SCpipeline: The Tool and Web Service for Identifying Potential Drug Targets Based on Single-Cell RNA Sequencing Data

Single-cell RNA sequencing (scRNA-seq) technology can provide gene expression information at single cell level. A computational system (SCpipeline) for identifying potential drug targets by comparing differential interactions between cells was constructed and can be served as online computation. SCpipeline takes scRNA-Seq data from disease and their control tissues as input, and predicts potential ligand-receptor pairs that can be used as potential therapeutic targets through computational processes including cell sorting, cell type annotation, tumor cell identification, differential expression analysis, enrichment analysis, and scoring for cell interaction. The analysis process was validated for each part of SCpipeline on public data. By applying this system to the datasets of intrahepatic cholangiocarcinoma, renal cancer, and colorectal cancer, 26, 63, and 8 differential interaction pairs (p < 0.05) were identified, respectively, including ITGB2 − ICAM1, MDK − (ITGA4 + ITGB1), KITL–KIT, JAG1 − NOTCH3, LAMA5 − DAG1 and other differentially expressed receptor-ligand pairs that act in angiogenesis, cell proliferation and other pathways closely related to tumor development. These results suggest that SCpipeline can be used to full-chart analysis for scRNA-Seq data, and can identify differential cellular interactions to inform drug target selection.