ataqv

ataqv provides quality control metrics and bias analysis for ATAC-seq datasets to assess data quality and identify technical sources of variation in chromatin accessibility measurements.

Key Features:

• Quality Control Measurement: Computes QC metrics for ATAC-seq datasets to assess data quality and detect technical bias.
• Visualization and Comparison: Generates visual summaries to compare QC metrics across samples and experiments.
• Integration into Pipelines: Integrates into computational pipelines to produce standardized QC outputs.
• Statistical Modeling: Implements statistical modeling to quantify technical variation and its impact on measured signals.

Scientific Applications:

• Analysis of Public Datasets: Applied to 2,009 public ATAC-seq datasets, revealing a tenfold range in QC metrics across datasets.
• Identification of Technical Biases: Through Tn5 dosage experiments and modeling, identifies technical variation—notably the Tn5 transposase:nuclei ratio and sequencing flowcell density—that induces systematic biases in read enrichment across promoters, enhancers, and transcription-factor-bound regions, with CTCF binding sites as an exception.

Methodology:

Uses statistical modeling and systematic bias analysis to quantify technical variation in ATAC-seq experiments, including effects of Tn5 transposase:nuclei ratio and sequencing flowcell density.