Evidence map›Paper›PMID 32543102›Full record

ArticleCurrent protocols in human genetics2020

Analytical Approaches for ATAC-seq Data Analysis.

Jason P Smith, Nathan C Sheffield

Abstract read
In one paragraph

Article in Current protocols in human genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

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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

2 authors.

Jason P SmithCenter for Public Health Genomics, University of Virginia, Charlottesville, Virginia.
Nathan C SheffieldCenter for Public Health Genomics, University of Virginia, Charlottesville, Virginia.

Funding

Translational Control in the Hepatitis C VirusS06GM008136 · NIGMS · NEW MEXICO STATE UNIVERSITY LAS CRUCES · PI KUEHN, GLENN D · 1989 to 2011
$23.2M
Training in Cell and Molecular BiologyT32GM139787 · NIGMS · UNIVERSITY OF VIRGINIA · PI Bryce Paschal · 2021 to 2026
$2.5M
A modular data analysis ecosystem using portable encapsulated projectsR35GM128636 · NIGMS · UNIVERSITY OF VIRGINIA · PI SHEFFIELD, NATHAN · 2018 to 2022
$1.9M
NIGMS NIH HHS R35 GM128636NIGMS NIH HHS S06 GM008136NIGMS NIH HHS T32 GM139787
6 · The paper itself

Abstract

ATAC-seq, the assay for transposase-accessible chromatin using sequencing, is a quick and efficient approach to investigating the chromatin accessibility landscape. Investigating chromatin accessibility has broad utility for answering many biological questions, such as mapping nucleosomes, identifying transcription factor binding sites, and measuring differential activity of DNA regulatory elements. Because the ATAC-seq protocol is both simple and relatively inexpensive, there has been a rapid increase in the availability of chromatin accessibility data. Furthermore, advances in ATAC-seq protocols are rapidly extending its breadth to additional experimental conditions, cell types, and species. Accompanying the increase in data, there has also been an explosion of new tools and analytical approaches for analyzing it. Here, we explain the fundamentals of ATAC-seq data processing, summarize common analysis approaches, and review computational tools to provide recommendations for different research questions. This primer provides a starting point and a reference for analysis of ATAC-seq data. © 2020 Wiley Periodicals LLC.

Indexed as

Data AnalysisChromatinChromatin Immunoprecipitation SequencingHigh-Throughput Nucleotide SequencingHumansSequence Analysis, DNATransposasesChromatinTransposasesATAC-seqbioinformatics toolschromatin accessibilitydata analysisopen chromatinpipelines

Identifiers

PMID32543102
PMCPMC8191135

What OpenQuestion holds

Textmetadata
LicenceTDM
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.