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NGS

27 bytes added, 07:46, 9 October 2018
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Challenges
==Challenges==
* Bad coverage of pharmacogenes. This most seriously affects WES.
* Haplotype calling is challenging due to short read. NGS requires ''in silico'' haplotype estimation. There is support for basic haplotype estimation in [https://software.broadinstitute.org/gatk/documentation/tooldocs/3.8-0/org_broadinstitute_gatk_tools_walkers_haplotypecaller_HaplotypeCaller.php the GATK haplotype caller since version 3.3]. Haplotype calling can e.g. also be performed by various imputation methods [http://faculty.washington.edu/browning/beagle/beagle.html Beagle] or [http://dx.doi.org/10.1038/ng.3679 Eagle2] or [https://doi.org/10.1371/journal.pgen.1004234 SHAPEIT].
* Variants in homologous regions are hard to capture (regions with copy number variations (CNV)). Notably, the genes CYP2D6 and CYP2A6 are challenging. The CYP2D6 genotyping tool used by [https://github.com/PharmGKB/PharmCAT/wiki PharmCAT] is [https://www.nature.com/articles/npjgenmed201639 Astrolabe].
* HLA-typing require special software. [https://doi.org/10.1002/cpt.411 Yang et al.] proposed to use [https://software.broadinstitute.org/cancer/cga/polysolver Polysolver] for whole exome sequencing (WES) or [https://github.com/FRED-2/OptiType OptiType] for whole genome sequencing (WGS). [https://doi.org/10.1101/356204 Reisberg et al.] proposed [https://doi.org/10.1371/journal.pone.0064683 SNP2HLA] for WGS.