Best Practices for Pre-Processing Large-Scale ATAC-Seq Data: Why Epidemiological Studies Demand Greater Stringency

PIPPA shows that ATAC-seq peak calling performance is dataset-dependent, and no single significance threshold works optimally across all scenarios in sorted cell-type datasets.

• Why it matters: Epidemiological studies need scalable, reproducible peak calling to ensure biologically meaningful chromatin accessibility signals, but optimal strategies lack consensus.
• What they did: The authors developed PIPPA for quality control and peak set curation, benchmarking it on two independent cell-type sorted ATAC-seq datasets and testing peak calling thresholds.
• The result: They provide parameter recommendations to generate high-confidence accessibility profiles, enabling standardized analyses for epidemiological studies and applicable to ChIP-seq and CUT&Tag.