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March 2012

  • Neutral calories?

    755 days ago

    Yoni Freedhoff dissects the recent study on how eating chocolate is making you thinner:

    So to recount – basically here we have a study with no controls whatsoever rendering conclusions impossible, authors who rather than mention their study’s pretty much insurmountable methodological limitations instead made up a “growing body of literature” on magic calorie neutral or negative foods, a press release that spins it all as fact and as a result, as of early this morning, less than 24 hours after publication, there were already 423 chocolate makes you thin stories on the newswire to further misinform an already nutritionally confused world.

    It does remind me of the science news cycle comic, although in this case even the underlying scientific methods are questionable.

  • A Primer on Complex Trait Genetics, April 4th

    755 days ago

    Harvard Catalyst is offering another primer on complex trait genetics next Wednesday, April 4 at MGH (8:30-4:30, Simches Research Building, Room 3.110). Registration is required. The program looks exciting:

    This event is sponsored by the MGH Clinical Research Program, the Center for Human Genetic Research, the Broad Institute of Harvard and MIT, and in partnership with the Harvard Catalyst.
    Are you able to keep up with the changing face of genetic research? Have you heard of disease areas that have seen explosive growth in genetic discoveries in the past year? This is an excellent opportunity to learn the essential elements of complex trait genetics and gain the latest insights from expert faculty from the Center for Human Genetic Research and the Broad Institute of Harvard and MIT.

    8:00-8:30am – Registration and Continental Breakfast
    8:30-9:15am | David Altshuler, MD, PhD: Introduction of Complex Trait Genetics
    9:15-10:00am – Jim Gusella, PhD: Mendelian Traits Focusing on Methods, Modifiers, and Implications for Complex Traits
    10:00-10:45am – Benjamin Neale, PhD: Resequencing
    10:45-11:00am – Break
    11:00-11:45am – Mark Daly, PhD: Inflammatory Bowel Disease Genetics
    11:45-12:30pm – Christopher Newton-Cheh, MD, MPH: Translating Findings from Human Genetics to an Improved Understanding of Blood Pressure Regulation
    12:30-1:30pm – Lunch on your own
    1:30-2:15pm – David Beier, MD, PhD: Mouse Models as Tools for Follow up of Human Genetics
    2:15-3:00pm – David Milan, MD: Zebrafish as a Model of Human Disease
    3:00-3:45pm – Sean Wu, MD: Human Stem Cells as In Vitro Models for Genetic Discovery
    3:45-4:30pm – Panel Discussion

  • PQG Training Grant Retreat April 6th

    759 days ago

    The Program in Quantitative Genomics is running another training grant retreat on April 6th from 1:00-4:30pm.

    The retreat provides a great opportunity to share your work with the PQG Faculty and your peers and get feedback, and builds on the success of last year’s retreat with many excellent talks and a stimulating discussion.

    Lunch will be provided — and a happy hour wraps up the day. Please send your abstract to Shaina Andelman by Monday March 26 (sandelma@hsph.harvard.edu).

  • Personalized medicine taken to the next level

    760 days ago

    The Snyderome — an attempt to link biochemical fluctuations in a single patient to his genome — has received a lot of attention, and rightly so.

    Between ‘private’ mutations and data generated for an individual patient ‘personal genomics’ eventually we will have to figure out what the data means just within the context of that one patient. George Church’s comment provides the best perspective on this, I think:

    “But one response is that it is the perfect counterpoint to correlative studies which lump together thousands of cases versus controls with relatively much less attention to individual idiosyncrasies,” Church says. “I think that N=1 causal analyses will be increasingly important.”

  • A different personal -ome

    764 days ago

    Attila Cordas introduces the Personal Proteomics site, using mass spec as the Illumina-sequencing distal equivalent in this particular omics field:

    I think what we have now present on Proteome Cluster does answer our first question, namely figuring out the basic bioinformatics of personal proteomics, n=1. Our second question is really where the biological journey begins: what does all this data mean, how can the results interpreted in the context of one individual

    Definitely a project worth following.

  • Rare99X Exome-seq deadline

    764 days ago

    The Genomics and Pathology Services at Washington University in St. Louis School of Medicine is offering support to tackle rare diseases:

    Do you have a patient population poised for sequencing, yet lack the funds or expertise to carry out the testing? Do you have specific families with a large pedigree and strong suspicion for a genetic cause that await whole exome analysis? Do you have compelling research ideas to solve a rare disease by exome sequencing?

    The deadline for letters of interest is April 2nd, with proposals being due on June 1st.

  • Post-publication reviews

    766 days ago

    Joe Pickrell’s great analysis of a controversial paper describing non-canonical RNA editing in human has received a lot (and well-deserved) attention already. He concludes that almost all editing sites are artifacts, most strongly supported because

    …mismatches to the genome at RDD sites occur almost exclusively at the ends of sequencing reads.

    What is even more interesting to me, though, is that the scientific discussion happens on blogs rather the primary publication sites. Take Heng Li’s comment for example which taught me more about aligners and how to evaluate results than most review articles ever did.

  • Crowd sourcing

    766 days ago

    Sometimes colleagues wonder what the point in tools like Twitter might be, and why we’d waste our time with it. A recent interaction with Neil Saunders just reminded me how useful new collaborative ways can be.

    We had noticed a strange cyclical bias in probe intensities from the 450k Illumina Methylation chip seemingly related to the Sentrix position, but had written it off as a potential problem with uneven distribution of chemistry… until Neil mentioned seeing the same phenomenon in an independent analysis.

    Crowd sourcing

    Neil kindly summarized his findings, and all of a sudden we have a much better overview of a potential technological problem and can account for this in future workflows.

  • Effectiveness of sequencing workshops and seminars

    768 days ago

    Titus Brown on teaching sequencing courses effectively:

    Right now, I think it’s too much effort for too few students & little professional impact for me to continue with things past 2013: I don’t want to just affect a few dozen people for the amount of effort we’re putting into this. So… is there a way to scale?

    The cost/benefit-ratio is something we have been struggling with as well. At some point you need a dedicated admin team to ensure even just two-day workshops run smoothly, and the immediate benefit isn’t always entirely clear. Good news is that this is widely recognized by now, and initiatives like Khan Academy are driving the development of better infrastructure and course delivery options.

  • One of R's best features

    769 days ago

    .. has to be ggplot2, and I nearly missed the new version. It adds a number of new plots, cleans up the handling of labels and axis transformations, and allows us to finally add photos of team members to graphs:

    One of R's best features
  • Big data keeps changing

    772 days ago

    Normally not a fan of top ten lists, but this one from Titus Brown comes with tons of additional comments, a good summary of the challenges to research computing environments and great insights:

    I think about it like this: generating hypotheses from large amounts of data isn’t that interesting — I can do that with publicly available data sets without spending any money! Constraining the space of hypotheses with big data sets is far more interesting, because it gives you the space of hypotheses that aren’t ruled out; and its putting your data to good use.

    And I wholeheartedly agree about one of the main challenges:

    We were delayed in some of our research by about a year, because of some systematic biases being placed in our sequencing data by Illumina. Figuring out that these non-biological features were there took about two months; figuring out how to remove them robustly took another 6 months; and then making sure that removing didn’t screw up the actual biological signal took another four months.

    Go read the whole thing, going to keep you thinking for quite a while.

  • Visualizing genomic alterations

    773 days ago

    Stumbled over the Gitools framework on the Vizbi 2012 conference site their tools for visualizing and manipulating information on genomic alterations look particularly useful:

    One of the advantages of having different dimensions in the same heatmap, like for example Copy Number Alterations (CNA) and Expression in the same file, is that after filtering or sorting on one dimension (e.g. CNA) it is possible to observe the effect of this filtering or sorting on another (gene expression changes).

    We have been looking into the distribution of variants across pathways independently, but being able to automatically filter for mutually exclusive mutations should make our lives easier:

    The rationale behind that observation is that once a gene involved in a particular critical pathway is altered, a second alteration affecting the same pathway does not confer a further selective advantage to the cancer cell.

    Visualizing genomic alterations
  • The complexities of cancer

    773 days ago

    Discover Magazine has a great summary of a terrific new study on tumor evolution published in NEJM:

    Swanton found that even the primary tumour was surprisingly varied. He found 128 mutations among the various samples, but only a third of these were common to all of them. A quarter of the mutations were “private” ones – unique to a single sample.

    The tumour had also split down two evolutionary lines. One area – part of R4 in the picture – had doubled its usual tally of chromosomes and seeded all the secondary tumours in the patient’s chest. The other branch had spawned the rest of the primary tumour. Even though this tumour looks like a single mass, whose cells all descended from a common ancestor, its different parts have all evolved independently of one another.

    Not exactly good news from a personalized medicine point of view — for advanced tumours this means at the very least getting multiple biopsies to determine the right treatment combination.

  • The Gorilla genome

    773 days ago

    Kerri Smith comments on the just published Gorilla genome. I particularly like Wolfgang Enard’s quote:

    But there is not much point without data on behaviour and physiology. “We want phenotypes too”, he says.

    While sequence and data analysis cost make it feasible to sequence thousands of species the real value is in linking this information to differences in phenotype.

    Update: David Winter describes why it is expected that some of our genes are more closely related to their Gorilla counterparts than those of the chimp.