scDrug: From single-cell RNA-seq to drug response prediction.
Comput Struct Biotechnol J
; 21: 150-157, 2023.
Article
de En
| MEDLINE
| ID: mdl-36544472
ABSTRACT
Single-cell RNA sequencing (scRNA-seq) technology allows massively parallel characterization of thousands of cells at the transcriptome level. scRNA-seq is emerging as an important tool to investigate the cellular components and their interactions in the tumor microenvironment. scRNA-seq is also used to reveal the association between tumor microenvironmental patterns and clinical outcomes and to dissect cell-specific effects of drug treatment in complex tissues. Recent advances in scRNA-seq have driven the discovery of biomarkers in diseases and therapeutic targets. Although methods for prediction of drug response using gene expression of scRNA-seq data have been proposed, an integrated tool from scRNA-seq analysis to drug discovery is required. We present scDrug as a bioinformatics workflow that includes a one-step pipeline to generate cell clustering for scRNA-seq data and two methods to predict drug treatments. The scDrug pipeline consists of three main modules scRNA-seq analysis for identification of tumor cell subpopulations, functional annotation of cellular subclusters, and prediction of drug responses. scDrug enables the exploration of scRNA-seq data readily and facilitates the drug repurposing process. scDrug is freely available on GitHub at https//github.com/ailabstw/scDrug.
Texte intégral:
1
Collection:
01-internacional
Base de données:
MEDLINE
Type d'étude:
Prognostic_studies
/
Risk_factors_studies
Langue:
En
Journal:
Comput Struct Biotechnol J
Année:
2023
Type de document:
Article
Pays d'affiliation:
Taïwan