期刊
GENOME BIOLOGY
卷 21, 期 1, 页码 -出版社
BMC
DOI: 10.1186/s13059-020-1932-8
关键词
Integrative analysis; Single-cell multiomics; Simultaneous measurements; Sparse epigenomic profile
资金
- NSF [DMS1763272]
- Simons Foundation [594598]
- NIH [U01AR073159, R01GM123731, P30AR07504]
Simultaneous measurements of transcriptomic and epigenomic profiles in the same individual cells provide an unprecedented opportunity to understand cell fates. However, effective approaches for the integrative analysis of such data are lacking. Here, we present a single-cell aggregation and integration (scAI) method to deconvolute cellular heterogeneity from parallel transcriptomic and epigenomic profiles. Through iterative learning, scAI aggregates sparse epigenomic signals in similar cells learned in an unsupervised manner, allowing coherent fusion with transcriptomic measurements. Simulation studies and applications to three real datasets demonstrate its capability of dissecting cellular heterogeneity within both transcriptomic and epigenomic layers and understanding transcriptional regulatory mechanisms.
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