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cellSTAAR: incorporating single-cell-sequencing-based functional data to boost power in rare variant association testing of noncoding regions

Van Buren, Eric
; 
Zhang, Yi
; 
Li, Xihao
; 
Selvaraj, Margaret Sunitha
; 
Li, Zilin
; 
Zhou, Hufeng
; 
Palmer, Nicholette D
; 
Arnett, Donna K
; 
Blangero, John
; 
Boerwinkle, Eric
... show 10 more
Author
Van Buren, Eric
Zhang, Yi
Li, Xihao
Selvaraj, Margaret Sunitha
Li, Zilin
Zhou, Hufeng
Palmer, Nicholette D
Arnett, Donna K
Blangero, John
Boerwinkle, Eric
Cade, Brian E
Carlson, Jenna C
Carson, April P
Chen, Yii-Der Ida
Curran, Joanne
Duggirala, Ravindranath
Fornage, Myriam
Franceschini, Nora
Graff, Misa
Gu, Charles
Guo, Xiuqing
He, Jiang
Heard-Cosa, Nancy
Hou, Lifang
Hung, Yi-Jen
Kalyani, Rita R
Kardia, Sharon LR
Kenny, Eimear
Kooperberg, Charles
Kral, Brian G
Lange, Leslie
Levy, Dan
Li, Changwei
Liu, Simin
Lloyd-Jones, Donald
Loos, Ruth JF
Manichaikul, Ani W
Martin, Lisa Warsinger
Mathias, Rasika
Minster, Ryan L
Mitchell, Braxton D
Mychaleckyj, Josyf C
Naseri, Take
North, Kari
O’Connell, Jeff
Perry, James A
Peyser, Patricia A
Psaty, Bruce M
Raffield, Laura M
Vasan, Ramachandran S
Redline, Susan
Reiner, Alex P
Rich, Stephen S
Smith, Jennifer A
Spitzer, Brian
Tang, Hua
Taylor, Kent D
Tracy, Russell
Viali, Satupa’itea
Yanek, Lisa
Zhao, Wei
Rotter, Jerome I
Peloso, Gina M
Natarajan, Pradeep
Lin, Xihong
Bustamante, Carlos
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Department
Personalized Medicine
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Journal article
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English
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Abstract
Understanding how rare genetic variants influence complex traits remains a major challenge, particularly when these variants lie in noncoding regions of the genome. The effects of variants within candidate cis-regulatory elements (cCREs) often depend on the cell type, making interpretation difficult. Here we introduce cellSTAAR, which integrates whole-genome sequencing data with single-cell assay for transposase-accessible chromatin using sequencing data to capture variability in chromatin accessibility across cell types via the construction of cell-type-specific functional annotations and regulatory elements. To reflect the uncertainty in cCRE–gene linking, cellSTAAR uses a comprehensive strategy to link cCREs to their target genes. We applied cellSTAAR to data from the Trans-Omics for Precision Medicine consortium (n ≈ 60,000) and replicated our findings using the UK Biobank (n ≈ 190,000). Across four lipid traits, cellSTAAR improved the detection of biologically meaningful associations and enhanced biological interpretability. These results demonstrate the potential of cell-type-aware approaches to boost discovery in rare variant whole-genome sequencing association studies.
Citation
E. Van Buren, Y. Zhang, X. Li, M.S. Selvaraj, Z. Li, H. Zhou , et al., "cellSTAAR: incorporating single-cell-sequencing-based functional data to boost power in rare variant association testing of noncoding regions," Nature Methods, vol. 23, no. 2, pp. 338-349, 2025, https://doi.org/10.1038/s41592-025-02919-5.
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Nature Methods
Conference
Keywords
31 Biological Sciences, 3102 Bioinformatics and Computational Biology, 3105 Genetics, Chromatin, Genetic Variation, Genome, Human, Genome-Wide Association Study, Humans, Polymorphism, Single Nucleotide, Regulatory Sequences, Nucleic Acid, Single-Cell Analysis, Whole Genome Sequencing, 3 Good Health and Well Being
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Springer Nature
DOI
10.1038/s41592-025-02919-5
Additional links
https://www.nature.com/articles/s41592-025-02919-5
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