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Cross-Comparison of Exome Analysis, Next-Generation Sequencing of Amplicons, and the iPLEX® ADME PGx Panel for Pharmacogenomic Profiling

Overview of attention for article published in Frontiers in Pharmacology, January 2016
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Title
Cross-Comparison of Exome Analysis, Next-Generation Sequencing of Amplicons, and the iPLEX® ADME PGx Panel for Pharmacogenomic Profiling
Published in
Frontiers in Pharmacology, January 2016
DOI 10.3389/fphar.2016.00001
Pubmed ID
Authors

Eng Wee Chua, Simone L. Cree, Kim N. T. Ton, Klaus Lehnert, Phillip Shepherd, Nuala Helsby, Martin A. Kennedy

Abstract

Whole-exome sequencing (WES) has been widely used for analysis of human genetic diseases, but its value for the pharmacogenomic profiling of individuals is not well studied. Initially, we performed an in-depth evaluation of the accuracy of WES variant calling in the pharmacogenes CYP2D6 and CYP2C19 by comparison with MiSeq(®) amplicon sequencing data (n = 36). This analysis revealed that the concordance rate between WES and MiSeq(®) was high, achieving 99.60% for variants that were called without exceeding the truth-sensitivity threshold (99%), defined during variant quality score recalibration (VQSR). Beyond this threshold, the proportion of discordant calls increased markedly. Subsequently, we expanded our findings beyond CYP2D6 and CYP2C19 to include more genes genotyped by the iPLEX(®) ADME PGx Panel in the subset of twelve samples. WES performed well, agreeing with the genotyping panel in approximately 99% of the selected pass-filter variant calls. Overall, our results have demonstrated WES to be a promising approach for pharmacogenomic profiling, with an estimated error rate of lower than 1%. Quality filters, particularly VQSR, are important for reducing the number of false variants. Future studies may benefit from examining the role of WES in the clinical setting for guiding drug therapy.

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Mendeley readers

Mendeley readers

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Geographical breakdown

Country Count As %
Italy 1 2%
Unknown 49 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 14 28%
Student > Ph. D. Student 8 16%
Student > Bachelor 5 10%
Student > Master 5 10%
Lecturer 2 4%
Other 6 12%
Unknown 10 20%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 18 36%
Agricultural and Biological Sciences 9 18%
Pharmacology, Toxicology and Pharmaceutical Science 4 8%
Medicine and Dentistry 3 6%
Engineering 2 4%
Other 3 6%
Unknown 11 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 January 2016.
All research outputs
#20,302,535
of 22,840,638 outputs
Outputs from Frontiers in Pharmacology
#10,086
of 16,082 outputs
Outputs of similar age
#333,544
of 396,750 outputs
Outputs of similar age from Frontiers in Pharmacology
#57
of 82 outputs
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