Welcome to the APSampler's den!

APSampler is a tool that allows multi-locus and multi-level association analysis of genotypic and phenotypic data. The goal is to find the allelic sets (patterns) that are associated with phenotype. The main difficulty of such a task is, given the multiple loci and multiple alleles, the number of all possible classifiers tends to be extremely large. Therefore, Monte Carlo Markov Chain method is applied to reduce the space of solutions and sample only from regions where it is likely to find a good classifier. Once a set of classifiers is found, there is a problem to validate the results, and this is done using a number of well known methods. In case of single disease level, the resulting classifier divides the space of healthy and ill individuals, and the result is represented in a classic Fisher table. Odds ratio and Fisher's p-value are calculated if applicable. Also, Kruskal's gamma and the corresponding p-value can be calculated. After each pattern in the output is described by a p-values set of different multiple-hypothesis corrections, including permutation tests.

The permutation procedure is highly paralleliseable, the examples of parallel scripts are in the package.

The authors would like to thank NIH/NLM (LM008932), UEPHA*MS FP7 Marie Curie Initial Training Network (FP7/2007-2013, grant agreement 212877), Russian Foundation for Basic Research (11-04-02016-a) for support of this work.

Original Reference

Favorov, A.V. et al. A Markov chain Monte Carlo technique for identification of combinations of allelic variants underlying complex diseases in humans. Genetics 171, 2113-2121 (2005).

References

Tsareva, E.Y. et al. Allelic combinations of immune-response genes associated with glatiramer acetate treatment response in Russian multiple sclerosis patients. Pharmacogenomics (2011).doi:10.2217/pgs.11.136

Sudomoina, M.A. et al. Complex analsis of association of inflammation genes with myocardial infarction. Mol. Biol. (Mosk.) 44, 463-471 (2010).

O’Doherty, C. et al. Genetic polymorphisms, their allele combinations and IFN-beta treatment response in Irish multiple sclerosis patients. Pharmacogenomics 10, 1177-1186 (2009).

Parfenov, M.G. et al. Complex analysis of genetic predisposition to ischemic stroke in Russians. Mol. Biol. (Mosk.) 43, 937-945 (2009).

Favorova, O.O. et al. Genetic predisposition to multiple sclerosis as a polygenic autoimmune disease. Zh Nevrol Psikhiatr Im S S Korsakova 109, 16-22 (2009).

Chikhladze, N.M. et al. Comparative genetic analysis of different forms of low-renin arterial hypertension. Mol. Biol. (Mosk.) 42, 588-598 (2008).

Chikhladze, N.M. et al. Contribution of CYP11B2, REN and AGT genes in genetic predisposition to arterial hypertension associated with hyperaldosteronism. Kardiologiia 48, 37-42 (2008).

Favorova, O.O. et al. Three allele combinations associated with multiple sclerosis. BMC Med. Genet. 7, 63 (2006).

Sudomoina, M.A. et al. Genetic risk factors of arterial hypertension: analysis of ischemic stroke patients from the Yakut ethnic group. Dokl. Biochem. Biophys. 410, 324-326 (2006).

Current version is 3.60

Check it by running APSampler --version

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