AIAP: A Quality Control and Integrative Analysis Package to Improve ATAC-Seq Data Analysis

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.

Widespread contribution of transposable elements to the rewiring of mammalian 3D genomes and gene regulation

“…The ATAC-seq libraries were quantitated by Qubit assays and sequenced by an Illumina NextSeq platform. QC and analysis on ATAC-seq libraries were performed using AIAP [66]. Peaks in the ATAC data were called using MACS2 [57] and visualized on the WashU Epigenome Browser [31].…”

From Reads to Insights: Integrative Pipelines for Biological Interpretation of ATAC-Seq Data

“…In this issue, Liu et al [13] and Qiu et al [14] make great strides toward a standalone analytical ATAC-seq pipeline. Liu et al present the ATAC-seq Integrative Analysis Package (AIAP), which defines a series of ATAC-seq-specific QC metrics to optimize data and further uses a pseudo single-end strategy (PE-asSE) specifically developed for ATAC-seq to improve data analysis [13] . Using these ATAC-seq-specific metrics ( e.g.…”

Regulation of human cortical interneuron development by the chromatin remodeling protein CHD2

“…Samples with unique dual-end indexes were pooled in equimolar concentrations and were sequenced by the Washington University Genome Technology Access Center (GTAC) @MGI on the NovaSeq-6000 sequencer with the S4 flow cell as 2 × 150 bp paired-end reads at a depth of at least 10 million (M) reads per sample. Raw reads from CUT&Tag samples were processed by AIAP (v1.1) using human genome hg38 as a reference to perform read quality control, alignment, quantification, and peak calling 38 . Peaks from replicates were intersected using bedtools intersect peak with options -f 0.25 -F 0.25 -e. Peaks identified as intersecting in 2 or more out of 4 total replicates were defined as reproducible peaks.…”