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Globus Developers Lend a Hand to Make GADU the Gateway to the Genomics
Grid

A small team of researchers at Argonne National Laboratory is quietly
developing a platform that could usher in the much-anticipated era of
grid-enabled bioinformatics tools. Called the GADU (Genome Analysis and
Database Update) system, the automated sequence analysis pipeline
architecture is the first genomics-based application to run on the US
Department of Energy\'s Science Grid - an ambitious project that began
in 2001 with the goal of linking the computational resources of the
entire DOE lab system.

The ANL bioinformatics team, led by Natalia Maltsev, has expert guidance
in navigating the unfamiliar grid landscape. Ian Foster, a grid
computing pioneer and co-developer of the open source Globus toolkit,
heads up a team of six Globus developers who are working closely with
Maltsev\'s group to bring GADU online.

For Globus, which was first released in 1998, biology is new territory,
said Foster.\"When we started, the primary user base was in the physical
 sciences,\" he told BioInform, \"but increasingly we\'re seeing
interest from the life sciences in the use of Globus as a technology for
data federation, federation of computing resources, and other such
things.\"

The Globus/ANL team recently completed a proof-of-principle project that
ran the GADU analysis pipeline on 160 nodes of the DOE Science Grid at
ANL and Pacific Northwest National Lab. The team successfully analyzed
59 DOE microbial genomes - a task that required more than 200,000 Blast
jobs and generated 50 GB of data - in 11 hours. Maltsev said the GADU
team is currently modifying other bioinformatics applications, in
addition to Blast, to run on the Science Grid backend, and plans to add
additional DOE computing nodes to the system. \"Once you have the
gateway, you can expand,\" she said.

While the computational capacity of the grid should help relieve the
obvious number-crunching bottleneck in high-throughput genomic analysis,
Maltsev said the GADU developers also plan to exploit the storage and
data distribution benefits of the grid infrastructure. GADU\'s grid
expert partners were especially helpful for this part of the project,
Maltsev said: The National Center for Supercomputing Applications (NCSA)
contributed storage space on its Starlight optical network system and
the Globus team modified its Chimera data-flow middleware, which
documents \"data provenance\" so users can assess the validity and
reliability of data and computational resources.

Storage capacity and management is a key component of GADU, Maltsev
said, and the system enables both permanent storage and temporary
storage -- an important requirement for genomic analysis, she noted,
because intermediate outputs of parsers and analysis tools can be just
as important to retain as sequence data and annotations, but require
considerable space. Analysis of an \"average\" prokaryotic genome of
4,000 genes, for example, would require 1.2 GB of temporary storage and
1.0 GB of permanent storage, she said.

If the project continues as smoothly as it has so far, GADU and the grid
will prove to be a perfect match, according to Maltsev. \"First, you can
analyze the data very quickly; second, there is storage space so you can
store the data you are acquiring; and third, you can distribute the data
you are acquiring - it\'s a dream environment.\"

# Bringing Biologists on Board

Of course, there are always a few bumps on the road to realizing such
dreams. \"Some of the protocols are incompatible,\" she noted, \"but
people are trying to resolve these issues. For example, we were trying
to use the PNNL nodes, but we need to do some additional work to make
the architectures compatible.\" In addition, she said, the DOE Science
Grid architecture was initially \"not very accommodating for the types
of data that we have, because our data is embarrassingly parallel with
huge amounts of sequences\" - a challenge that required a fair bit of
\"restructuring\" of the grid architecture to resolve.

But the relatively novel technological territory on both the grid and
the bioinformatics sides of the joint project helped make things
interesting, according to Maltsev. \"While they are observing how we do
bioinformatics, the Globus group also finds improvements to what
they\'re doing,\" she noted.

And, as far as grid proponents are concerned, this symbiotic interchange
is really the mission of the project: Not only do biologists need
applications that will run on Globus and other systems before
grid-enabled bioinformatics takes off, but the caretakers of the grid
infrastructure must ensure that the underlying technology is compatible
with biological data.

Based on the success of GADU so far, neither Maltsev nor Foster foresee
any hurdles to bringing more bioinformatics projects onto the grid.
\"Everyone thinks they\'re special,\" Foster said, referring to new user
communities adapting to grid computing, \"and in some sense they\'re not
because the basic technology requirements are the same.\" Foster did
note that life science research - even in academia - does require a
higher level of security than the physical sciences. With this in mind,
\"we\'re putting a lot of effort

right now into techniques that will allow communities to manage their
\[security\] policy on a community level while at the same time allowing
for more flexible local site security policies,\" he said.

Maltsev said the GADU development team is on track to launch an alpha
version of a public GADU server before the end of the summer, which will
give users access to the Science Grid\'s computational power and also
enable users to assemble their own analytical pipelines. \"Everybody is
using Blast and Interpro and transmembrane prediction programs in
various combinations, so what we will try to do is to allow them to
combine the tools in the pipeline that will be of specific interest to
them,\" she said.

GADU, as well as other grid-enabled bioinformatics projects, may offer
\"a chance to change the sociology of genetic sequence analysis,\"
Maltsev opined, by eliminating the computational barriers that many
small

universities and research groups currently face. \"If they were able to
analyze huge amounts of data using grid technologies and a public
server, they could do the analytical part of the investigation without
building all these clusters and huge databases,\" she said.

GADU is currently funded by the NCSA Alliance, NIH, the University of
Chicago, and ANL. In addition to Maltsev, major contributors to the
project include Alex Rodrigez, Veronika Nefedova, Jens Vockler and many
others. Maltsev said she plans to seek additional funding for the
project following the alpha release of the GADU server.