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MicroRNA expression profling from 14 adult whole blood samples with flow cytometry cell fractions

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NIAID Data Ecosystem2026-05-02 收录
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https://www.ncbi.nlm.nih.gov/sra/SRP510338
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资源简介:
Cellular heterogeneity represents one of the foremost confounding factors currently facing omics study, including miRNAome. Statistical methods leveraging the cell-specificity of miRNA expression for deconvoluting the cellular mixture of heterogeneous biospecimens, may provide a solution. The objective of this study is to develop and validate an algorithm for the deconvolution of heterogeneous samples such as whole blood based on miRNA expression profiling data. Overall design: Fourteen adult blood donors were included in the study. From each individual, global miRNA expression levels were analyzed in the whole blood. In addition, cell fractions for eight immune cell types (CD4+ T cell, CD8+ T cell, B cell, NK cell, Monocytes, Neutrophil, Eosinophils and Basophil) were determined by flow cytometry.
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2025-07-10
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