SC1: A Tool for Interactive Web-Based Single-Cell RNA-Seq Data Analysis

J Comput Biol. 2021 Jun 11. doi: 10.1089/cmb.2021.0051. Online ahead of print.

Abstract

Single-cell RNA-Seq (scRNA-Seq) is critical for studying cellular function and phenotypic heterogeneity as well as the development of tissues and tumors. In this study, we present SC1 a web-based highly interactive scRNA-Seq data analysis tool publicly accessible at https://sc1.engr.uconn.edu. The tool presents an integrated workflow for scRNA-Seq analysis, implements a novel method of selecting informative genes based on term-frequency inverse-document-frequency scores, and provides a broad range of methods for clustering, differential expression analysis, gene enrichment, interactive visualization, and cell cycle analysis. The tool integrates other single-cell omics data modalities such as T-cell receptor (TCR)-Seq and supports several single-cell sequencing technologies. In just a few steps, researchers can generate a comprehensive analysis and gain powerful insights from their scRNA-Seq data.

Keywords: SC1; TF-IDF; cell cycle; clustering; scRNA-Seq; single-cell analysis.