Omnibus and robust deconvolution scheme for bulk RNA sequencing data integrating multiple single-cell reference sets and prior biological knowledge.

ABSTRACT:

Motivation

Cell-type deconvolution of bulk tissue RNA sequencing (RNA-seq) data is an important step toward understanding the variations in cell-type composition among disease conditions. Owing to recent advances in single-cell RNA sequencing (scRNA-seq) and the availability of large amounts of bulk RNA-seq data in disease-relevant tissues, various deconvolution methods have been developed. However, the performance of existing methods heavily relies on the quality of information provided by external data sources, such as the selection of scRNA-seq data as a reference and prior biological information.

Results

We present the Integrated and Robust Deconvolution (InteRD) algorithm to infer cell-type proportions from target bulk RNA-seq data. Owing to the innovative use of penali

SUBMITTER: Chen C 

PROVIDER: S-EPMC9525013 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature