Evidence map›Paper›PMID 40027737›Full record

ArticlebioRxiv : the preprint server for biology2025

Reducing batch effects in single cell chromatin accessibility measurements by pooled transposition with MULTI-ATAC.

Daniel N Conrad, Kiet T Phong, Ekaterina Korotkevich, Christopher S McGinnis, Qin Zhu, Eric D Chow, Zev J Gartner

Abstract readPreprint
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

7 authors.

Daniel N ConradDepartment of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA 94158, USA.ORCID 0000-0002-9562-0354
Kiet T PhongDepartment of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA 94158, USA.ORCID 0000-0002-9273-4276
Ekaterina KorotkevichDepartment of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA 94158, USA.ORCID 0000-0001-8861-2316
Christopher S McGinnisDepartment of Pathology, Stanford University, Stanford, CA 94305, USA.ORCID 0000-0001-6923-9341
Qin ZhuDepartment of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA 94158, USA.ORCID 0000-0001-5539-6071
Eric D ChowDepartment of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA 94158, USA.ORCID 0000-0001-8079-918X
Zev J GartnerDepartment of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA 94158, USA.ORCID 0000-0001-7803-1219

Funding

MULTIseq: multiplexing massively parallel single cell transcriptional analysis across time, space, and conditionsR01GM135462 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI GARTNER, ZEV JORDAN · 2019 to 2022
$1.3M
Universal Sample Multiplexing for Single Cell AnalysisR33CA247744 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI GARTNER, ZEV JORDAN · 2021 to 2023
$1.2M
NCI NIH HHS R33 CA247744NIGMS NIH HHS R01 GM135462
6 · The paper itself

Abstract

Large-scale scATAC-seq experiments are challenging because of their costs, lengthy protocols, and confounding batch effects. Several sample multiplexing technologies aim to address these challenges, but do not remove batch effects introduced when performing transposition reactions in parallel. We demonstrate that sample-to-sample variability in nuclei-to-Tn5 ratios is a major cause of batch effects and develop MULTI-ATAC, a multiplexing method that pools samples prior to transposition, as a solution. MULTI-ATAC provides high accuracy in sample classification and doublet detection while eliminating batch effects associated with variable nucleus-to-Tn5 ratio. We illustrate the power of MULTI-ATAC by performing a 96-plex multiomic drug assay targeting epigenetic remodelers in a model of primary immune cell activation, uncovering tens of thousands of drug-responsive chromatin regions, cell-type specific effects, and potent differences between matched inhibitors and degraders. MULTI-ATAC therefore enables batch-free and scalable scATAC-seq workflows, providing deeper insights into complex biological processes and potential therapeutic targets.

Identifiers

PMID40027737
PMCPMC11870453

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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.