Today’s Tip of the Week is a short introduction to WAVe, or the Web Analysis of the Variome. The tool was recently introduced to us, and I’ve found it a welcome introduction to the tools available to the researcher to analyze human variation. This is apropos considering the recent paper we’ve been discussing on the clinical assessment of a personal genome (here, here and here) and that papers implications for personalized medicine and the use of online variation resources. WAVe also has introduced me to some additional tools I’ve either not been aware of, or haven’t used, which might be of use such as: LOVD (Leiden Open Variation Database), QuExT (Query Expansion Tool, also from the same developers as WAVe), and others. Of course there are also database information pulled in from Ensembl, Reactome, KEGG, InterPro, PDB, UniProt, NCBI and many others. Take some time to check it out.
Reactome has long been one of our favorite resources for looking at pathways and interactions. The data quality is very high, and there are some very fun tools to use. In fact, they were one of the earliest tutorials we did years back (but of course we have updated since).
If you aren’t already familiar with it, you should check it out: Reactome.org And even if you do know about this, you may not know that it also comes in green! I did that as a Tip of the Week once–and check out Arabidopsis Reactome. Of course, you’ll also find Reactome data in other places–like Entrez Gene, PID, and more.
And you should also help them out by answering their survey. Here’s the request from the Reactome team:
Reactome Pathway Database User Survey
Reactome is committed to providing access to high-quality pathway information and helpful data analysis tools. With this in mind, we are actively soliciting comments from the research community in order to assess community needs. We are interested to hear about your experience with Reactome, and would like to know a bit about your background and research interests so that we can continue to improve the Reactome site and tools.
You can access the survey at: http://tinyurl.com/l48zzq
Thank you for taking part.
Manager of Reactome Outreach
C’mon: you know the grant agencies and developers really want this kind of feedback. Help them out.
Last night I had coffee with good friends in Davis Square and I mentioned that we had this blog. One of the friends (a linguistics scholar) seemed excited by the prospect until I told her the topic. She’s not nearly as excited by new software and scientific data as I am
It cracked me up this morning when I read the Reactome news letter–my first thought was: cool, axon guidance pathways! And I imagined my friend’s bemused look….
Anyway, there’s a new Reactome release. Here’s some of the new stuff content-wise:
New content. As part of a project to annotate the general process of cell motility and its involvement in key biological processes, Version 29 introduces a new topic, Axon guidance, with material now available for NCAM signaling in neurite outgrowth. Pathway topics updated with new curated events in this release include: Synaptic transmission (Glutamate Binding, Activation of AMPA Receptors, and Synaptic Plasticity), DNA Repair (regulation of FANCD2 and FANCI activity in the Fanconi Anemia pathway), and pathways whose dysfunction plays a major role in the development of diabetes (Regulation of insulin secretion and Unfolded protein response). With the annotation of G-coupled protein receptors (GPCRs) for eicosanoids, leukotrienes, nucleotide-like (purinergic) molecules, LPA and lysosphingolipids, opsins, secretins, and GABA and related molecules (class C/3 receptors), our annotation of interactions between GPCRs and their ligands is essentially complete. The Telomere Maintenance pathway has been revised in this release. Updated release statistics are available.
If you are interested in keeping up with Reactome their mailing list is here: http://mail.reactome.org/mailman/listinfo/reactome-announce
At the recent ICSB conference I attended a terrific talk by Esther Schmidt. The focus of the talk was Reactome, which is an old favorite of ours. It has great high-quality curated data on biological pathways and has some fun tools to go beyond browsing around. But during the talk I learned about a new aspect of Reactome that I didn’t know about before: Arabidopsis Reactome!
Arabidopsis Reactome is based on the same Reactome software framework, but it is very very green :). The focus of the site is, of course, Arabidopsis pathways. In fact, in the paper that describes the resource says that this database covers about 8% of the Arabidopsis proteome at this time. But in addition they have “electronically projected” (aka inferred orthologous events) among 5 other plant species as well. Rice, poplar, a moss and 2 of the grapes have been completed, so they use those 6 species to provide the view of the plant pathway systems that you’ll find at the site.
In this ~3min movie I give you a quick look at the green pathways–but you should go over and have a look yourself as well: http://arabidopsisreactome.org/
Also, check out their paper: http://www.plantcell.org/cgi/content/full/20/6/1426
Arabidopsis Reactome: A Foundation Knowledgebase for Plant Systems Biology. Nicolas Tsesmetzis et al. The Plant Cell 20:1426-1436 (2008) DOI: 10.1105/tpc.108.057976
In this week’s tip I wanted to talk about a tool that offers a handy way to visualize the items in a list of genes that you might have on pathway diagrams. Reactome offers a tool called SkyPainter that allows you to enter a list of genes which is then analyzed statistically for genes in certain pathways. But then–and here’s the cool part–you also get a diagram of the pathways with the over-represented genes painted on a map of their pathway universe. See–SkyPainter. Anyway, it is a tool I have liked for years and I’ve been thinking a lot more about lists of genes and pathway representations. So I wanted to share that with you. This ~4 minute movie shows you how to access SkyPainter at Reactome and get started using it. Have fun!
Yesterday I attended the final session of the ICSB conference that I could fit into my schedule: a session on web services in systems biology. (I would link to the description but the ICSB server is down while I write this…) There were several tools covered that I will address later (including one of our old favorites: Reactome. And Esther Schmidt showed me a trick to accomplish some teeny little thing that was making me crazy….Yea Esther!). But I wanted to get you thinking about using tools in workflow pipelines. This is not just for giant sequencing projects anymore!
Although there are a variety of tools that can let the average user in on this handy strategy, yesterday we heard specifically about the Taverna project. Taverna will let you pull re-usable modules of analysis tools into a series of actions that you can perform on your lists, or favorite sequences, or genomic regions, or whole genomes…and annotate, analyze, and process. Don’t be daunted by the look of that project page. We can help you to understand what to do and how to do it. But start to think about the series of things you might be doing from website-to-website as you do your research on genes of interest. Can you imagine a way to streamline that and set up a re-usable protocol to do that? I’ll bet you can….
More later on these types of services. But I’m off to Copenhagen today and won’t be online much until next week. Enjoy your weekend! Scandinavians seem to really understand the purpose of the weekend…
OpenHelix today announced the availability of a new tutorial suite on MINT, a highly used database of protein-protein interactions, and an update to the Reactome tutorial. MINT is a collection of molecular interaction databases that can be used to search for, analyze and graphically display molecular interaction networks from a wide variety of species. Reactome is a knowledgebase of biological processes that is a high quality, deeply curated assembly of information about biological pathways and their components, including both biological and chemical entities.
The tutorial suites, available for single purchase or through a low-priced yearly subscription to all OpenHelix tutorials, contain a narrated, self-run, online tutorial, slides with full script, handouts and exercises. With the tutorials, researchers can quickly learn to effectively and efficiently use these resources. These tutorials will teach users:
- how to search for protein interaction data in MINT
- how to search for protein interaction data in MINT
- how to search for inferred human interaction data in HomoMINT
- how to search Domino for peptide domain interactions
- to edit and manipulate interaction data in the MINT viewer
- to navigate through the high-quality biochemical pathway information in Reactome
- how to find diagrams and details about biological pathways
- ways to link to information about specific pathways and participating molecules
- to use the Reactome Mart interface to generate custom queries of the underlying database
OpenHelix, LLC, (http://www.openhelix.com) provides the genomics knowledge you need when you need it. OpenHelix currently provides online self-run tutorials and on-site training for institutions and companies on the most powerful and popular free, web based, publicly accessible bioinformatics resources. In addition, OpenHelix is contracted by resource providers to provide comprehensive, long-term training and outreach programs.
PLoS Biology reports today on WikiPathway. The paper entitled “WikiPathways: Pathway editing for the people,” announces a new wiki for the ‘public curation’ of pathway data. The authors argue that
The exponential growth of diverse types of biological data presents the research community with an unprecedented challenge to keep the flood of biological data as accessible, up-to-date, and integrated as possible.
I agree with this. We’ve seen it here and mentioned it many times, the growth of data is exponential and difficult to keep track of. The proposed solution for pathway data, as there has been for other data types and curation that I’ve written about lately, is a wiki: WikiPathways to be exact. The authors have high hopes for this wiki, as they state:
WikiPathways will be a powerful resource for the research community and a vital forum for pathway curation, And we are hopeful that it will serve as an example for how the continuing flood of biological data can be managed and utilized by the community to irrigate future hypotheses and discoveries
I’ve already made known my “skeptical optimism” for wikis for biological data known in a previous post, reading this later paper, that would still apply here. But right now I’m not going to write beyond that, I’m just going to point you to this paper and wiki. Later (this week, next at the latest) I’ll be critiquing this paper more fully and more generally look at this trend currently to use wikis for community curation and documentation of biological data and databases.
Pico, A.R., Kelder, T., van Iersel, M.P., Hanspers, K., Conklin, B.R., Evelo, C. (2008). WikiPathways: Pathway Editing for the People. PLoS Biology, 6(7), e184. DOI: 10.1371/journal.pbio.0060184
Sometimes the Google brings you things that surprise you. I have to say this link rattled me for a minute:
Came across a nice bacterial genome browser today via “Discovering Biology in a Digital World:” the Genome Projector. The is a map of over 100 bacterial genomes including a circular genome map, a genome map, a pathways map and a “DNAWalk” map. Put in a search term (I put “iron” in here, you know, as in ‘mining for,’ tried gold, but alas.. there is no gold in them thar… anyway…) and the hits show up as numbers in the tabs and pins in the maps. The maps are zoomable (just like GoogleMaps) and the pins are clickable with a popup to links out to databases and more information. It’s not quite as useful or in depth as perhaps IMG as a browser or Reactome or Kegg for pathways, but it’s simple and cool way to browse the genomes for more information and links to databases. Below the fold (continue reading link) are two more screenshots of my search in pathways and zoomed with clicked pin. Continue reading