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! [[NGS|Challenge]] !! Solution !! Comments
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| [[Allele definition]] || Pruning of allele definitions (removing variants from allele definitions (i.e. only keeping variants that destroys the protein), removing [[Unknown function|alleles with unknown function]]) || The allele pruning also makes it more likely that patients are indeed normal, thus making the problem of removing most sources to [[Unknown function|alleles with unknown function]] less critical
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| [[NGS|HLA-typing]] || SNP2HLA tool (WGS only) || SNP2HLA is a fast and reasonably accurate tool, but it seems that in a clinical setting [https://www.ncbi.nlm.nih.gov/pubmed/27802932 other tools may be considered]
| [[Allele definition|Multiple allele matches]] || Made hierarchy of alleles based on the biochemical function (No function > Decreased Function > Other functional statuses) || Probably this can be seen as a variant of the best solution to the [[Unknown function|unknown function problem]]: Look for the most serious consequence, and if not found, assume Normal function.
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| Haplotype calling || Eagle2. In case there were more than one star allele match per haplotype, they matched all possible star allele diplotypes || We suppose that they used haplotype Haplotype estimation for WGS was performed, but it is unclear which method was used (Eagle2 as for microarrays?, probably)
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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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