Rub the lamp and make a wish....

A recent article by Allen-Brady , Wong & Camp (2006) in BMC Bioinformatics details a new program called PedGenie which provides a java (GUI) interface to performing association and transmission disequilibrium tests (TDT).

Personally I have mixed feelings about GUI interfaces for analysis, firstly they mean that it is hard to make work reproducible, which is an essential part of any investigation (Gentleman 2005). More importantly because people are often very familiar with point and click interfaces they can go ahead and perform their analysis witout necessarily understanding whether it is appropriate to perform their analysis, or even worse they'll perform every possible test they can and think that because they've found something "significant" they have found an important front. This may come acorss as elitist, but its really not meant to be, since when performing statistical analysis one needs to be very careful and precise about what you are doing.

On the flip side GUI's provide a relatively easy interface to what can be a sometimes impenetrable field, since there is often a steep learning curve to becoming proficent in a given statistical package, OS or scripting language to the extent that one can perform their analysis in a reproducable manner.

At the end of the day its about finding a balance between needing to getting things done, and hey, if it means theres one less person banging on my door needing their hand held to perform their analysis then its not all bad!

References

• Allen-Brady K, Wong J, Camp NJ (2006) PedGenie: an analysis approach for genetic association testing in extended pedigrees and genealogies of arbitrary size BMC Bioinformatics 7:209
  
• Gentlemean R (2005) Reproducible Research: A Bioinformatics Case StudyStatistical Applications in Genetics and Molecular Biology 4:2
  
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(m)utterings....

A rather provocative article appeared in the European Journal of Human Genetics recently from Terwilliger & Tero Hiekkalinna (2006) "An utter refutation of the 'Fundamental Theorem of the HapMap'". The article provides a mathematical proof that the theorem behind the HapMap is flawed.

It is often assumed that the power to detect association is directly proportional to the correlation coefficent (r²) between the disease locus B and the marker locus A, but this is not the case. This makes intuitive sense, for the power of testing a proxy marker to be equal to that of testing the disease polymorphism itself, the allele frequencies must be identical. In such cases p_a = p_b (i.e. r² = 1), if the allele frequencies are not the same the there will be instances when the marker allele (a) occurs with the 'normal' allele B. The paper claims that because this assumption is flawed then it will not be possible to utilise LD mapping to sucessfully map disease polymorphisms. This may be true, but there is evidence that the structure of LD in the human genome is not uniform, there are some regions of strong LD where D' and r² are high, and others where it is very weak. As a consequence there will be some regions where LD mapping will work, and others where it will not.

The wording is very strong in the paper, and is rather acerbic in its tone as exemplified in the title "Utter" refutation and and the inverted commas around the Fundamental Theorm (which to the best of my memory I have never heard of it being referred to as such, although it is implicit in the strategy of the HapMap).

To quote someone else "The devil is in the detail" and what is written above is far from all that is covered in the paper, but as it is freely available at the EJHG web-site, head on over, read it and make up your own mind.

Terwilliger J, Hiekkalinna (2006) An utter refutation of the 'Fundamental Theorem of the HapMap' Eurpoean Journal of Human Genetics 14:426-437.