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

被引:6
|
作者
Moussa, Marmar [1 ]
Mandoiu, Ion I. [2 ]
机构
[1] Univ Connecticut, Sch Med, Carole & Ray Neag Comprehens Canc Ctr, 263 Farmington Ave, Farmington, CT 06030 USA
[2] Univ Connecticut, Comp Sci & Engn Dept, Storrs, CT USA
关键词
cell cycle; clustering; scRNA-Seq; SC1; single-cell analysis; TF-IDF;
D O I
10.1089/cmb.2021.0051
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
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.
引用
收藏
页码:820 / 841
页数:22
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