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The Estonian Genome Centre at the University of Tartu has done a considerable job with [https://doi.org/10.1101/356204 Translating genotype data of 44,000 biobank participants into clinical pharmacogenetic recommendations].
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| CYP2D6 calling || Combination of Genome STRiP and normal allele matching (favorable comparison to Astrolabe used by PharmCAT) || Did not understand exactly how they did it (maybe check out reference by [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5292679/ ''Gaedigk et al.''])
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==Take home messages==
* Haplotype calling essential
* Prefiltering (pruning) of the allele definition tables provided by PharmGKB
* Rare variants (< 1% mean allele frequency) account for 89% of all deleterious mutations
* Rare variants should only be used for research
* Multiple star alleles are for some genes expected on same haplotype. Suggestion: look for the functional effect of variants within star alleles instead of looking for star alleles, making decision trees that prioritize variants
* WES is not good enough for PGx, unless adding customized probes (which is generally more expensive than a pure microarray approach)
* Mircoarrays with impuation of unknown variants is cost-effective approach to PGx
* WGS has similar quality as microarrays. In addition WGS allows for HLA-calling and finds additional variants that are as yet not actionable
