Discovery and construction of prognostic model for clear cell renal cell carcinoma based on single-cell and bulk transcriptome analysis.

ABSTRACT:

Background

Clear cell renal cell carcinoma (ccRCC) is the most common malignant kidney tumor in adults. Single-cell transcriptome sequencing can provide accurate gene expression data of individual cells. Integrated single-cell and bulk transcriptome data from ccRCC samples provide comprehensive information, which allows the discovery of new understandings of ccRCC and the construction of a novel prognostic model for ccRCC patients.

Methods

Single-cell transcriptome sequencing data was preprocessed by using the Seurat package in R software. Principal component analysis (PCA) and the t-distributed stochastic neighbor embedding (t-SNE) algorithm were used to perform cluster classification. Two subtypes of cancer cells were identified, pseudotime trajectory analysis and gene ont

SUBMITTER: Zhang F 

PROVIDER: S-EPMC8511535 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature