Integration of Single-Cell RNA Sequencing and Bulk RNA Sequencing Data to Establish and Validate a Prognostic Model for Patients With Lung Adenocarcinoma.

ABSTRACT: Background: Lung adenocarcinoma (LUAD) remains a lethal disease worldwide, with numerous studies exploring its potential prognostic markers using traditional RNA sequencing (RNA-seq) data. However, it cannot detect the exact cellular and molecular changes in tumor cells. This study aimed to construct a prognostic model for LUAD using single-cell RNA-seq (scRNA-seq) and traditional RNA-seq data. Methods: Bulk RNA-seq data were downloaded from The Cancer Genome Atlas (TCGA) database. LUAD scRNA-seq data were acquired from Gene Expression Omnibus (GEO) database. The uniform manifold approximation and projection (UMAP) was used for dimensionality reduction and cluster identification. Weighted Gene Correlation Network Analysis (WGCNA) was

SUBMITTER: Jiang A 

PROVIDER: S-EPMC8829512 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature