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

被引:7
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
相关论文
共 38 条
[1]  
AllenInstitute, 2018, SCRATTCH VIS
[2]  
[Anonymous], 2001, Bioinformatics, DOI [DOI 10.1093/BIOINFORMATICS/17.SUPPL1.S22, DOI 10.1093/BIOINFORMATICS/17.SUPPL_1.S22]
[3]   An unbiased approach to defining bona fide cancer neoepitopes that elicit immune-mediated cancer rejection [J].
Brennick, Cory A. ;
George, Mariam M. ;
Moussa, Marmar M. ;
Hagymasi, Adam T. ;
Al Seesi, Sahar ;
Shcheglova, Tatiana V. ;
Englander, Ryan P. ;
Keller, Grant L. J. ;
Balsbaugh, Jeremy L. ;
Baker, Brian M. ;
Schietinger, Andrea ;
Mandoiu, Ion I. ;
Srivastava, Pramod K. .
JOURNAL OF CLINICAL INVESTIGATION, 2021, 131 (03)
[4]  
Consortium GO, 2004, Nucleic Acids Res, V32, pD258, DOI DOI 10.1093/NAR/GKH036
[5]  
Cooper G.M, 2000, CELL MOL APPROACH, V2
[6]   A high-resolution transcriptome map of cell cycle reveals novel connections between periodic genes and cancer [J].
Dominguez, Daniel ;
Tsai, Yi-Hsuan ;
Gomez, Nicholas ;
Jha, Deepak Kumar ;
Davis, Ian ;
Wang, Zefeng .
CELL RESEARCH, 2016, 26 (08) :946-962
[7]  
Erichson N.B., 2016, ARXIV PREPRINT ARXIV
[8]   Deconstructing Olfactory Stem Cell Trajectories at Single-Cell Resolution [J].
Fletcher, Russell B. ;
Das, Diya ;
Gadye, Levi ;
Street, Kelly N. ;
Baudhuin, Ariane ;
Wagner, Allon ;
Cole, Michael B. ;
Flores, Quetzal ;
Choi, Yoon Gi ;
Yosef, Nir ;
Purdom, Elizabeth ;
Dudoit, Sandrine ;
Risso, Davide ;
Ngai, John .
CELL STEM CELL, 2017, 20 (06) :817-+
[9]   High-Dimensional Analysis Delineates Myeloid and Lymphoid Compartment Remodeling during Successful Immune-Checkpoint Cancer Therapy [J].
Gubin, Matthew M. ;
Esaulova, Ekaterina ;
Ward, Jeffrey P. ;
Malkova, Olga N. ;
Runci, Daniele ;
Wong, Pamela ;
Noguchi, Takuro ;
Arthur, Cora D. ;
Meng, Wei ;
Alspach, Elise ;
Medrano, Ruan F. V. ;
Fronick, Catrina ;
Fehlings, Michael ;
Newell, Evan W. ;
Fulton, Robert S. ;
Sheehan, Kathleen C. F. ;
Oh, Stephen T. ;
Schreiber, Robert D. ;
Artyomov, Maxim N. .
CELL, 2018, 175 (04) :1014-+
[10]   SINCERA: A Pipeline for Single-Cell RNA-Seq Profiling Analysis [J].
Guo, Minzhe ;
Wang, Hui ;
Potter, S. Steven ;
Whitsett, Jeffrey A. ;
Xu, Yan .
PLOS COMPUTATIONAL BIOLOGY, 2015, 11 (11)