Cited by 567Genomics and Chromatin DynamicsEpigenetics and DNA MethylationChromatin Remodeling and Cancer

The DOI matches its Crossref record; 21 of the 21 references it cites were found in a registry or an index.

Peak calling by Sparse Enrichment Analysis for CUT&RUN chromatin profiling

Open access
Meers, Michael P., Tenenbaum, Dan, Henikoff, Steven·2019·Epigenetics & Chromatin

Abstract

BACKGROUND: CUT&RUN is an efficient epigenome profiling method that identifies sites of DNA binding protein enrichment genome-wide with high signal to noise and low sequencing requirements. Currently, the analysis of CUT&RUN data is complicated by its exceptionally low background, which renders programs designed for analysis of ChIP-seq data vulnerable to oversensitivity in identifying sites of protein binding. RESULTS: Here we introduce Sparse Enrichment Analysis for CUT&RUN (SEACR), an analysis strategy that uses the global distribution of background signal to calibrate a simple threshold for peak calling. SEACR discriminates between true and false-positive peaks with near-perfect specificity from "gold standard" CUT&RUN datasets and efficiently identifies enriched regions for several different protein targets. We also introduce a web server ( http://seacr.fredhutch.org ) for plug-and-play analysis with SEACR that facilitates maximum accessibility across users of all skill levels. CONCLUSIONS: SEACR is a highly selective peak caller that definitively validates the accuracy of CUT&RUN for datasets with known true negatives. Its ease of use and performance in comparison with existing peak calling strategies make it an ideal choice for analyzing CUT&RUN data.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1186/s13072-019-0287-4

Cites

21 of 21 references verified0 citation errors · 0 not checkable

Statistics

Figures

Fig. 1 SEACR enforces peak calling specificity across a range of read depths. a Schematic of SEACR methodology. Contiguous signal blocks (top) are identified and plotted by the percentage of blocks exceeding a total signal threshold (right), and an optimal threshold is empirically identified and used for filtering (bottom). b Plot of area under the precision–recall curve (AUPR) for peaks called from H3K4me3 CUT&RUN data by SEACR, MACS2, MACS2 with local lambda inactivated (MACS2 llocal), and HOMER that were compared to a stringent test set of H3K4me3 peaks called from ENCODE ChIP-seq data. Read subsampling levels are indicated on the X-axis
Fig. 1 SEACR enforces peak calling specificity across a range of read depths. a Schematic of SEACR methodology. Contiguous signal blocks (top) are identified and plotted by the percentage of blocks exceeding a total signal threshold (right), and an optimal threshold is empirically identified and used for filtering (bottom). b Plot of area under the precision–recall curve (AUPR) for peaks called from H3K4me3 CUT&RUN data by SEACR, MACS2, MACS2 with local lambda inactivated (MACS2 llocal), and HOMER that were compared to a stringent test set of H3K4me3 peaks called from ENCODE ChIP-seq data. Read subsampling levels are indicated on the X-axisCC BY · PubMed Central
Fig. 2 SEACR minimizes true negative detection from a gold standard dataset. a Schematic of SEACR threshold selection. A target/total signal block curve (right) is calculated, and the stringent and relaxed thresholds are set based on the knee and the peak of the curve. b Peaks were called from Sox2 or FoxA2 experiments carried out in either hESCs or Endoderm cells using SEACR in stringent or relaxed mode; MACS2; or HOMER
Fig. 2 SEACR minimizes true negative detection from a gold standard dataset. a Schematic of SEACR threshold selection. A target/total signal block curve (right) is calculated, and the stringent and relaxed thresholds are set based on the knee and the peak of the curve. b Peaks were called from Sox2 or FoxA2 experiments carried out in either hESCs or Endoderm cells using SEACR in stringent or relaxed mode; MACS2; or HOMERCC BY · PubMed Central
Fig. 3 SEACR thresholding provides an improved specificity/sensitivity trade-off. a Precision–recall curves derived from a comparison of peaks called from subsampled H3K4me2 CUT&RUN to ENCODE peaks called from H3K4me2 ChIP-seq data. Colors denote peak calling method, size of points denotes read subsampling level, and dotted black line denotes 85% precision in peak calling. b F1 score for each point on the plots in A
Fig. 3 SEACR thresholding provides an improved specificity/sensitivity trade-off. a Precision–recall curves derived from a comparison of peaks called from subsampled H3K4me2 CUT&RUN to ENCODE peaks called from H3K4me2 ChIP-seq data. Colors denote peak calling method, size of points denotes read subsampling level, and dotted black line denotes 85% precision in peak calling. b F1 score for each point on the plots in ACC BY · PubMed Central
Fig. 4 SEACR identifies coherent broad domains. a CUT&RUN domains identified by SEACR are broader than those found by MACS2 or HOMER. b A representative region of a H3K27me3 profile is shown. SEACR domains are relatively coherent compared with HOMER and MACS2 domains, which are fragmented into mixtures of wide and narrow segments
Fig. 4 SEACR identifies coherent broad domains. a CUT&RUN domains identified by SEACR are broader than those found by MACS2 or HOMER. b A representative region of a H3K27me3 profile is shown. SEACR domains are relatively coherent compared with HOMER and MACS2 domains, which are fragmented into mixtures of wide and narrow segmentsCC BY · PubMed Central
Fig. 5 SEACR exhibits competitive run time and memory usage. Comparison of run time (a), average disk read memory (b), and average disk write memory (c) recorded for SEACR, MACS2, and HOMER peak calling from H3K27me3 data at read depths indicated. Error bars indicate standard deviation from the mean of 10 trials
Fig. 5 SEACR exhibits competitive run time and memory usage. Comparison of run time (a), average disk read memory (b), and average disk write memory (c) recorded for SEACR, MACS2, and HOMER peak calling from H3K27me3 data at read depths indicated. Error bars indicate standard deviation from the mean of 10 trialsCC BY · PubMed Central
Fig. 6 A web server for SEACR analysis. a The SEACR web server home page (https://seacr.fredhutch.org) contains browse functions for bedgraph input files and toggles for normalization and stringent/relaxed mode options. b The SEACR web server output page features a progress window with regular updates, a link for downloadable results in BED format, and the empirical false discovery rate (FDR) calculated by quantifying the percentage of control signal blocks remaining out of the total above the threshold
Fig. 6 A web server for SEACR analysis. a The SEACR web server home page (https://seacr.fredhutch.org) contains browse functions for bedgraph input files and toggles for normalization and stringent/relaxed mode options. b The SEACR web server output page features a progress window with regular updates, a link for downloadable results in BED format, and the empirical false discovery rate (FDR) calculated by quantifying the percentage of control signal blocks remaining out of the total above the thresholdCC BY · PubMed Central

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 21 references

Cited by

Sorted by citations

Items 501–567 of 567

Metadata

Authors
Meers, M. P., Tenenbaum, D., & Henikoff, S.
Affiliations
  • Fred Hutch Cancer Center (US)
  • Howard Hughes Medical Institute (US)
Corresponding author
Henikoff, Steven
Venue
Epigenetics & Chromatin
Published
2019-07-12
Volume
12
Issue
1
Pages
42-42
ISSN
1756-8935 (ISSN-L)
OpenAlex
W2958184371
Cited by
556
References
21
Citations by year
2026: 86 · 2025: 123 · 2024: 126 · 2023: 95 · 2022: 65 · 2021: 44 · 2020: 16
FWCI
10.34
Type
journal article
Language
en
Open access
Locations
  • Epigenetics & Chromatin (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • Howard Hughes Medical Institute (Henikoff)
  • National Human Genome Research Institute (1R01HG010492)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Chromatin Remodeling and Cancer
Keywords
peak calling, CUT&RUN, chromatin profiling, protein-DNA binding sites, epigenetic profiling, web server
MeSH terms
Algorithms, Animals, Binding Sites, Chromatin, DNA-Binding Proteins, Humans, Protein Binding, Genome, Sequence Analysis, DNA, Epigenesis, Genetic, Chromatin Immunoprecipitation, Epigenomics

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review