Evidence map›Paper›PMID 32014034›Full record

ReviewGenome biology2020

From reads to insight: a hitchhiker's guide to ATAC-seq data analysis.

Feng Yan, David R Powell, David J Curtis, Nicholas C Wong

Open access · goldAbstract readReview
In one paragraph

Review in Genome biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 282 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
282citing papers in PubMed, 1 pooled it
23.5field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

282 citing papers in PubMed, 1 synthesis or guideline pooled it, 526 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. UnlockingNAR genomics and bioinformatics · 2026
    Article
  5. Review
  6. Review
  7. Article
  8. Article
  9. Article
  10. Cross-Modal Denoising and Integration of Spatial Multi-Omics Data with CANDIES.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
  11. Article
  12. Article
  13. NovelbioRxiv : the preprint server for biology · 2026
    Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

222 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 3 institutions in 1 country.

Feng YanAustralian Centre for Blood Diseases, Central Clinical School, Monash University, Melbourne, VIC, Australia.
David R PowellMonash Bioinformatics Platform, Monash University, Melbourne, VIC, Australia.
David J CurtisAustralian Centre for Blood Diseases, Central Clinical School, Monash University, Melbourne, VIC, Australia.
Nicholas C WongAustralian Centre for Blood Diseases, Central Clinical School, Monash University, Melbourne, VIC, Australia. feng.yan@monash.edu.ORCID http://orcid.org/0000-0003-4393-7541
Australian Centre for HIV and Hepatitis Virology Research · AUMonash Medical Centre · AUMonash University · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Assay of Transposase Accessible Chromatin sequencing (ATAC-seq) is widely used in studying chromatin biology, but a comprehensive review of the analysis tools has not been completed yet. Here, we discuss the major steps in ATAC-seq data analysis, including pre-analysis (quality check and alignment), core analysis (peak calling), and advanced analysis (peak differential analysis and annotation, motif enrichment, footprinting, and nucleosome position analysis). We also review the reconstruction of transcriptional regulatory networks with multiomics data and highlight the current challenges of each step. Finally, we describe the potential of single-cell ATAC-seq and highlight the necessity of developing ATAC-seq specific analysis tools to obtain biologically meaningful insights.

Indexed as

AnimalsChromatinChromatin Immunoprecipitation SequencingGene Regulatory NetworksGenomicsHumansSingle-Cell AnalysisTranscriptomeTransposasesChromatinTransposases

Identifiers

PMID32014034
PMCPMC6996192
OpenAlexW3008816049

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.