scDrug: From single-cell RNA-seq to drug response prediction

Single-cell RNA sequencing (scRNA-seq) technology allows massively parallel characterization of thou-sands 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 identifica-tion 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.(c) 2022 The Authors. Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology. This is an open access article under the CC BY license (http://creativecommons. org/licenses/by/4.0/).

Automated summary

Single-cell RNA sequencing (scRNA-seq) technology is a powerful tool for investigating cellular components and interactions in the tumor microenvironment. It has also been used to study the association between tumor microenvironmental patterns and clinical outcomes, and to analyze the effects of drug treatment on specific cell populations. Recent advances in scRNA-seq have led to the discovery of biomarkers and therapeutic targets. The scDrug bioinformatics workflow provides a one-step pipeline for scRNA-seq data analysis and drug prediction, facilitating the exploration of scRNA-seq data and drug repurposing.