Nature CommunicationsBioinformaticsPeer-reviewed journal article
Bulk Tissue Cell Type Deconvolution with Multi-Subject Single-Cell Expression Reference
Xuran WangiD, Jihwan ParkiD, Katalin SusztákiD, Nancy Ruonan ZhangiD, Mingyao LiiD
Abstract
We present MuSiC, a method that utilizes cell-type specific gene expression from single-cell RNA sequencing (RNA-seq) data to characterize cell type compositions from bulk RNA-seq data in complex tissues. When applied to pancreatic islet and whole kidney expression data in human, mouse, and rats, MuSiC outperformed existing methods, especially for tissues with closely related cell types. MuSiC enables characterization of cellular heterogeneity of complex tissues for identification of disease mechanisms.
- organism: human
- organism: mouse
- organism: rat
- assay: bulk RNA-seq
- assay: scRNA-seq
- research focus: deconvolution
- approach: statistical model
- Citations
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- FWCI
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- Field percentile
- top 1%
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