Cypiripi：使用高通量测序数据进行 CYP2D6 的精确基因分型。
Cypiripi: exact genotyping of CYP2D6 using high-throughput sequencing data.
机构信息
School of Computing Science, Simon Fraser University, Burnaby, BC V5A 1S6, Canada, Department of Medicine, Division of Clinical Pharmacology, Indiana University School of Medicine, Indianapolis, IN 46202, USA and School of Informatics and Computing, Indiana University, Bloomington, IN 47401, USA School of Computing Science, Simon Fraser University, Burnaby, BC V5A 1S6, Canada, Department of Medicine, Division of Clinical Pharmacology, Indiana University School of Medicine, Indianapolis, IN 46202, USA and School of Informatics and Computing, Indiana University, Bloomington, IN 47401, USA.
School of Computing Science, Simon Fraser University, Burnaby, BC V5A 1S6, Canada, Department of Medicine, Division of Clinical Pharmacology, Indiana University School of Medicine, Indianapolis, IN 46202, USA and School of Informatics and Computing, Indiana University, Bloomington, IN 47401, USA.
出版信息
Bioinformatics. 2015 Jun 15;31(12):i27-34. doi: 10.1093/bioinformatics/btv232.
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.
动机
CYP2D6 是高度多态性基因，编码（CYP2D6）酶，参与人体中 20-25%的所有临床处方药物和其他异源生物的代谢。在涉及对 CYP2D6 等位基因组成敏感的一种或多种众多药物的治疗决策之前，建议进行 CYP2D6 基因分型。在这种情况下，高通量测序（HTS）技术为目前使用的基因分型技术提供了一种有前途的高效、经济有效的替代方法。然而，为了准确解释 HTS 数据，需要克服几个障碍，例如 CYP2D6 和进化上相关的假基因 CYP2D7 和 CYP2D8 之间的高序列相似性和遗传重组、个体之间的高拷贝数变异以及 HTS 技术产生的短读长。
结果
在这项工作中，我们提出了第一个从 HTS 数据以碱基分辨率计算推断 CYP2D6 基因型的算法。我们的算法能够解析复杂的基因型，包括 CYP2D6 及其进化相关表亲 CYP2D7 中涉及重复、缺失和融合事件的产物的等位基因。通过使用模拟和真实数据集的广泛实验，我们表明我们的算法能够准确地解决这个具有潜在临床意义的重要问题。
可用性和实现
Cypiripi 可在 http://sfu-compbio.github.io/cypiripi 获得。
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