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OneStopRNAseq: A Web Application for Comprehensive and Efficient Analyses of RNA-Seq Data.

Rui LiKai HuHaibo LiuMichael R GreenJulie Lihua Zhu
Published in: Genes (2020)
Over the past decade, a large amount of RNA sequencing (RNA-seq) data were deposited in public repositories, and more are being produced at an unprecedented rate. However, there are few open source tools with point-and-click interfaces that are versatile and offer streamlined comprehensive analysis of RNA-seq datasets. To maximize the capitalization of these vast public resources and facilitate the analysis of RNA-seq data by biologists, we developed a web application called OneStopRNAseq for the one-stop analysis of RNA-seq data. OneStopRNAseq has user-friendly interfaces and offers workflows for common types of RNA-seq data analyses, such as comprehensive data-quality control, differential analysis of gene expression, exon usage, alternative splicing, transposable element expression, allele-specific gene expression quantification, and gene set enrichment analysis. Users only need to select the desired analyses and genome build, and provide a Gene Expression Omnibus (GEO) accession number or Dropbox links to sequence files, alignment files, gene-expression-count tables, or rank files with the corresponding metadata. Our pipeline facilitates the comprehensive and efficient analysis of private and public RNA-seq data.
Keyphrases
  • rna seq
  • single cell
  • gene expression
  • electronic health record
  • big data
  • dna methylation
  • healthcare
  • mental health
  • quality control
  • poor prognosis
  • genome wide
  • machine learning
  • data analysis