ATAC-Seq Analysis

Methods

ATAC-seq samples, consisting of two replicates from a human source, were subjected to a comprehensive analysis pipeline. The analysis commenced with quality control (QC) and adapter trimming using FastQC (v0.12.0) and Trimmomatic (v0.39), respectively. The reads were then aligned to the human reference genome (hg38) using Bowtie2 (v2.5.3), with the -X 2000 flag utilized to optimize alignment efficiency. To ensure data integrity, alignments to the mitochondrial chromosome were filtered out using SAMtools (v1.19.2). Additionally, to mitigate bias introduced during the tagmentation process, a read-shifting step was performed using deeptools (v3.5.6). Following read processing, fragment size distributions were assessed using ATACSeqQC using the atacseqqc.R script for quality control evaluation. Peak calling was conducted separately for each replicate using MACS3 (v3.0.1) with default parameters tailored for ATAC-seq data. To generate a set of reproducible peaks, peaks called from individual replicates were intersected using the intersect function in bedtools (v2.31.1). Furthermore, peaks falling within blacklisted regions were filtered out to enhance the reliability of the dataset. Peak annotation was performed using HOMER (v4.11) to associate peaks with nearby genes and genomic features with their proportions being calculated and visualized using the Unique_proportions.R script. Motif analysis was conducted on the reproducible peaks using MEME Suite (v5.5.5) to identify enriched sequence motifs. Lastly, signal coverage plots centered on the transcription start site (TSS) were generated for nucleosome-free regions (NFR) and nucleosome-bound regions (NBR) with PlotProfile from deeptools.

References

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