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

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. 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.

SCALA: A web application for multimodal analysis of single cell next generation sequencing data

“…It handles both raw and pre-processed datasets, thus giving the users the flexibility to perform their analysis from-scratch, or to visualize and reanalyze already processed data. For comparison, we report a catalog of similar tools (e.g., pagoda2, SingleCAnalyzer (55), Bingle-seq (56), iCellR (57), cerebro (29), Is-CellR (58), SeuratWizard (31), ICARUS (59), SC1 (60), alona (61), WASP (62), CHIPSTER (63), Asc-Seurat (64), GenePattern (65), PIVOT (66) and we highlight their pros and cons along with their complementarity to SCALA (Supplementary Table 1). To this end, it is worth mentioning that to our knowledge, only icellR (67) offers scATAC seq analysis whereas only six applications are available as web server applications.…”