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Motivation: CYP2D6 is highly polymorphic gene which encodes the (CYP2D6) enzyme, involved in the metabolism of 20-25% of all clinically prescribed drugs and other xenobiotics in the human body. CYP2D6 genotyping is recommended prior to treatment decisions involving one or more of the numerous drugs sensitive to CYP2D6 allelic composition. In this context, high-throughput sequencing (HTS) technologies provide a promising time-efficient and cost-effective alternative to currently used genotyping techniques. To achieve accurate interpretation of HTS data, however, one needs to overcome several obstacles such as high sequence similarity and genetic recombinations between CYP2D6 and evolutionarily related pseudogenes CYP2D7 and CYP2D8, high copy number variation among individuals and short read lengths generated by HTS technologies., Results: In this work, we present the first algorithm to computationally infer CYP2D6 genotype at basepair resolution from HTS data. Our algorithm is able to resolve complex genotypes, including alleles that are the products of duplication, deletion and fusion events involving CYP2D6 and its evolutionarily related cousin CYP2D7. Through extensive experiments using simulated and real datasets, we show that our algorithm accurately solves this important problem with potential clinical implications., Availability and Implementation: Cypiripi is available at http://sfu-compbio.github.io/cypiripi., (© The Author 2015. Published by Oxford University Press.)

Background: Positive control materials for clinical diagnostic molecular genetic testing are in critically short supply. High-quality DNA that closely resembles DNA isolated from patient specimens can be obtained from Epstein-Barr virus (EBV)-transformed peripheral blood lymphocyte cell lines. Here we report the development of a process to (a) recover residual blood samples with clinically important mutations detected during routine medical care, (b) select samples likely to provide viable lymphocytes for EBV transformation, (c) establish stable cell lines and confirm the reported mutation(s), and (d) validate the cell lines for use as positive controls in clinical molecular genetic testing applications., Methods: A network of 32 genetic testing laboratories was established to obtain anonymous, residual clinical samples for transformation and to validate resulting cell lines for use as positive controls. Three panel meetings with experts in molecular genetic testing were held to evaluate results and formulate a process that could function in the context of current common practices in molecular diagnostic testing., Results: Thirteen laboratories submitted a total of 113 residual clinical blood samples with mutations for 14 genetic disorders. Forty-one EBV-transformed cell lines were established. Thirty-five individual point and deletion mutations were shown to be stable after 20 population doublings in culture. Thirty-three cell lines were characterized for specific mutations and validated for use as positive controls in clinical diagnostic applications., Conclusions: A process for producing and validating positive control cell lines from residual clinical blood samples has been developed. Sustainable implementation of the process could help alleviate the current shortage of positive control materials.