Evidence map›Paper›PMID 40791457›Full record

ArticlebioRxiv : the preprint server for biology2025

Quality control of single-cell ATAC-seq data without peak calling using Chromap.

Omar Ahmed, Haowen Zhang, Ben Langmead, Li Song

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Omar AhmedDepartment of Computer Science, Johns Hopkins University, Baltimore, MD, USA.ORCID 0000-0002-9933-8508
Haowen ZhangSchool of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, GA, USA.
Ben LangmeadDepartment of Computer Science, Johns Hopkins University, Baltimore, MD, USA.ORCID 0000-0003-2437-1976
Li SongDepartment of Biomedical Data Science, Dartmouth College, Hanover, NH, USA.ORCID 0000-0002-0180-7426

Funding

Zhao - Proj 2P20GM130454 · NIGMS · DARTMOUTH COLLEGE · PI Li Song · 2019 to 2026
$27.2M
Methods for sequencing data analysis and archive-scale data science - RenewalR35GM139602 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI Benjamin Thomas Langmead · 2021 to 2026
$5.0M
Personal and panel references for improved alignmentR01HG011392 · NHGRI · JOHNS HOPKINS UNIVERSITY · PI LANGMEAD, BENJAMIN THOMAS · 2020 to 2025
$4.2M
NHGRI NIH HHS R01 HG011392NIGMS NIH HHS P20 GM130454NIGMS NIH HHS R35 GM139602
6 · The paper itself

Abstract

In this work, we extend Chromap, an ultrafast method for single-cell ATAC-seq data alignment, to directly report peak-based quality control (QC) metrics, such as the fraction of reads in peaks, without calling peaks. Recent single-cell ATAC-seq analysis methods like SnapATAC2 utilize the genome-interval-based feature for data analysis, which disables filtering low-quality cells using common peak-based QC metrics. We show that Chromap's QC metrics capture additional low-quality cells missed by SnapATAC2 and improve downstream analysis results without sacrificing computational efficiency.

Indexed as

quality controlSingle-cell ATAC-seqsketch

Identifiers

PMID40791457
PMCPMC12338639

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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.