UMI-ATAC-seq
UMI-ATAC-seq improves quantification of chromatin accessibility by integrating unique molecular identifiers (UMIs) into ATAC-seq to distinguish true Tn5 transposase insertion events from PCR duplicates and enhance transcription factor footprint detection.
Key Features:
- Improved Quantification: UMIs are incorporated to distinguish true biological Tn5 transposase insertion events from PCR-induced duplicates, enabling more accurate chromatin accessibility quantification.
- Enhanced Footprinting Sensitivity: UMI-ATAC-seq rescues approximately 20% of reads that would be discarded by standard duplicate removal and yields over 50% more identified transcription factor footprints.
- Bias Reduction: The approach mitigates the bias toward highly accessible chromatin regions introduced by traditional duplicate removal based on mapping coordinates.
- Analytic Pipeline: The pipeline performs sequencing adapter removal, UMI extraction from FASTQ read1 files, ME sequence removal, and UMI-based PCR duplicate removal.
Scientific Applications:
- Chromatin accessibility mapping: Provides more accurate quantification of accessible chromatin regions for genome-wide accessibility profiling.
- Transcription factor footprinting: Increases sensitivity and recovery of transcription factor binding site footprints through improved duplicate resolution.
- Nucleosome-free region identification: Enhances detection of nucleosome-free regions by recovering insertion events obscured by PCR duplicates.
- Epigenetics and cellular differentiation studies: Facilitates analysis of epigenetic modifications and accessibility changes during cellular differentiation.
- Disease-associated chromatin changes: Supports investigation of chromatin structure alterations linked to disease by improving signal fidelity.
Methodology:
Computational processing includes sequencing adapter removal, UMI extraction from FASTQ read1 files, ME sequence removal, and UMI-based PCR duplicate removal.
Topics
Details
- Programming Languages:
- Python
- Added:
- 1/18/2021
- Last Updated:
- 3/6/2021
Operations
Publications
Zhu T, Liao K, Zhou R, Xia C, Xie W. ATAC-seq with unique molecular identifiers improves quantification and footprinting. Unknown Journal. 2020. doi:10.1101/2020.10.22.351478.