Evidence map›Paper›PMID 42167226›Full record

ArticleCell reports methods2026

ATACompass enables cross-species cell identity mapping for scATAC-seq without gene annotations.

Jie Jiang, Yali Ding, Bu Jin, Guole Liu, Siqi Wang, Ying Zhang, Yong Wang, Xin Li, Jing Liu, Wei Li and 1 more

Abstract read
In one paragraph

Article in Cell reports methods, 2026. 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
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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

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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

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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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

11 authors.

Jie JiangState Key Laboratory of Organ Regeneration and Reconstruction, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.
Yali DingState Key Laboratory of Organ Regeneration and Reconstruction, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China.
Bu JinUniversity of Chinese Academy of Sciences, Beijing 100049, China; Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.
Guole LiuState Key Laboratory of Organ Regeneration and Reconstruction, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; Beijing Institute for Stem Cell and Regenerative Medicine, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China.
Siqi WangState Key Laboratory of Organ Regeneration and Reconstruction, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; Beijing Institute for Stem Cell and Regenerative Medicine, Beijing 100101, China.
Ying ZhangState Key Laboratory of Organ Regeneration and Reconstruction, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; Beijing Institute for Stem Cell and Regenerative Medicine, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China.
Yong WangUniversity of Chinese Academy of Sciences, Beijing 100049, China; CEMS, NCMIS, HCMS, MADIS, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China.
Xin LiState Key Laboratory of Organ Regeneration and Reconstruction, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; Beijing Institute for Stem Cell and Regenerative Medicine, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China. Electronic address: xinli@ioz.ac.cn.
Jing LiuInstitute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China. Electronic address: jliu@nlpr.ia.ac.cn.
Wei LiState Key Laboratory of Organ Regeneration and Reconstruction, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; Beijing Institute for Stem Cell and Regenerative Medicine, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China. Electronic address: liwei@ioz.ac.cn.
Guihai FengState Key Laboratory of Organ Regeneration and Reconstruction, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; Beijing Institute for Stem Cell and Regenerative Medicine, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China. Electronic address: fenggh@ioz.ac.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Single-cell assay for transposase-accessible chromatin with sequencing (scATAC-seq) provides insights into transcriptional regulation, but there remain challenges in cell identity annotation due to data sparsity and limited gene regulatory annotations, particularly in non-model organisms. To address these limitations, we present ATACompass, a sequence-based framework for cell annotation that directly encodes chromatin accessibility peak sequences using the DNA foundation model HyenaDNA and large language models. By incorporating controlled sequence mutations for data augmentation, ATACompass achieves performance competitive with or superior to existing state-of-the-art methods in intra-species tasks. Critically, ATACompass enables zero-shot cross-species cell annotation by restricting input data to conserved sequences shared between species, allowing non-model organism data to be annotated without species-specific prior knowledge. Furthermore, the integration of datasets from representative evolutionary lineages enhances predictive accuracy, enabling comprehensive annotation across species. In summary, ATACompass provides a gene annotation-independent framework for studying cell types and regulatory landscapes, especially in non-model organisms.

Indexed as

Chromatin Immunoprecipitation SequencingMolecular Sequence AnnotationSingle-Cell AnalysisAnimalsChromatinComputational BiologyHumansSpecies SpecificityTransposasesChromatinTransposasescell type annotationCP: computational biologyCP: systems biologycross speciesDNA foundational modelsscATAC-seqsequence-based prediction

Identifiers

PMID42167226
PMCPMC13390006

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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.