Skip to content

Sumstats Epigenetics Single cell

Curation of Single cell within Epigenetics — listings under the Summary statistics tab.

Summary Table

Click a column header to sort the table.

NAME Main citation YEAR
CIMA
Yin J et al., Science, 2026
2026

CIMA

Summary statistics
PUBMED_LINK
41505528
DESCRIPTION
Chinese Immune Multi-Omics Atlas
URL
https://db.cngb.org/trueblood/cima
TITLE
Chinese Immune Multi-Omics Atlas.
Main citation
Yin J, Zheng Y, Huang Z, Zhou W, ...&, Liu C. (2026) Chinese Immune Multi-Omics Atlas. Science, 391 (6781) eadt3130. doi:10.1126/science.adt3130. PMID 41505528
ABSTRACT
Human peripheral blood exhibits molecular and cellular heterogeneity across populations, yet the underlying mechanisms remain unclear. We present the Chinese Immune Multi-Omics Atlas (CIMA), characterizing molecular variations linked to sex, age, and genetic variants through multi-omics analysis of more than 10 million circulating immune cells from 428 Chinese adults. CIMA established an enhancer-driven gene regulatory network comprising 237 robust regulons; identified 9600 eGenes and 52,361 caPeaks at cell type resolution; and revealed pleiotropic associations among immune-related disease risk loci, cis-expression quantitative trait loci (QTLs), and chromatin accessibility QTLs. Furthermore, the cell language model CIMA-CLM predicted chromatin accessibility and evaluated the effects of noncoding variants from chromatin sequences and gene expression. CIMA provides a comprehensive reference for immune-related disease research.
DOI
10.1126/science.adt3130