Evidence map›Paper›PMID 32213349›Full record

ArticleCell systems2020

Quantification, Dynamic Visualization, and Validation of Bias in ATAC-Seq Data with ataqv.

Peter Orchard, Yasuhiro Kyono, John Hensley, Jacob O Kitzman, Stephen C J Parker

Abstract read
In one paragraph

Article in Cell systems, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers.

0numbers the graph read from it
0cells of the map it votes in
62citing papers in PubMed
–field-weighted citation impact
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

62 citing papers in PubMed.

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2 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

5 authors.

Peter OrchardDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.
Yasuhiro KyonoDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA; Department of Human Genetics, University of Michigan, Ann Arbor, MI 48109, USA.
John HensleyDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.
Jacob O KitzmanDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA; Department of Human Genetics, University of Michigan, Ann Arbor, MI 48109, USA.
Stephen C J ParkerDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA; Department of Human Genetics, University of Michigan, Ann Arbor, MI 48109, USA. Electronic address: scjp@umich.edu.

Funding

University of Michigan Training Program in Genomic ScienceT32HG000040 · NHGRI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Sebastian Zoellner · 1995 to 2026
$16.4M
Multidisciplinary Training Program in Basic Diabetes ResearchT32DK101357 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI PETER ARVAN, Ormond A MacDougald · 2014 to 2026
$4.1M
Context-specific and combinatorial genetic regulatory grammars in diabetesR01DK117960 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Stephen CJ Parker · 2018 to 2026
$2.8M
NHGRI NIH HHS T32 HG000040NIDDK NIH HHS R01 DK117960NIDDK NIH HHS T32 DK101357
6 · The paper itself

Abstract

The assay for transposase-accessible chromatin using sequencing (ATAC-seq) has become the preferred method for mapping chromatin accessibility due to its time and input material efficiency. However, it can be difficult to evaluate data quality and identify sources of technical bias across samples. Here, we present ataqv, a computational toolkit for efficiently measuring, visualizing, and comparing quality control (QC) results across samples and experiments. We use ataqv to analyze 2,009 public ATAC-seq datasets; their QC metrics display a 10-fold range. Tn5 dosage experiments and statistical modeling show that technical variation in the ratio of Tn5 transposase to nuclei and sequencing flowcell density induces systematic bias in ATAC-seq data by changing the enrichment of reads across functional genomic annotations including promoters, enhancers, and transcription-factor-bound regions, with the notable exception of CTCF. ataqv can be integrated into existing computational pipelines and is freely available at https://github.com/ParkerLab/ataqv/.

Indexed as

AnimalsBiasChromatinChromatin Immunoprecipitation SequencingComputational BiologyHigh-Throughput Nucleotide SequencingHumansPromoter Regions, GeneticQuality ControlRegulatory Sequences, Nucleic AcidSequence Analysis, DNASoftwareTranscription FactorsTransposasesChromatinTn5 transposaseTranscription FactorsTransposasesbioinformaticschromatincomputational genomicsepigenometools

Identifiers

PMID32213349
PMCPMC8245295

What OpenQuestion holds

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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.