Tag Archives: genetics

Farming and allergy prevention could be caused by Berkson’s fallacy

Lets look at the Wikipedia definition first

Berkson’s fallacy is a result in conditional probability and statistics which is often found to be counterintuitive, and hence a veridical paradox. It is a complicating factor arising in statistical tests of proportions. Specifically, it arises when there is an ascertainment bias inherent in a study design … The most common example of Berkson’s paradox is a false observation of a negative correlation between two positive traits, i.e., that members of a population which have some positive trait tend to lack a second.

The original example is developed unsing the example of an hospital based group of patients. The only thing to know is that diabetes is a risk for cholecystitis in the general population.

Any given hospital in-patient without diabetes must have another disease (otherwise he would not be there), for example cholecystitis. And by definition this will be cholecystitis without diabetes caused by some other risk facors (female, fat, forty…) So in this group of in-patients there maybe a spurious negative association between cholecystitis and diabetes.

My example here is with families who are living on farms. Since around 1960  [Leynaert 2001] there is this interesting observation that farming families have less allergy, an effect that I found back in 1989 and that is most likely a healthy farmer effect.
This selected farm population has a lower allergy prevalence and of course their children will also have less allergy. All the negative correlations (that are interpreted as protection) with endotoxin, microbiome, etc could be caused by Berkson’s fallacy. The observation will also be even replicated as the same selection criteria are also present in the replication sample.

Many more cognitive biases could also be involved: anchoring, availability cascade, confirmation and expectation bias and of course: law of the instrument.

Finally! 23 and the FDA warning

Quite some time passed already since my last post (to be exact, more than 5 years) but now there are good news. The FDA issued a warning letter on the 22nd

… The Food and Drug Administration (FDA) is sending you this letter because you are marketing the 23andMe Saliva Collection Kit and Personal Genome Service (PGS) without marketing clearance or approval in violation of the Federal Food, Drug and Cosmetic Act (the FD&C Act) … However, even after these many interactions with 23andMe, we still do not have any assurance that the firm has analytically or clinically validated the PGS for its intended uses … Therefore, 23andMe must immediately discontinue marketing the PGS until such time as it receives FDA marketing authorization for the device …

The response is quite flimsy. Yes, there may be negative side effects of genetic testing and of course tests need to validated first. Slate may be correct that the FDA’s battle with 23andMe won’t mean anything in the long run but now at least, we are set back to science, yea, yea.

Keep secret

There is a new Edge Special Event about the Hillis’s question “WHO GETS TO KEEP SECRETS?”

The question of secrecy in the information age is clearly a deep social (and mathematical) problem, and well worth paying attention to.
When does my right to privacy trump your need for security?; Should a democratic government be allowed to practice secret diplomacy? Would we rather live in a world with guaranteed privacy or a world in which there are no secrets? If the answer is somewhere in between, how do we draw the line?

With all the wikileaks hype over the last year, the Edge essay is la perfect supplement to our last paper about anonymity in genetics – check out BMC Ethics “Caught you: Threats to confidentiality due to the public release of large-scale genetic data sets“.
What we didn’t mention in this paper are more complicated statistics like stochastic record linkage – more on that in RJournal 2/2010, p.61 ff

PLINK: Bug or feature?

I am struggling now for 4 weeks with some unusual behaviour in PLINK that gives me different results with a trait of the alternate phenotype files either by calling that trait directly

plink –file mydata –tdt –pheno pheno2.txt –mpheno 1

or from a loop over all traits

plink –file mydata –tdt –pheno pheno2.txt –all-pheno

It seems that I am working with different numbers at both occasions – click to enlarge the log Continue reading PLINK: Bug or feature?

Evolutionary legacy

It’s an exceptional good science book – Cancer, The evolutionary legacy – by Mel Greaves. Having written last year a grant application about resequencing of lung specimens (and more recently a correspondence letter about the lung cancer genome that updates our earlier 31 events to 22,910) Continue reading Evolutionary legacy

Genome Browser now with GADview track

Just reveived an email from the creators of the Genetic Association Database (GAD)

… Your published genetic association study has been included in the recent update of the NIH based, Genetic Association Database (GAD), the database of human genetic association studies. Continue reading Genome Browser now with GADview track

Want to work with you

Over and over I am flooded with emails like

Let me introduce myself to you. I am xxxxxxxxxx, completed M. Sc Micro Biology. At present I am working as a research Fellow in Centre for xxxxxxxx, xxxxxxxxxx, India. How are you sir? I am your student. How can I mean, in January 2005 you come to India. At that time your engaged some class to us in xxxxxxxxx College, Axxxxxxxx. Presently I am working on Genetics of “xxxxxxxxxxxx” under the esteemed guidance of Dr. xxxxxxxxxxx and Dr. xxxxxxxxxx. I am very much interested to do PhD. Herewith, I am sending my curriculum Vitae as attachment to your kind perusal. I assure you, I shall work with at most devotion and sincerity to give you satisfaction and also I am confident that I can lead PhD successfully with the experience I gained during my research work at xxxxxxxxx. Given a chance I will prove my caliber.

Continue reading Want to work with you

Gene lists by automatic literature extraction

Just found at the HUM MOLGEN bulletin board a link to Fable, a new automated literature extraction system. Fable is pretty fast and can output gene lists. Sure, the screenshot below shows only those genes that I mentioned in the abstract, but this is not so bad as the most important genes wil be placed there.
BTW, the number of reviews on asthma genetics have been falling to less than 50% after closing the Asthma Gene Database. Maybe this new service will help to re-establish the former output of reviews ;-) yea, yea.

fable.png

On the “Self”

If I would ever find the time, I would write a book on the “self”. Inspired by the Eccles/Popper book that I bought as a student, I always wondered how different the self is being defined in sociology, psychology/psychiatry, philosophy and theology.
As my current focus is more on genetics and immunology, I found a paper by Francisco Borrego on the “missing self” quite interesting as it highlights the genetic self is determined mainly by MHC class I molecules, where only NK cells transfected with H-2Dd were able to confer resistance for being self-attacked. It would be nice if other disciplines could also provide such simple answers, yea, yea.

Addendum

I have another suggestion: Zfp608 protects mouse mothers against immune-mediated attack by fetal cells.

Is there also a “digiself“?

Our identity has, for many years, existed quite independent of our physical incarnation in government, financial and other institutional databases. We are not real to the bank or other authorities unless we can produce something that links our physical self to our “real identity” in their database. We have many versions of this digital identity – or digiSelf, as I like to call it – spread among many databases, each with its unique characteristics, and inferred behaviours. Each one is more real to the institution – and ironically, to the people in that institution – than our physical self, what we consider to be our real self.