ArticleCell reports methods2022
Normalization benchmark of ATAC-seq datasets shows the importance of accounting for GC-content effects.
Article in Cell reports methods, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- UnlockingNAR genomics and bioinformatics · 2026Article
- G-quadruplexes regulate chromatin accessibility and gene expression in Bloom Syndrome.bioRxiv : the preprint server for biology · 2026Article
- Profiling the epigenomic landscape of late embryonic and adult mouse hind limb muscles.Scientific reports · 2026Article
- Integrating multi-omic QTLs and predictive models reveals regulatory architectures at immune related GWAS loci in CD4+ T cells.medRxiv : the preprint server for health sciences · 2026Article
- ATAC-seq in Emerging Model Organisms: Challenges and Strategies.Journal of experimental zoology. Part B, Molecular and developmental evolution · 2025Review
- Adaptive individualized gene pair signatures distinguishing melanoma and predicting response to immune checkpoint blockade.iScience · 2025Article
- A hierarchical, count-based model highlights challenges in scATAC-seq data analysis and points to opportunities to extract finer-resolution information.Genome biology · 2025Article
- Chromatin accessibility provides a window into the genetic etiology of human brain disease.Trends in genetics : TIG · 2025Review
- Going beyond cell clustering and feature aggregation: Is there single cell level information in single-cell ATAC-seq data?bioRxiv : the preprint server for biology · 2024Article
- Best practices for differential accessibility analysis in single-cell epigenomics.Nature communications · 2024Article
- On the identification of differentially-active transcription factors from ATAC-seq data.PLoS computational biology · 2024Article
- Context transcription factors establish cooperative environments and mediate enhancer communication.Nature genetics · 2024Article
- On the identification of differentially-active transcription factors from ATAC-seq data.bioRxiv : the preprint server for biology · 2024Article
- Activity-Dependent Transcriptional Program in NGN2+ Neurons Enriched for Genetic Risk for Brain-Related Disorders.Biological psychiatry · 2024Article
- Aging differentially alters the transcriptome and landscape of chromatin accessibility in the male and female mouse hippocampus.Frontiers in molecular neuroscience · 2024Article
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7 authors.
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Abstract
The assay for transposase-accessible chromatin using sequencing (ATAC-seq) allows the study of epigenetic regulation of gene expression by assessing chromatin configuration for an entire genome. Despite its popularity, there have been limited studies investigating the analytical challenges related to ATAC-seq data, with most studies leveraging tools developed for bulk transcriptome sequencing. Here, we show that GC-content effects are omnipresent in ATAC-seq datasets. Since the GC-content effects are sample specific, they can bias downstream analyses such as clustering and differential accessibility analysis. We introduce a normalization method based on smooth-quantile normalization within GC-content bins and evaluate it together with 11 different normalization procedures on 8 public ATAC-seq datasets. Accounting for GC-content effects in the normalization is crucial for common downstream ATAC-seq data analyses, improving accuracy and interpretability. Through case studies, we show that exploratory data analysis is essential to guide the choice of an appropriate normalization method for a given dataset.
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