The OpenHelix Blog

Welcome to our Friday feature link dump: SNPpets. During the week we come across a lot of links and reads that we think are interesting, but don’t make it to a blog post. Here they are for your enjoyment…

• @reactome: Ver 3 of FlyReactome Knowledgebase released: http://tinyurl.com/388a8sh [Mary]
• Are your kids bored enough with their summer break that they might be into some science? Have them check out ‘Science reporting for kids!‘ from AAAS. [Jennifer]
• Scientific American does Personal Genomics. [Mary]
• Much tweet buzz about this paper on genomics patents hindering research and innovation. If you can’t access the paper, there’s also discussion of it here. [Mary]
• Cool (so to speak): the Ice Man genome is coming. (At least he has no worries about insurers denying him coverage based on his genome….).  Another example of archaeology needing genome tools too… [Mary]
• This just in from GenomeWeb: “The Data Center of the Future” [Jennifer]
• ROFL: What it’s like to own an Apple product. Heh. That said, people have already shown  up at our workshops with iPads, folks. Prepare your software.  Hint: the tools aren’t all working correctly now. [Mary]
• I know it’s wrong. But it did crack me up: the Lawn Gegnome Project. [Mary]
• UCSC Genome Browser downtime Sun Aug 1. Should be short. See announcement for mirror URLs, and I’ll also post them below:

http://genome.hmgc.mcw.edu/
http://genome-mirror.duhs.duke.edu/
http://genome-mirror.bscb.cornell.edu/
http://genome-mirror.binf.ku.dk/
http://genome.qfab.org/

As I’ve posted before, the next Biocuration meeting will be in Tokyo, Oct 11-14th. I recently got notified that they are now accepting abstracts for the meeting:

We cordially invite you to join us for Biocuration2010, the Conference
of International Society for Biocuration (ISB) and the 4th International Biocuration
Conference, is held in Tokyo, Japan, from October 11-14, 2010.

Abstract submission and registration are now open!

* abstract submission
http://hinv.jp/biocuration2010/abstract.html
* registration
http://hinv.jp/biocuration2010/registration.html

Currently abstracts are only being accepted June 1- July 14th and the organizers say authors will be notified by August 14th as to whether their abstracts have been accepted for presentation.

OpenHelix’s abstract was selected for presentation & I was really happy with all the comments, feedback and interest that we received – both from the poster presentation and the 15 minute talk we were able to give. If you’ve got a resource that you’d like to present, or get feedback on, from this group I highly suggest that you submit an abstract now!

Ok, terrible pun, I know. But the twittosphere was abuzz with the louse genome today.  I largely ignored it for a while, but then decided to go and look at the actual paper instead of the press coverage.

It is wild. Not only did they do the louse genome, but they did an endosymbiont it carries.  But there’s more!  There are “18 minicircular mitochondrial chromosomes” in this beast.

And quite honestly, I had no idea they spread these diseases:

Of the two forms, only the body louse has been implicated as a vector of human disease and is the principal vector of epidemic typhus (Rickettsia prowazekii), relapsing fever (Borrelia recurrentis), and trench fever (Bartonella quintana) (5–9).

I wonder if this would of use to anthropologists and archaeologists.  I have been unable to shake the story of the difference between the hair lice and the clothing lice that lead to insights on the origin of clothing.  Hmmm….

Much cooler than I expected.

Genome sequences of the human body louse and its primary endosymbiont provide insights into the permanent parasitic lifestyle June 21, 2010, doi: 10.1073/pnas.1003379107

If you haven’t noticed, we’ve started adding our tips of the week to SciVee and using the embed to embed them here. This allows you to view the video and share it on your web site or with friends. We’ve also created a “community” over at SciVee we’ve called “Genome Resource Training” where we will be gathering all these video tutorial tips along with any other video tutorials we find over at SciVee that train or introduce researchers on some of the huge amount of resources out there (click the “SciVee” icon above to visit the community). We’ve got about 8 tips over there now and another 8 or so videos from other sources. This community will only grow! So, come check it out, join SciVee and join our community! Of course you will _always_ find our tips here and much more on this blog, so keep us in your feeds and bookmarks and don’t forget to get some in-depth training with our tutorials! We are looking forward to a longterm and expanding work with SciVee.

We also now have a Facebook page, where we will be posting these tips weekly with an occasional ‘general-interest’ genomics link or two. So, please.. follow us there if you are on Facebook and ’share with friends!

I’ve mentioned before that personal genomics seemed to have hit a tipping point. Some of the evidence of that seems to be that the FDA and other regulatory agencies have taken a heightened interest in mass-market gene and genomics tests.

That is going to be the next step in our progress towards personal genomics and medicine, and one that if done right will make this part of our history a successful one. To that end, the Genomics Law Report has an interesting post: “Transparency First: A Proposal for DTC Genetic Testing Regulation.” His argument, make the registry mandatory, make transparency mandatory, is a good start.

There is also a debate going on (which I’m going to be a fence-sitter on for now) on whether the FDA should be governing these ‘Direct to Consumer’ tests. Decisiontree says no:

The controversy seems to have stirred the FDA to assert its authority – and that of physicians – over any and all medical metrics. As readers of The Decision Tree know, I have little patience for the argument that we need doctors as gatekeepers of our genetic information. This isn’t a drug, and this isn’t a device – it’s information about ourselves, as ordinary as our hair color or our waist size or our blood pressure – all things that we can measure and consider without a doctor’s permission.

Gene Sherpa says they got it all wrong:

This is not about getting access to your data.

Fine, you want a whole genome, go get it!

The FDA is not asking should people be able to go out and buy this. It is asking several other questions.

1. Is Interpretation of biometric data considered medicine?

2. Is DTCG analyzing biometric data and intending to give an interpretation of that data which indicates a disease a person has?

3. Should we regulate a system which has not given indication of their quality control if they are indeed intending to provide medical diagnosis?

4. Are these methods of obtaining human samples to derive biometric data for the intent of analyzing and providing information about disease considered medical devices?

All three are interesting and informative reads. Just thought I’d point them out. (hat tip on those last to to Daily Scan).

Please indulge a long post from a personal perspective, what genomics is about to do for _me_. This is information that many, if not all, of our readers already know. I’ve been researching and working in either experimental biology or genomics for over 20 years. Ever since the beginning of the Human Genome Project , which coincidently started the same year I started my Ph.D. program, into my postdoctoral research at EMBL and now my work at OpenHelix, I’ve known that someday personal genomics was going to impact me, and millions of others, in a big way. Yet, it has always felt that it was one of those things that would be a decision I and we as a society didn’t have to make until we turned that corner that seemed always “just ahead.”

But now I think we’ve turned a corner. It feels, to mix metaphors, that we’ve hit a tipping point. The Human genome project, the mapping and sequencing of the/a human genome from 1990 to 2003, cost approximately 2,700,000,000 dollars (that’s 2.7 billion, I wanted to get all the zeros in). Celera did the genome for 300,000,000. The cost of sequencing an entire human genome has been plummeting ever since. In 2007, the cost of sequencing the genome of James Watson (co-discoverer of DNA) was about 2,000,000. The today cost is about 10,000. Complete Genomics and other companies are on the march to quickly reducing the cost of sequencing a genome under 1,000.

Let me graph the last 8 years for you, mind you, this is starting from the 300,000,000 number, not the 2.7billion, because that graph would be a straight line down.

So, within a year, the cost of sequencing your, my, genome will reach 1,000. If not less. We’ve seen this coming for years now, and it’s upon us. But what does it mean?  A lot of data. But data means nothing without context and analysis. Sequencing my genome would be a waste of 1,000 dollars if I gleaned nothing from it.

Yet, even that seems to have turned the corner from a few tidbits of genetic information to a steady steam and the beginning of a flood.

You know you’ve turned a corner when a genomics testing company begins to offer genetic tests to the mass market through Walgreens. There’s enough context in that data to make money from it, or so they hope. You can be sure the corner is safely behind you when the FDA tells Pathway Genomics and Walgreens that they will need to hold off while they make sense of the regulatory implications. Genomic ancestry test are are also gaining is usability… and scrutiny.

It was the recent Lancet paper on the clinical analysis that seemed to be a tipping point, not for me or those in the field. Genomics has been on my radar since 1988, but for society. I blogged about the paper and it’s use of genomics resources such as GVS, dbSNP and others. In the paper, the researchers did a thorough clinical assessment of an individual’s genome. We’ve brought down the cost of sequencing, now we are learning how much it’s going to take to assess that data from a medical point of view, and importantly, what we can learn from it.

What can we learn from it? I read this paper again from a personal perspective now. Could I learn something from sequencing and analyzing my genome, and if so what. My answer came to this: yes, I could learn something and in fact enough that I’m not convinced that as soon as that sequencing gets down to a 1,000 or lower (and is a high quality sequence , I’m going to do it.

There are three things I see from this paper that one could learn from assessing their genome: prevention, early detection and therapy. I believe the former will be, for most people, something they already know and their genome sequence will tell them nothing new. The other two could be a wealth of information they will want, even need, to know. You’ll notice I left off ‘cure.’ I saw nothing in this paper, and nothing on the near horizon, that suggests to me that our genome sequence data will help with curing anything. Perhaps, just not much. Yet, the possibilities of early detection of disease and personalized drug treatment are tantalizing.

Recently there was much buzz in the #bioinformatics twittersphere over this blog post by Sean Eddy: The next five years of computational genomics at NHGRI

It is a very nice post about some exciting prospects for the future.  The idea of planning “explicitly for sustainable exponential growth” is wise.  There will be no abatement of the flow of data at this point–it’s no longer a big bolus of one species data, or one type of project.  The taps are wide open now, and we just keep adding more taps.

I also love the idea of “democratization“.  In part, it includes:

….To enable individual investigators to make effective use of large datasets, we must create an effective infrastructure of data, hardware, and software. NHGRI has extensive experience in big data, and can lead and catalyze across the NIH….

Now, I know this is a snippet of some thoughts–there may be more to it in the actual planning meetings on this.  But it pushed my buttons because it sounds a lot like what we always hear about big data projects: build it and they will come.

It got a little better in another segment:

Spur better software development. Traditional academia and funding mechanisms do not reward the development of robust, well-documented research software; at the same time, the history of commercial software viability in a narrow, rapidly-moving research area like computational genomics is not at all encouraging….

Well-documented research software.  Sigh.  We probably read more documentation than most people. And even the good documentation can be brutal. Dated. And not particularly effective. But still–if nothing else, please reward time spent on documentation….

But what is missing for me from this–and not just this, but most of these big data types of projects–is a real commitment to outreach and support for end users.  Formal, organized, supported, rewarded, outreach.  Sometimes there is a place to write to with questions.  But we probably send in more questions to projects than most people too–and the success rate for answers varies widely.  But even when we get good answers–that’s not enough.

I know funding is hard.  We can’t fund everything.  Databases and software project have to struggle to even persist.  Curation is frequently not valued enough.  And often curators are expected to do outreach as just one of their tasks…which pushes outreach even further down the priority list.  But without dedicated outreach–formal, quality, active outreach–databases and software projects won’t have so many users, and not many effective users.   Which will make funding agencies wonder if they should keep supporting them.  Which…well, you can see where this spiral goes….

What bugs me, I guess, is essentially this: Nobody speaks for the end users. There’s really no one in these types of meeting that really speaks for the consumers of this software and this data.  I mean people who aren’t directly attached to the data production and management.   The project teams think they are thinking about the users.  They really want users.  But ur not doin’ it rite.

I would like to see outreach and end user support valued, required, and really done right.  No matter how  much hardware and documentation you throw at these projects, if people 1) don’t know it exists, and 2) have no idea how to use it, the project will not yield all the results that it could. A marker paper is nice.  But it’s not sufficient, folks. And it’s nice to have the high-end team members talk at conferences. But that reaches only a tiny subset of the users or potential users.  And another thing about that: a lot of times people are hesitant to ask what sound like naive questions to the high-end representatives of these projects.  I’m jes’ sayin.

Yes, this is fairly self-serving for me to say.  But we see the users when we do outreach.  They crave it.  They love it.  We’ve been lucky to be a part of some great projects that do outreach right.  We have seen it work.  It should be Standard Operating Procedure on software and database projects.  Not an afterthought.

If you haven’t been reading the news, the draft sequence of the Neandertal (or is it Neanderthal, spell check won’t take the former) was released and published in Science today. There is a lot of fascinating stuff over there. Still reading it. Of course the big news, the stuff thats flying through the news, are non-African genomes are 1-4% Neanderthal. This seems to conclusively settle the question that yes, we are a little bit Neanderthal and we didn’t replace them, we absorbed them with some interbreeding. Perhaps not so completely as that but definitely some admixture going on. As Razib of Gene Expression points out, it’s fascinating to watch how quickly, in the face of data, the paradigm has shifted. (great post and discussion, should read it).

As Razib points out, and as you can read in the announcement at UCSC, the UCSC Genome Browser now has the draft data up in the hg18 genome assembly. Like the coding region allelic differences data, selective sweep data, etc. With the Neanderthal data now being in the UCSC Genome Browser and other data sources, we can pull apart that data, analyze it.. (and you know I’ll be putting my personal genome in a comparative track when I ever get it. Just curious ya know).

(btw, there is an interesting photo, copyrighted… so I won’t post it here, you might want to check out. There’s an interesting story there, how our illustrations of Neanderthal have evolved over the years to be more ‘humanizing’ as we learn that they made tools, had culture and now… are part of our ancestry…”)

I am itching to go play there and see what I can see, as I am sure many scientists are. It’s also fascinating to be in this world of huge amounts of data coming quickly. I think a lot of paradigms will be shifting for a while.

Welcome to our Friday feature link dump: SNPpets. During the week we come across a lot of links and reads that we think are interesting, but don’t make it to a blog post. Here they are for your enjoyment…

• If you are on the coding end of things in Bioinformatics, you might want to take a look at Yokofakun, a bioinformatics blog [Trey]
• If you want to see a hilarious take-down of junk science in medicine:
  
  That’s from the Brits Mitchell and Webb, if your vegetarian you might not want to watch this .  [Trey]
• The buzz of the personal genomics twittosphere this week was this terrific article at Genomics Law Report, by Dan Vorhaus: Mapping the Personal Genomics Landscape [Mary]
• The bunny browser hops along!  European Rabbit Genome Browser released at UCSC Genome Browser [Mary]
• I think this is interesting to think about, but not sure which I am: Evolution of science from Lauren Urban at the The Scientist.com [Jennifer]

• Not the penguin you think it is: Comparative Functional Genomics: Penguin vs. Bacterium at Byte Size Biology. Things that make you go: huh. I always figured binary was too limited since we run on 4 bases, now it looks like programming is backwards. [Mary]

• For those of us who have had research papers reviewed, just a bit of humor. [Trey]

The Lancet paper, Clinical assessment incorporating a personal genome, has held my fascination this weekend (yes, I read it at the beach). Mary posted Friday and again Saturday on the paper and related NPR segment. It feels to me to be a seminal paper, though I do agree with Daniel at Genetic Future, there are a lot there we still don’t know. A large portion of the variation is in non-coding regions, and thus predictions and propensities are hard to come by with the available analysis. In fact, as he pointed out, many of the coding region variations have little information as to their effect on disease. I would add also that even if we get to that holy grail of $1,000 to sequence a personal genome, this kind of extensive analysis would still be time and cost-prohibitive for the vast majority of sequenced genomes.

Yet, as with all early steps in science and medicine, there’s missing pieces, large gaps and huge efforts (think “space travel,” “computers,” “microwave ovens,” “internet,”) that over time become inexpensive and commonplace (ok, so the former isn’t necessarily “inexpensive”). Sequencing genomes will become inexpensive before the analysis does, but both will come. And I think this paper is pointing to that future.

The other hurdle to large scale personal genomics I see (of course) is the understanding and use of the genomics and data resources. The authors use a large (and excellent, in my opinion) suite of genomics resources to do obtain data and do their analysis. I’ll list them here with links in alphabetical order:

dbSNP (T)
GVS (T)
HapMap (T)
HGMD
OMIM (T)
PharmGKB
PolyPhen
PubMed (T)
SIFT
UniProt (T)

All of these resources have a wealth of data, but even then, that is a lot of analysis and familiarization that is needed with each tool. Each tool does have documentation and tutorials, and of course OpenHelix has tutorials on many of the ones mentioned (those with linked “T”s after the name). Still, this one analysis took a large number of tools and familiarization.

The paper does have a pretty good figure (figure 1) outlining the analysis process. For example, they SIFTed the genome to find gene-associated, non-synonymous, rare and novel and disease associated variations and then analyzed those using dbSNP, HGMD, OMIM and PubMed to analyze something like HFE2 which might have an association with Haemochromotosis. One of my quibbles with the paper, as often is with these papers, is that there isn’t a good methods ‘walk-through’ of the paper using something like Galaxy or Taverna in a history or workflow that would help reproduce the analysis.

We also have a tutorial I’d like to point you to, one that walks through a similar process and teaches users the basics of walking through that process. You can find this tutorial here, it’s free and publicly available. The tutorial walks the user through the analysis of a gene variation, in this case in the CYPC9 that effects an individual’s response to Warfarin. There is a similar variation (different gene, affects same drug response) in the paper. The tutorial uses the NIEHS SNPs site to get an overview of the variation including SIFT and PolyPhen predictions, then to the UCSC Genome Browser to find an overview of the region, walks through the dbSNP information and does a quick tag SNP analysis using GVS. That tutorial is only one very small step in what will have to be a immense education into genomics and genomics resources.

That is all to point out that the paper is an fascinating first step, and as a first step suggests the gaping holes we will have in bringing personal genomics to medicine.

Ashley, E., Butte, A., Wheeler, M., Chen, R., Klein, T., Dewey, F., Dudley, J., Ormond, K., Pavlovic, A., & Morgan, A. (2010). Clinical assessment incorporating a personal genome The Lancet, 375 (9725), 1525-1535 DOI: 10.1016/S0140-6736(10)60452-7