Data from: AftrRAD: a pipeline for accurate and efficient de novo assembly of RADseq data

An increase in studies using restriction site-associated DNA sequencing (RADseq) methods has led to a need for both the development and assessment of novel bioinformatic tools that aid in the generation and analysis of these data. Here, we report the availability of AftrRAD, a bioinformatic pipeline that efficiently assembles and genotypes RADseq data, and outputs these data in various formats for downstream analyses. We use simulated and experimental data sets to evaluate AftrRAD's ability to perform accurate de novo assembly of loci, and we compare its performance with two other commonly used programs, stacks and pyrad. We demonstrate that AftrRAD is able to accurately assemble loci, while accounting for indel variation among alleles, in a more computationally efficient manner than currently available programs. AftrRAD run times are not strongly affected by the number of samples in the data set, making this program a useful tool when multicore systems are not available for parallel processing, or when data sets include large numbers of samples.

随着限制性位点相关DNA测序（restriction site-associated DNA sequencing, RADseq）技术在研究中的应用愈发广泛，学界亟需开发并评估可辅助此类数据生成与分析的新型生物信息学工具。本研究介绍了一款名为AftrRAD的生物信息学分析流程，其可高效完成RADseq数据的组装与基因型分型，并支持将数据以多种格式输出以用于后续分析。本研究利用模拟数据集与实测数据集，评估了AftrRAD对基因座进行精准从头组装的能力，并将其性能与两款常用软件stacks及pyrad进行了对比。研究结果表明，相较于现有同类工具，AftrRAD能够在兼顾等位基因间插入缺失（insertion-deletion, indel）变异的前提下，以更高的计算效率完成基因座的精准组装。AftrRAD的运行时长不受数据集样本量的显著影响，因此在无法使用多核系统进行并行计算，或数据集包含大量样本的场景下，该工具具备极高的实用价值。