AbCD: arbitrary coverage design for sequencing-based genetic studies.
AbCD: arbitrary coverage design for sequencing-based genetic studies.
复制标题
AbCD：基于测序的遗传研究的任意覆盖设计。
DOI：
10.1093/bioinformatics/btt041
复制
发表时间：
2013
期刊：
影响因子：
--
通讯作者：
Li,Yun
中科院分区：
文献类型：
--
作者：
Kang,Jian;Huang,Kuan-Chieh;Xu,Zheng;Wang,Yunfei;Abecasis,GonçaloR;Li,Yun
摘要：测序技术的最新进展使基因研究发生了革命性的变化。虽然高覆盖率测序可以发现测序样本中存在的大多数变异，但低覆盖率测序因其成本效益而吸引人。在这里，我们提出ABCD(任意覆盖设计)来辅助基于序列的研究的设计。ABCD是一个用户友好的界面，提供预先估计的有效样本量，特定于每个次要等位基因频率类别，用于任意覆盖(0.5-30×)和样本量(20-10,000)的设计，以及四个主要民族(欧洲人、非洲人、亚洲人和非裔美国人)。此外，我们还介绍了两个软件工具：鸟枪和DesignPlanner，这两个工具用于生成ABCD背后的估计。鸟枪是一款灵活的短读模拟器，可用于任意用户指定的读取长度和平均深度，允许特定周期的测序错误率和真实的读取深度分布。DesignPlanner是一个完整的流水线，它使用猎枪生成序列数据并执行初始SNP发现，使用我们之前提出的连锁不平衡感知方法来调用基因类型，最后提供次要等位基因频率特定的有效样本量。对于高深度和低深度数据的任何组合(例如，全基因组低深度和外显子高深度)或序列和基因数据的组合[例如，全外显子测序加上现有基因组关联研究中的基因分型]，Shotgan plus DesignPlanner可以适应有效的样本量估计。可用性和实施：ABCD，包括其可下载的终端界面和基于网络的界面，以及包括文档、示例和可执行文件在内的相关工具ShotGill和DesignPlanner，可在http://www.unc.edu/∼yunmli/AbCD.html.Contact:yunli@med.unc.edu上获得
Summary:Recent advances in sequencing technologies have revolutionized genetic studies. Although high-coverage sequencing can uncover most variants present in the sequenced sample, low-coverage sequencing is appealing for its cost effectiveness. Here, we present AbCD (arbitrary coverage design) to aid the design of sequencing-based studies. AbCD is a user-friendly interface providing pre-estimated effective sample sizes, specific to each minor allele frequency category, for designs with arbitrary coverage (0.5–30×) and sample size (20–10 000), and for four major ethnic groups (Europeans, Africans, Asians and African Americans). In addition, we also present two software tools: ShotGun and DesignPlanner, which were used to generate the estimates behind AbCD. ShotGun is a flexible short-read simulator for arbitrary user-specified read length and average depth, allowing cycle-specific sequencing error rates and realistic read depth distributions. DesignPlanner is a full pipeline that uses ShotGun to generate sequence data and performs initial SNP discovery, uses our previously presented linkage disequilibrium-aware method to call genotypes, and, finally, provides minor allele frequency-specific effective sample sizes. ShotGun plus DesignPlanner can accommodate effective sample size estimate for any combination of high-depth and low-depth data (for example, whole-genome low-depth plus exonic high-depth) or combination of sequence and genotype data [for example, whole-exome sequencing plus genotyping from existing Genomewide Association Study (GWAS)].Availability and implementation:AbCD, including its downloadable terminal interface and web-based interface, and the associated tools ShotGun and DesignPlanner, including documentation, examples and executables, are available at http://www.unc.edu/∼yunmli/AbCD.html.Contact:yunli@med.unc.edu