XKCD

Apologies for the lack of blog posts. I blame the laziness induced by summer vacation. That said, I enjoyed this recent XKCD post. Ties in nicely with a previous "Correlation" comic.

On a somewhat related note, if you ever need to incorporate XKCD comics into your R code for some reason (I'd be interested in hearing what that reason is), there's a clever new package out called RXKCD just for this purpose.

What's my age again?

As a bioinformatics student, most of my studies in biology thus far have focused on molecular mechanisms, genetics, and diseases. One "disease" that I find fascinating but know relatively little about, is aging. With talk of telomere lengths and "fountain of youth" pills, I find the topic of aging to be interesting, but haven't seen much of my sort of computational research applied to the subject. For this reason, I highly recommend all you data miners out there to check out a recent paper in PLoS One by Sven Bocklandt and colleagues at UCLA. The concept is fairly simple: input DNA methylation patterns (labeled with age), build model, predict age. Result: "we built a regression model that explained 73% of the variance in age, and is able to predict the age of an individual with an average accuracy of 5.2 years". The initial model was based on 34 sets of male identical twins, then validated in 60 additional people. It would be interesting to see if lifestyle factors (e.g. smoking or drinking, which can affect DNA methylation) are important covariates in their model. Kudos to all those involved for this simple and elegant yet effective study. 
Original Paper: Epigenetic Predictor of Age

cell phones --> cancer?

In case your mother hasn't forwarded it to you, or your Facebook feed hasn't been blowing up with links to articles like this, I thought I'd post it here. The summary: a panel of 31 scientists from 14 countries have concluded that cell phone use may be linked to cancer. First off, getting 31 scientists to come to a definitive conclusion about anything is sometimes difficult, so in a sense, this vague statement is not surprising. But as a scientist, this conclusion doesn't mean much (a huge number of environmental factors "may" be linked to cancer). While I frankly have not seen the raw data or published study, from what I've seen in the media, no odds ratios or relative risks have been reported. Sure there was an increased risk of gliomas in heavy cell phone users (original article), but what was the sample size? Where there confounding factors? Perhaps I have been reading too many epidemiological studies recently, but I believe these reports have had a greater PR impact than any scientific impact. Even the W.H.O has only classified cellphones as Category 2B (possibly carcinogenic, along with...coffee). My take: Until we start seeing more functional validation studies...calm down people. And journalists, please report your data responsibly.

WHO/IARC Press Release
Cellphone Radiation May Cause Cancer, Advisory Panel Says
by Tara Parker-Pope and Felicity Barringer

Nanotech + Sequencing

With Illumina's recently released TruSeq v3 Cluster kits producing up to 600 Gb of data per run (!), there's no doubt that we are getting more information and coverage for our hard-earned research dollars. While the quality and depth of sequence is increasing, this doesn't really matter to clinicians. Noblegen Biosciences, a Massachusetts startup is trying to change that. While no industrial-scale prototype has been developed, the company, funded by the National Human Genome Research Institute, is building on nanopore-genome sequencing technology. With a goal of being able to accurately call 1000 bases per second (theoretically scaled up to cover an entire human genome 30x in 15 minutes!), the company aims to bring fast and cheap sequencing to the clinic. No word on technology specifics, or how they plan to analyze all this data in a speed/manner that is reflective of the quick sequencing time. It will also be interesting to see how their technology compares to that of Oxford Nanopore, which has not released any commercial product. While it is still early days, I'll be keeping an eye out for future developments.
MIT Technology Review Article by Katherine Bourzac: Simpler Genome Sequencing

Where is all that money going?

An online opinion piece by David Bornstein at NYTimes.com is generating some interesting discussion on the gap between academic research and the development of new drugs. While hundreds of thousands of biomedical research papers are being published each year, and millions of dollars are being spent on research (by both government funding agencies and pharmaceutical companies), there were only 21 new drugs approved by the FDA last year. There is clearly a need for more "translational" research, as addressed by Francis Collins' recent push for a federal drug development center. While researchers from all sides are making significant scientific progress, there are some glaring social issues that need to be fixed. Kudos to the author for bringing some of these issues to light. Be sure to stay tuned his follow-up article. 

Helping New Drugs Out of Research's 'Valley of Death'

Let the games begin

Earlier today, Pacific Biosciences (Menlo Park, CA) announced that they are now shipping their commercial single molecule, real-time PacBio RS sequencing systems. In the press release, PacBio claim that their new technology "allows customers to obtain results in less than a day", compared to the week+ it takes to obtain data from other sequencing technologies. While papers, talks, and videos of PacBio technology has certainly created a buzz among researchers, it will be interesting to see how this step affects business. NASDAQ:PACB stock closed at 11.60 today, lower than their $16 starting share price last October when they IPO'd.

NGS in the clinic

Not quite there yet, but it's a step in the right direction: Whole-Genome Sequencing Reaches Clinic. With a flurry of recent papers on tumor sequencing, it's not surprising that the clinicians predict cancer to be the first major application for NGS in a clinical setting.

As we move forward with the technology, I find it interesting to see how people handle the information that is generated. In the case reported here, researchers did not seem prepared to follow up on this issue:
"Genotyping of the patient's mother and absence of a cancer history in the father suggested that the TP53 mutation had arisen spontaneously rather than being inherited. However, the patient could have passed it on to her children. Studies by Wilson and colleagues along with previous research indicated that defects in TP53can cause or promote cancer.
The researchers reported that they communicated the potential risk to next of kin, encouraging them to seek genetic testing and counseling. However, a confidentiality "firewall" included in the research protocol prevented the research team from learning whether the children acted on the recommendations."

As was seen with direct-to-consumer genomics, it's not always clear how patients, physicians, and family members will use the data, and it is important for researchers to consider the implications of releasing such information prior to actually doing so.