PolITiGenomics

Soon after Illumina announced its HiSeq 2000, it also announced the GA IIx’s little brother, the GA IIe. The IIe will produce about half as much data as the IIx, but no one seems to know exactly how this is done. The unit is cheaper than the IIx, $250,000 for the IIe compared to $400,000 (I think) for the IIx, but is upgradeable to the IIx. So perhaps the optics system is cheaper. But the run time is the same, so it seems like the optics would need to be about the same (the older optics system was slower). The IIe seems to use the same kits as the GA IIx. That seems odd to me because the consumables cost is typically the largest part of the per run cost. So while you will save on instrument depreciation costs per run, those savings disappear when considering cost per Gb. Another way to look at it is that if reagent costs are indeed the same, it makes no sense to buy two GA IIe instruments. You would be much better off buying one GA IIx. It is only if your lab has a sequencing workload that cannot utilize a GA IIx full time that a GA IIe makes economic sense.

Please consider writing your representatives in Congress to support the Fair Elections Now Act (S. 752 and H.R. 1286); a bill that will greatly limit the damage done by the recent Supreme Court decision overturning a century of election law. Change Congress makes it easy to email your representatives. See the video below for one reason why this is important.

Update: Added video.

Earlier this week Life Technologies announced the next revision of their SOLiD platform, SOLiD 4. I don’t have all the details that I had for the Illumina HiSeq 2000, but here is what I do know: the system will produced 100 Gb of alignable sequence data on two slides per 14 day run. The sequence data will be paired-end, 50×35 base reads. Reagent costs for each run will be about $6,000. Since you need about 100 Gb of sequence to sequence a human genome, you’re looking at about $6000 in reagent costs per human genome. They also indicated that capacity for the instrument will increase to 300 Gb per run and the cost for reagents per human genome will be less than $3000 by the end of 2010. In comparison, the Illumina HiSeq 2000 reagent costs will be about $10,000 per human genome at its release with, by my calculations, a path to about $4000 per human genome (I have no idea what the time frame might be to reach the end of that path, but given this announcement by Life, it will likely be aggressive). You have to love the way competition drives down costs. Similar to Illumina’s announcement of a big HiSeq 2000 purchase at its announcement, Life announced that Ignite Institute would acquire 100 SOLiD 4 instruments as part of partnership with Life. Life also announced a major bioinformatics investment program as well as a physician education program through their Foundation.

Update: According to the press release, Ignite is “acquiring”, not purchasing, the instruments in “partnership” with Life. So it appears this is not an outright purchase of a large number of instruments. I have updated the text in the post to be more accurate.

So much for populist rage. We better be careful to not anger Wall Street tycoons.

There is a story about regional data centers in the Jan/Feb 2010 issue of St. Louis Commerce Magazine that includes a section on our Genome Data Center; the only regional data center to achieve LEED certification (and gold at that!). Unfortunately, the issue seems to only be available as part of a Flash application, so I cannot link to the story, only to the issue and tell you that the data center story starts on page 62 and the Genome Data Center section is on page 64 (it includes pictures!). This issue of the magazine also includes stories on cloud computing and Washington University in St. Louis Chancellor Mark Wrighton (and high-speed rail of course).

The National Cancer Institute (NCI) posted a couple stories that discuss, directly and indirectly, the Pediatric Cancer Genome Project. The first, St. Jude, Washington University Launch Genome Project for Childhood Cancers, is, obviously, about the project. The second is A Conversation about Sequencing Cancer Genomes with Dr. Elaine Mardis.

I’m not talking about Rob Lowe, but about the corrupting influence of money in politics. Watch the talk Lawrence Lessig recently gave at the conservative Cato Institute to learn how bad it is, and how it is likely to become much worse.

And for fun, watch Stephen Colbert’s take on it.

And finally, do something about it.

Update: Added Colbert video and link to Change Congress.

What should the Democrats learn from their fall from grace over the past year? There are a lot of opinions as to what exactly the recent losses mean and what the Democrats and President Obama should do. Two of the more interesting come from David Brooks in Politics in the Age of Distrust and Drew Western in Obama Finally Gets His Victory For Bipartisanship.

Today, St. Jude Children’s Research Hospital and Washington University School of Medicine in St. Louis announced a joint Pediatric Cancer Genome Project. This project aims to sequence tumor and normal genomes from over 600 pediatric cancer patients over three years. There is a press conference today (right now) at the National Press Club in Washington, DC (click on the 10 a.m. item in the DayBook on the left-hand side of the page). St. Jude’s will be supplying the tissue samples and The Genome Center will be doing all of the whole-genome sequencing on the samples. Genomic analysis will be done jointly between WU and St. Jude’s. It’s an ambitious project and personally I am very excited to be a part of it. You can find more coverage of the project in the press at the WU NewsRoom, GenomeWeb, Wall Street Journal, BusinessWeek, USA Today, Memphis’ The Commercial Appeal, KWMU (local NPR station), CBC, and the St. Louis Business Journal. You can find video interviews with some of the principles on the project’s multimedia web site.

Update: I have added links to press coverage as it has become available (and will continue to do so).

As stated in previous posts (Bioinformatics and cloud computing and Head in the clouds), I don’t think that cloud computing wins the cost competition with local resources. However, there are several reasons why an organization should consider cloud computing. Several of the reasons I present below are discussed in a great interview with Russ Daniels of HP at ars technica, Into the cloud: a conversation with Russ Daniels, Part I and Part II. If you are at all curious about cloud computing, it is well worth reading. (You may also be interested in the ScienceCloud 2010 Workshop.)

Peaks and valleys

The ability to dynamically provision computing resources is integral to the concept of clouds. Dynamic provisioning is often used by online retailers to account for variability in consumer buying. The retailer may have 20 servers that it maintains year round to service average purchasing but also dynamically add servers in the cloud to account for peaks in purchasing, e.g., around the Christmas holiday. In bioinformatics, there are often computational crunches before papers get submitted or before meetings or when a mistake in an algorithm is found and a large amount of calculations need to be redone (Miron Livny of Condor and Open Science Grid calls these “oopses”). Another type of dynamic provisioning involves varying levels of certain hardware architectures or operating systems as needed by current computational demand. For example, certain applications may require x86 and Ubuntu 8.04 LTS while another may require amd64/em64t/x86_64 and Ubuntu 9.10. If the utilization of each of these programs is cyclical, you can provision the exact system you want when it is needed. This can be done using something like Amazon EC2 or an internal cloud. Thus, dynamic provisioning allows IT departments to design their solutions for steady state operations but still meet computational needs during peaks.

Space, the final frontier

At universities all over the world there is a constant battle for space. Researchers are always seeking more and administrators are always miserly about allocating it. If your computing needs expand beyond your ability to house, power, and cool them, cloud computing offers a solution. While it may not be cheaper than if the space, power, and cooling was available and paid for out of your grant overhead, it will almost certainly be cheaper than buying your own land and building your own data center. Of course, what people traditionally think of as cloud computing, e.g., Amazon EC2, is not the only option here. There are collocation facilities and scientific computing resources, e.g., NCSA and Open Science Grid. The latter are normally acquired through a granting process.

Persistence pays off

Cloud computing is also very attractive because of its persistence. If I have my computing and storage in the cloud, I can access it from anywhere. When the power goes out at my office, I can use my phone to access the data. When my computer crashes, the computation is still running on the cloud. When my disk fails, my data is still in the cloud. Of course, the cloud does fail at times too. Amazon promises 99.9% uptime, or nearly 9 hours of downtime per year. Of course, if the cloud resources are pulling data from your site (something that may take more time than the computation with current solutions), when your systems go down, you’re still out of luck.