Evidence map›Paper›PMID 37730813›Full record

ArticleNature communications2023

epiAneufinder identifies copy number alterations from single-cell ATAC-seq data.

Akshaya Ramakrishnan, Aikaterini Symeonidi, Patrick Hanel, Katharina T Schmid, Maria L Richter, Michael Schubert, Maria Colomé-Tatché

Open access · goldAbstract read
In one paragraph

Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
5.1field-weighted citation impact, top 4% 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

30 citing papers in PubMed, 33 citations in OpenAlex.

  1. FFPE-CUTAC: A Single Assay, Multiple Layers.bioRxiv : the preprint server for biology · 2026
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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

7 authors at 4 institutions in 2 countries.

Akshaya Ramakrishnan *Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.ORCID http://orcid.org/0000-0002-3897-5677
Aikaterini Symeonidi *Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany. aikaterini.symeonidi@helmholtz-munich.de.ORCID http://orcid.org/0000-0002-3729-3500
Patrick HanelInstitute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
Katharina T SchmidBiomedical Center (BMC), Physiological Chemistry, Faculty of Medicine, LMU Munich, Planegg-Martinsried, Germany.ORCID http://orcid.org/0000-0001-7082-1099
Maria L RichterBiomedical Center (BMC), Physiological Chemistry, Faculty of Medicine, LMU Munich, Planegg-Martinsried, Germany.ORCID http://orcid.org/0000-0002-8510-0128
Michael SchubertOncode Institute, Division of Cell Biology, Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, the Netherlands.ORCID http://orcid.org/0000-0002-6862-5221
Maria Colomé-TatchéInstitute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany. maria.colome@bmc.med.lmu.de.
Helmholtz Zentrum München · DEUrologische Klinik München · DEMedigene (Germany) · DEThe Netherlands Cancer Institute · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Single-cell open chromatin profiling via scATAC-seq has become a mainstream measurement of open chromatin in single-cells. Here we present epiAneufinder, an algorithm that exploits the read count information from scATAC-seq data to extract genome-wide copy number alterations (CNAs) for individual cells, allowing the study of CNA heterogeneity present in a sample at the single-cell level. Using different cancer scATAC-seq datasets, we show that epiAneufinder can identify intratumor clonal heterogeneity in populations of single cells based on their CNA profiles. We demonstrate that these profiles are concordant with the ones inferred from single-cell whole genome sequencing data for the same samples. EpiAneufinder allows the inference of single-cell CNA information from scATAC-seq data, without the need of additional experiments, unlocking a layer of genomic variation which is otherwise unexplored.

Indexed as

Chromatin Immunoprecipitation SequencingDNA Copy Number VariationsAlgorithmsChromatinChromatin

Identifiers

PMID37730813
PMCPMC10511508
OpenAlexW4386887711

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.