The OpenHelix Blog

There may be a lot of opportunity to get one’s genome of interest sequenced in the near future.  And I don’t only mean your own personal genome–I mean your species of interest.  There should be academic centers and service providers who offer genome sequencing at increasingly reasonable pricing soon.

So let’s say you get your favorite sample done: what next?  We have talked about how cool it is to be able to use the GBrowse or WebGBrowse tools to display your data.  But that is missing a step, actually.  To get appropriate data to display you need to annotate your genome.  You need to curate your genome.  The GMOD suite offers some tools to do this–Apollo can be a part of your strategy. JCVI has an annotation service for prokaryotic genomes that uses Manatee. They frequently offer a prokaryotic annotation course around that process as well.

But the other day I heard about another option that I thought I would mention: the BLAST2GO team is announcing a course on Automated Functional Annotation and Genome Mining.  Here is their announcement via the GOFriends mailing list–personally I would choose the one in Valencia

•Are you working in sequencing projects?
(EST projects, Next Generation Sequencing, Microarray desing, etc… )
•Do no have thousands of novel sequences that need functional annotation?
•Do you need a user-friendly tool to functionally analyze your data?
The Blast2GO Team is very pleased to announce:

FIRST INTERNATIONAL COURSE IN
AUTOMATED FUNCTIONAL ANNOTATION AND DATA MINING

In this course you will learn tools and tips for functional
annotation, visualization and analysis of novel sequence data making use of Blast2GO.

The course will be offered to 35 participants at 2 locations:
•Valencia, Spain: 28 to 30, September 2009
•Florida, USA: 14 to 16, October, 2009
For more information and registration until the 1 of September please visit:
http://bioinfo.cipf.es/blast2gocourse

But Florida in October wouldn’t be a bad option either!

For more information about just the BLAST2GO part, check out this site: http://blast2go.org/

Yes, I know, but I used to be resistant to blogging too….

I’m starting to get a number of announcements about Twitter feeds from bioinformatics resource groups.  I think it’s time to start a collection of those.  This post will have a couple to get started, but I’m going to use this as a collector for others that will inevitably come across over time.

WormBase: (announcement), their feed is http://twitter.com/wormbase

GO: (announcement), their feed is http://twitter.com/news4go

If you have others, let me know in the comments. Or for my co-bloggers feel free to edit this post to grow the list.

No doubt you’ve seen all those Gene Ontology (GO) terms in the databases.  There’s a nice story behind the development, structure and use of GO terms which we describe in our full tutorial on the topic.  But another important feature of GO is that is continues to evolve and improve, and a new feature is in the process of rolling out.

I learned about this from the a GO mailing list.  If you find yourself relying on GO terms for tools you support or queries you may do to annotate lists of genes, you may want to keep up with changes like this.

On February 17th the GO team implemented major new features, one of which is expanding the use of “regulates” to the Molecular Function hierarchy.  Earlier in GO development the relationships didn’t indicate a “regulates” relationship at all.  There were only “is a” or “part of” relationships between terms.  But they added regulates to the Biological Process group some time ago.  Here’s a sample of how that looks:

The really big new aspect of this, though, is not just this functionality within Molecular Function terms.  It is that now they are creating a “regulates” function between the Molecular Function and Biological Process terms–these are called intra-ontology links.

This is a nifty new way to be able to annotate genes and gene products.  It carries more information than just a single definition would. But, it is also rather a challenge for software developers because it is a largee conceptual leap than the straight hierarchies are.  So it may take a while to fully roll out to your favorite database that uses GO.  But watch for it–it is a big deal.

For more details if you are interested (or you have software that may break because of this) you can see more details and an example in the GO wiki:

http://wiki.geneontology.org/index.php/Overview_of_Function-Process_regulates_links

One example is this:

Specifically, we have made the implicit regulatory relationships between ‘regulation of molecular function’ BP terms and the corresponding MF terms explicit. For example:

   * regulation of kinase activity (BP) regulates kinase activity (MF)

It makes sense in English, I know. But it’s not so simple for a computer. They have to be told this. And that’s what this change can do.

I’ll concede that this may not be among the most exciting things in your life lately.  But it is big for what we do.  So I just thought I’d mention it….

Comprehensive tutorials on the Gene Ontology and Textpresso databases enable researchers to quickly and effectively use these invaluable resources.

Seattle, WA (PRWEB) December 8, 2008 — OpenHelix today announced the availability of an updated suite on the Gene Ontology (GO) database and a new tutorial on Textpresso. Gene Ontology is a consortium project developed to create a list of biologically relevent and carefully structured terms that can be shared among all sorts of bioinformatics resources. Textpresso is a customizable open source web tool, using GO ontologies, that allows you to text-mine the biological literature. In addition to the OpenHelix Controlled Vocabularies tutorial and others, these two tutorials give the researcher an excellent start to understanding and using gene ontologies.

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:

Gene Ontology

• how to understand the organization of the Gene Ontology hierarchies
• how to search the AmiGO browser for terms, definitions, and annotated genes and gene products
• how to begin with sequence data and find useful terms and definitions that may help to characterize your sequence of interest

Textpresso

• how Textpresso works
• the layout for all Textpresso sites
• how to perform both basic and advanced searches
• how to use Textpresso as an information retrieval and extraction tool

To find out more about these and other tutorial suites visit the OpenHelix Tutorial Catalog and OpenHelix or visit the OpenHelix Blog for up-to-date information on genomics.

About OpenHelix
OpenHelix, LLC, 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.

An email from the GO mailing list reminded me of some upcoming changes. It used to be that there were term relationships of “is a” and “part of” between items. Recently they added a new relationship–”regulates” in the Biological Process hierarchy. And regulates can be plain, positive, or negative–with very cool icons to make that clear:

(to see these in the software, go to this link: DNA Metabolic Process, and open to see the children of that term in the text view)

But now we are going to get more relationships! Next February they will add “regulates” to Molecular Function terms, and they will have inter-hierarchy relationships (full announcement here):

Specifically, we will make the implicit regulatory relationships between ‘regulation of molecular function’ BP terms and the corresponding MF terms explicit. For example:

• regulation of kinase activity (BP) regulates kinase activity (MF)

Similarly, we will make the implicit regulatory relationships between terms within the MF ontology explicit. For example:

• calcium channel regulator activity (MF) regulates calcium channel activity (MF)

They are trying to get the word out because if you have software developed that works with the relationship descriptors, this is a big change. It may break your software.

And yes, it will break our tutorial…but we’ll fix that when the time comes.

We are thinking quite a bit about pathway tools these days. I got a jolt of input on them from the ICSB meeting recently, too. As I continue to progress through my meeting notes I’ll be checking out more tools and writing about them.

One of the things that seemed new and important (well, to me at least) was the first release of a set of standards for drawing pathway diagrams. During this meeting they announced the release of 1.0 of the SBGN notations (also known as Level 1; more levels are anticipated as this progresses). SBGN is Systems Biology Graphical Notation. You can access the SBGN site here: http://www.sbgn.org/

The idea is that if we can standardize our representations of pathways we can all be sure that the meanings are the same for arrows, and boxes, and so on. For example, if I draw a pathway with an arrow, my arrow means the same thing as your arrow in your pathway diagram.

What the SBGN team says on their homepage:

SBGN defines a comprehensive set of symbols with precise semantics, together with detailed syntactic rules defining their use and how diagrams are to be interpreted.

So this is kind of like Gene Ontology for systems and pathway diagrams. Not only is it increasing the clarity of the diagrams, it will guide software development so that software for generating diagrams and analytical tools can work in this framework as well.

There are examples on the web site. Check out the document on the specifications (a big PDF), too–lots of detail on what, how, and why this is important. They want feedback on this. You can also check out the associated SBGN wiki with more details and the SBGN forum for interaction with the team.

The question we probably hear the most from researchers is…what can I do with a giant list of genes to figure out what’s going on in there? And about once every 6 months this question comes across the Gene Ontology mailing list. This is followed by a flurry of developers who offer their cool tools for analysis purposes. There are actually quite a few different tools with different strategies out there–and they are designed for different purposes, and in this tip I’m going to use the Gene Ontology consortium’s GO Term Enrichment tool as a primary example, but I’ll also point you to a list of other tools to try out.

Just came across the GO-friends mailing list:

As previously announced, The Gene Ontology Consortium has now introduced three new relationship types

– regulates,negatively_regulates and positively_regulates — into the Biological Process ontology. These relationship types improve the representation of regulatory processes in the GO.

Please see the following pages on the GO website for more information:

http://geneontology.org/GO.process.guidelines.shtml#reg
http://geneontology.org/GO.doc.shtml#ontology-structure
http://geneontology.org/GO.usage.shtml#relationships

The new relationship types will be visible through the AmiGO browser by the end of this month and at the various model organism databases that display GO as they update their ontology files.

Sincerely,

Tanya Berardini
David Hill
Chris Mungall

on behalf of the GO Consortium

Keep this in mind as you use GO tools–some tools will implement the changes before others, and it may affect what you see in different databases.

Congrats to the GO team, I’m sure it was a major project to wrangle.

Yesterday from the Gene Ontology GoFriends mailing list I got notified about Babelomics. The creators describe Babelomics as:

Babelomics is a suite of interconnected tools oriented to the functional annotation of genome-scale experiments. One of the field for which Babelomics is best suited is the analysisn of microarray gene expression experiments. Nevertheless Babelomics is not restricted to this type of data and has been designed for facilitating the interpretation of large-scale experiments.

I think the tools sound terrific. But I just wasn’t sure I could handle another -omic…

And then my email from the HUM-MOLGEN list arrived. I found out about the Variome meeting. The Variome project aims to collect and make available information on human variation that is correct and complete. Another worthy exercise. But another -ome for the collection. I can’t take the growth of the suffixome any more….