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Changes

NGS

249 bytes added, 10:37, 16 November 2018
Challenges
==Challenges==
* Bad coverage of pharmacogenes. This most seriously affects Notably, the lack of intronic variants in WES.* Haplotype calling is challenging due to short readreads. 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 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 Difficult variant calling in homologous regions are hard to capture (, such as CYP2D6. I.e. regions with copy number variations (CNV)). Notably, the genes CYP2D6 and CYP2A6 are challengingor pseudogenes. The CYP2D6 genotyping tool that was used by [https://github.com/PharmGKB/PharmCAT/wiki PharmCAT] is [https://www.nature.com/articles/npjgenmed201639 Astrolabe]. Recently, a (seemingly) vastly improved program [https://github.com/inumanag/aldy Aldy], has been published.* HLA-typing require special software. There are many options. [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. Recently, a (seemingly) vastly improved program [https://github.com/humanlongevity/HLA xHLA] has been published.
* New variants are discovered, and needs to be [[gene function|functionally assessed]].