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AIAP: A Quality Control and Integrative Analysis Package to Improve ATAC-seq Data Analysis
Authors:Shaopeng Liu  Daofeng Li  Cheng Lyu  Paul M Gontarz  Benpeng Miao  Pamela AF Madden  Ting Wang  Bo Zhang
Institution:Department of Developmental Biology,Center of Regenerative Medicine,Washington University School of Medicine,St.Louis,MO 63108,USA;Department of Genetics,Center for Genomic Sciences and Systems Biology,Washington University School of Medicine,St.Louis,MO 63108,USA;Department of Developmental Biology,Center of Regenerative Medicine,Washington University School of Medicine,St.Louis,MO 63108,USA;Department of Genetics,Center for Genomic Sciences and Systems Biology,Washington University School of Medicine,St.Louis,MO 63108,USA;Department of Psychiatry,Washington University School of Medicine,St.Louis,MO 63108,USA
Abstract: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.
Keywords:ATAC-seq  Quality control  Chromatin accessibility  Differential analysis  Data visualization
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