An improved reference library and method for accurate cell-type deconvolution of bulk-tissue miRNA data.

ABSTRACT: MicroRNAs (miRNAs) play key roles in development and disease, and have great biomarker potential. However, because miRNA expression is highly cell-type specific, identifying miRNA biomarkers from complex tissues is hampered by the underlying cell-type heterogeneity. Due to that current single-cell RNA-Seq protocols are lagging behind for quantification of miRNA expression, and most miRNA profiling samples do not have matched mRNA expression or DNA methylation data for cell-type deconvolution, it is an urgent need to develop computational methods for cell-type proportion estimation of bulk-tissue miRNA data. Here we present a novel miRNA expression reference library and deconvolution tool for cell-type composition estimation of complex tissues. We show that our tool is accurate and robust f

SUBMITTER: Zhu S 

PROVIDER: S-EPMC12215801 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature