Literature DB >> 34115950

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

Marmar Moussa1, Ion I Măndoiu2.   

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.

Entities:  

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

Mesh:

Year:  2021        PMID: 34115950     DOI: 10.1089/cmb.2021.0051

Source DB:  PubMed          Journal:  J Comput Biol        ISSN: 1066-5277            Impact factor:   1.479


  1 in total

1.  scCloudMine: A cloud-based app for visualization, comparison, and exploration of single-cell transcriptomic data.

Authors:  Mathew G Lewsey; Changyu Yi; Oliver Berkowitz; Felipe Ayora; Maurice Bernado; James Whelan
Journal:  Plant Commun       Date:  2022-01-22
  1 in total

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