HArmonized single-cell RNA-seq Cell type Assisted Deconvolution (HASCAD).

ABSTRACT:

Background

Cell composition deconvolution (CCD) is a type of bioinformatic task to estimate the cell fractions from bulk gene expression profiles, such as RNA-seq. Many CCD models were developed to perform linear regression analysis using reference gene expression signatures of distinct cell types. Reference gene expression signatures could be generated from cell-specific gene expression profiles, such as scRNA-seq. However, the batch effects and dropout events frequently observed across scRNA-seq datasets have limited the performances of CCD methods.

Methods

We developed a deep neural network (DNN) model, HASCAD, to predict the cell fractions of up to 15 immune cell types. HASCAD was trained using the bulk RNA-seq simulated from three scRNA-seq datasets that have been norma

SUBMITTER: Chiu YJ 

PROVIDER: S-EPMC10619225 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature