A novel method for predicting cell abundance based on single-cell RNA-seq data.

ABSTRACT:

Background

It is important to understand the composition of cell type and its proportion in intact tissues, as changes in certain cell types are the underlying cause of disease in humans. Although compositions of cell type and ratios can be obtained by single-cell sequencing, single-cell sequencing is currently expensive and cannot be applied in clinical studies involving a large number of subjects. Therefore, it is useful to apply the bulk RNA-Seq dataset and the single-cell RNA dataset to deconvolute and obtain the cell type composition in the tissue.

Results

By analyzing the existing cell population prediction methods, we found that most of the existing methods need the cell-type-specific gene expression profile as the input of the signature matrix. However, in real appli

SUBMITTER: Peng J 

PROVIDER: S-EPMC8386079 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature