Difference between revisions of "NGS"
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* Short read NGS requires a priori knowledge of likelihood of particular haplotypes. ''In silico'' haplotype estimation can e.g. be performed by [http://faculty.washington.edu/browning/beagle/beagle.html Beagle]. | * Short read NGS requires a priori knowledge of likelihood of particular haplotypes. ''In silico'' haplotype estimation can e.g. be performed by [http://faculty.washington.edu/browning/beagle/beagle.html Beagle]. | ||
* Variants in homologous regions are hard to capture. | * Variants in homologous regions are hard to capture. | ||
| + | * HLA-typing require special software, e.g. [https://software.broadinstitute.org/cancer/cga/polysolver Polysolver] for whole exome sequencing or [https://github.com/FRED-2/OptiType OptiType] for whole genome sequencing | ||
Revision as of 08:28, 14 August 2018
Next Generation Sequencing (NGS) is an interesting technology for PGx
A nice overview of the Requirements for comprehensive pharmacogenetic genotyping platforms was published by Volker Lauschke et al. They claim that rare variants account for 30-40% of functional variability in PGx. However they argue that pre-emptive PGx should only include validated variants.
Challenges
- Short read NGS requires a priori knowledge of likelihood of particular haplotypes. In silico haplotype estimation can e.g. be performed by Beagle.
- Variants in homologous regions are hard to capture.
- HLA-typing require special software, e.g. Polysolver for whole exome sequencing or OptiType for whole genome sequencing
