts: 415
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Interesting!
What would you say are the key advantages or disadvantages of DEIVA with respect to DEGUST ? http://www.vicbioinformatics.com/degust/ Is it, say, easier to install (Degust is _very_ hard) ? |
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#3 |
Junior Member
Location: San Diego, CA, USA Join Date: Jun 2016
Posts: 7
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Hi colindaven,
DEIVA is extremely easy and fast to install - please have a look at "Deploying DEIVA with your own data" in the GitHub readme. There are no server dependencies or plug-ins needed, just clone the gh-pages repo and replace the example data with your own data. If you just want to quickly look something up, this is even easier, in that case you can just drop your own file onto the "Drop your own data here" button; it is safe, no data is sent anywhere, everything stays client side. Compared to DEGUST: DEIVA is the only tool that has gene lookup. This is great for looking up lists of marker genes or any gene list of interest. It is also far easier to use than DEGUST in my opinion. The aim behind DEIVA was to make it as easy to use as, say, Google mail. Pros of DEGUST: it has more functionality than DEIVA. But again, the motivation to create DEIVA was to make a tool for identifying and looking up genes as easily as is possible, so that bioinformaticians can communicate and share their results with domain experts easily while meeting user expectations (easy to understand and use like any other web app, mobile device support), being scalable to very large projects, and secure. If you want more functionality than what DEIVA provides, I recommend setting up something like Gene Pattern by Broad Institute (http://www.broadinstitute.org/cancer...e/genepattern#), this requires some heavy lifting though. Their Multiplot module is somewhat similar to DEIVA, but again: without gene lookup as fas as I can see. We are working on a manuscript where we also compare DEIVA to several other tools in a feature matrix. |
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#4 |
Senior Member
Location: Germany Join Date: Oct 2008
Posts: 415
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Thanks, that's a great answer. I will look at looking DEIVA in the future if it is easy to install since there is a lot of value in this kind of app where a biologists' exploration of their own data is not tied to availability of a bioinformatician.
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#5 | |
Junior Member
Location: San Diego, CA, USA Join Date: Jun 2016
Posts: 7
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#6 |
Junior Member
Location: San Diego, CA, USA Join Date: Jun 2016
Posts: 7
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There is now also a publication for DEIVA:
Harshbarger J, Kratz A, Carninci P. 2017. DEIVA: a web application for interactive visual analysis of differential gene expression profiles. BMC Genomics 18. http://bmcgenomics.biomedcentral.com...864-016-3396-5 |
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#7 | |
Junior Member
Location: Vienna Join Date: Aug 2016
Posts: 1
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Hi Anton, Is it possible to change the pre-uploaded data in project-chi-electron-app? I would like to upload my deseq2 files here? I am having troubles installing from the source code and making the changes suggested on the website. I am not a bioinformatician so I would'nt be surprised if I am doing something extremely stupid. If data cannot be changed to the electron-app, I would be grateful for a step by step installation instruction. Thanks, Utkarsh |
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#8 | |
Junior Member
Location: San Diego, CA, USA Join Date: Jun 2016
Posts: 7
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instead of installing from source, a far easier way is to download the gh-pages branch Zip file from https://github.com/Hypercubed/DEIVA/...e/gh-pages.zip You can just download this zip-file and unpack it somewhere, and replace the example data with your data, and adjust the index.tsv file. See section “Deploying DEIVA with your own data” in the readme at https://github.com/Hypercubed/DEIVA#...-your-own-data For this to work, probably (depends on your browser and maybe other external circumstances) it might be necessary that some web server is running. The reason is because many browsers do not run JavaScript anymore if you simply open a webpage. The webpage has to be served. I found that some versions of some browsers simply ignore this, though, and execute DEIVA even without a web server running. If that is too difficult or too convoluted, simply go to http://hypercubed.github.io/DEIVA/#/ and drop your file onto the blue button labelled "Select or drop data here". Or just press the button and navigate to the file in question on your hard disk. Please ask if you have further questions. Anton |
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Tags |
deseq2, differential expression, edger, visualization tools, web services |
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