Biological Augmented Browsing Connector
Explore the ideas of augmented browsing in life sciences-related applications.
Key topics:
Originally posted at the OpenHelix Blog.
This next post in our continuing semi-regular Guest Post series is from Pedro Lopez, developer of WAVe at the University of Aveiro Bioinformatic Group in Aveiro Portugal. If you are a provider of a free, publicly available genomics tool, database or resource and would like to convey something to users on our guest post feature, please feel free to contact us at wlathe AT openhelix DOT com or the contact form (write ‘guest post’ as subject heading). We welcome introductions to your resource, information on updates, highlights of little known gems or opinion pieces on the state of genomic research and databases.
I would like to start by thanking Trey Lathe for the opportunity to promote WAVe in this great blog. After his short tip of the week post, I’ll now try to make a more detailed overview of this new application.
What is WAVe?
WAVe stands for Web Analysis of the Variome and is a simple application focused on centralizing the access to distributed and heterogeneous locus-specific databases (LSDB). LSDBs are an emerging type of bioinformatics applications, aiming at providing gene-centric information regarding discovered genomic variants. In WAVe, we offer both LSDBs as well as to its variants. Moreover, we also provide access to a comprehensive list of carefully selected external resources. With this, users have, in a single application, access to gene and variation information enriched with a multitude of gene-related resources in a lightweight and easy to use web application.
What are WAVe’s key features?
At this early stage, WAVe’s publicly available features are related with data access. Users can easily browse through available genes, search for genes, view gene info and access each gene RSS feed. In WAVe’s entry page, users simply need to start typing a gene HGNC-approved symbol and several suggestions will appear: accepting one of them leads directly to the gene view page. Following the view all link, users can browse all available genes or check, for each gene, how many LSDBs and variants are available.
To access the application data, users just need to navigate in the gene tree. Each tree node represents a distinct data type and the various leaf provide access to external applications: by clicking a leaf, the destination page is loaded in the main content area. Repeating this process, users can navigate in the dozens of listed links for each gene.
WAVe also offers its core data to other developers. To obtain the gene tree and its links, users just need to add the rss tag to the end of gene address. This will output a RSS2.0 feed that can be easily parsed by any application or added to a feed reader.
How was WAVe born?
The european GEN2PHEN project is an initiative to link, as deeply as possible, data from genotype features to its phenotype counterparts. The first step consisted in an attempt to improve various genomic variation resource scenarios. This implied normalizing LSDBs (the “LSDB-in-a-box” approach, LOVD) and defining novel data models and formats for data exchanges from and to LSDBs.
In a long term perspective, applying the GEN2PHEN-approved data models, will enhance the creation of new services and applications to integrate and interact with the exponentially growing dataset of genomic variation data.
With WAVe we tried a different approach based on three questions: why wait for everyone to adopt these new formats? What will happen to legacy LSDBs that won’t adopt the new formats? How can we have an immediate solution? We have created a lightweight integration architecture, based on links to applications and adopted a simple (yet familiar) tree-based navigation interaction to deploy a new application that can be used right now and will easily scale to integrate the foreseen data exchanges formats. Technical details aside, based on a manually curated LSDB list, we can connect and integrated any kind of LSDB application whether it is a modern LOVD application or a simple text-based legacy LSDB.
How is it relevant?
To demo WAVe efficiency let’s just try to perform a simple search in our lab: Are there any LSDBs for COL3A1 gene in the human species? And known variants? And what are the associated proteins and pathways?
In a WAVe-free scenario, to find out COL3A1 LSDBs (if any), researchers need to google it (the main COL3A1 LSDB does not appear in the first result page) or, if you they are used to it, go to HGVS site, go to the “Databases & Tools” section, select “Locus-specific Mutation Databases” and then search for the gene in search box. Now for the variants researchers just need to browse the last page they’ve just entered. How many clicks (and time!) does it take?
For protein information, researchers enter in UniProt and search for COL3A1: that gives about 29 results. Add a filter for the human species and there are 5 results. Good enough to access directly to P02461 (SwissProt reviewed). Though, there is new window/tab open. Now for pathway information, a KEGG quick search for COL3A1 lists 14 results. In the end, there are about 3 windows/tabs and made some 20 mouse clicks to obtain the desired information.
Using WAVe, researchers simply need to access WAVe, start typing the gene HGNC symbol, select COL3A1 from the suggestions and access COL3A1 page. Once in the page, it’s as easy as browsing in the tree… Variations? Check the variation node, they’re even grouped according to the change type. UniProt information? Check the protein node where you have direct access to SwissProt, TrEMBL, PDB, Expasy and InterPro. And I guess you get the picture. In the end, one window/tab and about 6/7 mouse clicks.
Other UA.PT Bioinformatics tools
At the University of Aveiro’s Bioinformatics research group we are mainly young and enthusiast computer science experts, simply trying to make biology easier (at least in terms of computer applications!). Our more relevant web-based tools include MIND (a microarray analysis tool), GeneBrowser (a gene expression tools, useful to process data gathered from systems like MIND) and QuExT (a comprehensive MEDLINE mining application).
New application that will search results for user submitted queries in various search engines (Google, Yahoo, Bing…).
A map is built from the results, showing relations between pages, what the pages contain, what the pages refers to… and then, show information about the pages in an outstanding workspace.
For instance, searching for BRCA2 in Google provides an immense amount of information that cannot be ignored: wiki pages, uniprot, genome.gov… If we could organize this information in a coherent manner, it could mean something in bioinformatics. Moreover, we can predefine a set of “known links” and offer more information about these links. If a link points to uniprot, we could provide a bigger set of related data or enable data expansion from that concept on.
2010 begun with a new challenge: plan and develop, as fast as possible, a simple variant integration application based on DiseaseCard‘s navigation concept. The idea was to reach GEN2PHEN‘s goals with a new DiseaseCard-like application focused on integrating LSDBs (no one does it!) and variants contained in those LSDBs. Moreover, relevant gene-related information (pathways, proteins…) should be provided in the elegant navigation mechanism.
WAVe | Web Analysis of the Variome (version 1.0beta) is online and I consider it a success. There is plenty of room for improvements and new features which, I believe, will make WAVe a key application in GEN2PHEN.
Enough talking, WAVe is a variome integration application, focused on providing a centralized access to online available locus-specific databases and genomic variants. If you have any interest in life sciences you should visit at http://bioinformatics.ua.pt/WAVe. In case you really know something about genes, go directly to a gene by providing its HGNC symbol: for instance, BRCA2 is at http://bioinformatics.ua.pt/WAVe/gene/BRCA2.
Feel free to give your comments/critics/opinions/suggestions, they are welcome! Comment here or send it to pdrlps@gmail.com!
WAVe
Until about a year ago I’ve never heard about Tron before. Well, I’ve probably heard about it, I guess I’ve seen something similar on TV but I haven’t really looked into it. Then, with all the hype surrounding Tron Legacy I was pushed into “Flynn’s world”.
This week I’ve finally managed to watch the original Tron. Tron premiered in 1982 and it was a “medium-weak” moving using state-of-the-art 3D CGI images mixed with human actors. Explaining, Tron was one of the first movies (28 years ago!) to combine computer generated images with real live performances. Well, how many movies don’t do this nowadays? 2 out of 10?
At a first glance Tron is a really poor movie. The idea is great, though the dialog is crappy… Nevertheless, Tron was released in 1982!!! And from that point of view this is a fantastic movie! Ok, it’s not Blade Runner or ET or The Wrath of Khan but it’s a very entertaining (Disney) family movie!
Looking at the concept, the plot is focused around a “hacker”, trying to clear is name in a technology company controlled by an evil “Master Control Program”, that gets digitalized into a virtual world and has to help a defense program (Tron) to destroy the Master Control Program. So… evil virtual Master Control Program… Skynet anyone? Agent Smith? Humans inside a virtual world? What? Like the Matrix?
Tron may not be the original source for this hot idea in movies about robotic/digital entities trying to annihilate humanity but it definitely has it’s place in movie history. And such a place has gave this movie a new life. Maybe because of the current hype surrounding 3D or everything digital, Disney is re-exploring Tron with a new movie to release this year. This time it’s focused on Flynn’s son journey into the digital world…
And if you really want to know what evolution is (in movies and in computer graphics), here are the original Tron trailer (from 1982) and the teaser and first trailer for 2010’s Tron legacy. Just look at those lightcycles!
Go and see Tron and get hyped for December’s Tron Legacy prémiere here, here and here.
Yay! After many many many hours of web design, finally found a good-looking style to use in WAVe. Is almost everything done, except typography, autocomplete boxes and the tree!
Now it’s time to put everything in the Java application and start writing “the stuff”. (for “the stuff” I mean disclaimers, tutorials, help, content…)
I’m getting near version 0.1. In ideal conditions there is search, browsing, navigation… for all the genes… looking good so far!
The tree was almost finished today, time to add more and more features!
There is a gene tree working on WAVe finally. Only missing the empty data types issue… I’ll try to correct it later… Content is only loaded in an iFrame also, it should be AJAX in a div, but for now it works!
Time for greater things: features, features, features! And a theme?
Today developed the algorithm for reading the tree for each gene… so many stuff to test (LSDB? no leafs? gene values or GeNS values? statis or dynamic?)
Therefore, XML card methods are done… and there is a lot of code to comment!!!
Finally managed to finish the VarCrawler (sub)application for WAVe.
Deploy calls Creator and then Builder.
Creator for starting up and loading default values, Builder will read variants from all the web and load information from GeNS.
It is running now… for 6 hours and is at COLA63…
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