Assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) is a technique widely used to investigate genome-wide chromatin accessibility. The recently published Omni-ATAC-seq protocol substantially improves the signal/noise ratio and reduces the input cell number. High-quality data are critical to ensure accurate analysis. Several tools have been developed for assessing sequencing quality and insertion size distribution for ATAC-seq data; however, key quality control (QC) metrics have not yet been established to accurately determine the quality of ATAC-seq data. Here, we optimized the analysis strategy for ATAC-seq and defined a series of QC metrics for ATAC-seq data, including reads under peak ratio (RUPr), background (BG), promoter enrichment (ProEn), subsampling enrichment (SubEn), and other measurements. We incorporated these QC tests into our recently developed ATAC-seq Integrative Analysis Package (AIAP) to provide a complete ATAC-seq analysis system, including quality assurance, improved peak calling, and downstream differential analysis. We demonstrated a significant improvement of sensitivity (20%–60%) in both peak calling and differential analysis by processing paired-end ATAC-seq datasets using AIAP. AIAP is compiled into Docker/Singularity, and it can be executed by one command line to generate a comprehensive QC report. We used ENCODE ATAC-seq data to benchmark and generate QC recommendations, and developed qATACViewer for the user-friendly interaction with the QC report. The software, source code, and documentation of AIAP are freely available at https://github.com/Zhang-lab/ATAC-seq_QC_analysis.

使用高通量测序 ( ATAC-seq ) 检测转座酶可及染色质是一种广泛用于研究全基因组染色质可及性的技术。最近发布的 Omni-ATAC-seq 协议大大提高了信噪比并减少了输入单元数。高质量数据对于确保准确分析至关重要。已经开发了几种工具来评估 ATAC-seq 数据的测序质量和插入大小分布；然而，关键的质量控制(QC) 指标尚未建立来准确确定 ATAC-seq 数据的质量。在这里，我们优化了ATAC-seq的分析策略，并为ATAC-seq数据定义了一系列QC指标，包括峰值比（RUPr）、背景（BG）、启动子富集（ProEn）、子采样富集（SubEn）、和其他测量。我们将这些 QC 测试纳入我们最近开发的 ATAC-seq 综合分析包 (AIAP)，以提供完整的 ATAC-seq 分析系统，包括质量保证、改进的峰值调用和下游差异分析. 通过使用 AIAP 处理配对末端 ATAC-seq 数据集，我们证明了峰值调用和差异分析的灵敏度显着提高 (20%–60%)。AIAP被编译成Docker/Singularity，可以通过一个命令行执行，生成一份全面的QC报告。我们使用 ENCODE ATAC-seq 数据进行基准测试并生成 QC 建议，并开发了qATACViewer以便与 QC 报告进行用户友好的交互。AIAP 的软件、源代码和文档可在 https://github.com/Zhang-lab/ATAC-seq_QC_analysis 免费获得。