PT  - JOURNAL ARTICLE
AU  - Marmar Moussa
AU  - Ion I. Măndoiu
TI  - SC1: A Tool for Interactive Web-Based Single Cell RNA-Seq Data Analysis
AID  - 10.1101/2021.03.19.435534
DP  - 2021 Jan 01
TA  - bioRxiv
PG  - 2021.03.19.435534
4099  - http://biorxiv.org/content/early/2021/03/20/2021.03.19.435534.short
4100  - http://biorxiv.org/content/early/2021/03/20/2021.03.19.435534.full
AB  - Single cell RNA-Seq (scRNA-Seq) is critical for studying cellular function and phenotypic heterogeneity as well as the development of tissues and tumors. Here, 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 (TF-IDF) 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 like 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.Competing Interest StatementThe authors have declared no competing interest.