I'm on my way back from the Terabase Metagenomics meeting in Snowbird, UT, and I'm buzzing with ideas about how to move forward in metagenomics and bioinformatics research. Metagenomics, the use of genomics approaches to study microbial communities, has been opening up as sequencing drops in price. With sequencing becoming ever more ridiculously deep and inexpensive -- we're looking at a power of 2-5 increase in depth every year for the next 5 years -- the questions have increasingly become intertwined with (surprise!) computational science problems and specifically bioinformatics. As we move towards multiple individual terabase (and collectively petabase) sequencing data sets in the next two years, life is going to become more complicated for metagenomicists and the bioinformaticians who aspire to help them. (That's me.)

The meeting was focused on the promise of terabase metagenomics for a "whole earth" microbial ecology sampling projects, and we spent quite a lot of time trying to figure out the size of unknown unknowns in metagenomics. There was a great mix of people at the meeting -- both "pure" microbial ecologists who regarded computers with suspicion and computer scientists who didn't understand how DNA became protein, as well as the entire range between those two poles. We talked about questions such as: "how deep do we need to sequence in order to get a real picture of microbial diversity?" (a: very) and "how do we reconcile genomic and transcriptomic data sets?" (a: unknown) and "how can we scale up 1000-fold when our existing algorithms are all N-squared?" (a: with difficulty.) The discussion was at a reasonably high level of sophistication: pretty much everyone in the room had "seen the elephant", and representatives of the major analysis pipelines were also present.

We didn't come to any firm conclusions about the biology, but we did sketch the outlines of a global sampling project to look at global microbial diversity, together with the deeper sequencing of specific locales to plumb the depths of a few communities. Coming up with a computational pipeline to deal with data and metadata on this scale -- storage, analysis, integration, presentation, and querying -- is truly challenging and should be fun.

For me, one recurring theme in the meeting was entanglement with management and standardization issues in big projects. Everyone was bitching about these on their existing projects, and I'm trying to avoid them. I have little or no interest in telling other people how to do their job; absolutely no interest in being told how to do my job; and a general lack of patience with standardization issues, however important and critical they may be. (In some ways, the Benevolent Dictator For Life approach to decision making used by the Python community seems optimal for medium-sized projects, although of course it takes a special person to pull it off. I acknowledge that decisions need to be made, but have no real interest in doing anything more myself than exploring the technical issues that could inform the decisions. Hmm, I wonder if the PEP process might be a good way to do a formal standards process in metagenomics?) I don't if there's any way for me to avoid this stuff in the future, but it's the main reason that I'm wary of joining big projects.

A few interesting references came up during the meeting. For example, I hadn't seen the Heilmeier Catechism before; I think it's a good idea for both scientific and open source projects to look at this before they do too much work! I was also entertained by Jonathan Eisen's report on things that the workshop participants disliked: for example, "Bureaucracy (and how it impedes science)."

All in all, I think this meeting was fantastic: very small, very focused, and with plenty of time for discussion and socializing. I'm happy the organizers invited me, so thanks to them!

--titus

Legacy Comments

Posted by Deepak on 2010-07-31 at 13:25.

Ben Black gave a talk at OSCON recently on standards in another
context.  The point he made and which applies really well here, is
that in any area that is moving rapidly, if you standardize too early
you might standardize to the wrong thing.      While we should avoid
inventing new formats or using old ones incorrectly, with next gen, is
it sufficient to let the community settle on a common framework (set
of formats, standards)?  It's happened in other areas (small
molecules, proteins). At the current rate of change, by the time you
get a committee in place it will be a moot point.

Posted by Titus Brown on 2010-08-02 at 14:57.

I have no comment other than "great point" ;).  I think the metadata
issues are pretty important, though, and should be something that
microbial ecologists have already thought through thoroughly.    also
see <a
href="http://gensc.wordpress.com/">http://gensc.wordpress.com/</a>.