Improved RNA-seq Workflows Using CyVerse Cyberinfrastructure

Kapeel M. Chougule, Liya Wang, Joshua C. Stein, Xiaofei Wang, Upendra Kumar Devisetty, Robert R. Klein, Doreen Ware

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

RNA-seq is a vital method for understanding gene structure and expression patterns. Typical RNA-seq analysis protocols use sequencing reads of length 50 to 150 nucleotides for alignment to the reference genome and assembly of transcripts. The resultant transcripts are quantified and used for differential expression and visualization. Existing tools and protocols for RNA-seq are vast and diverse; given their differences in performance, it is critical to select an analysis protocol that is scalable, accurate, and easy to use. Tuxedo, a popular alignment-based protocol for RNA-seq analysis, has been updated with HISAT2, StringTie, StringTie-merge, and Ballgown, and the updated protocol outperforms its predecessor. Similarly, new pseudo-alignment-based protocols like Kallisto and Sleuth reduce runtime and improve performance. However, these tools are challenging for researchers lacking command-line experience. Here, we describe two new RNA-seq analysis protocols, in which all tools are deployed on CyVerse Cyberinfrastructure with user-friendly graphical user interfaces, and validate their performance using plant RNA-seq data.

Original languageEnglish
Article numbere53
JournalCurrent Protocols in Bioinformatics
Volume63
Issue number1
DOIs
StatePublished - Sep 2018
Externally publishedYes

Keywords

  • CyVerse
  • RNA-seq
  • bioinformatics
  • differential gene expression
  • discovery environment
  • pseudo-alignment based transcript quantification
  • reference guided gene expression
  • transcript assembly
  • tuxedo protocol

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