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RNAseq data analysis using Galaxy

Author(s): Matthew Escobar1, Sam S Donovan2, Irina Makarevitch3, Bill Morgan4, Sabrina Robertson5

1. California State University San Marcos 2. University of Pittsburgh 3. Hamline University 4. The College of Wooster 5. North Carolina State University

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Summary:
This is a bioinformatics exercise intended for use in a computer lab setting with life science majors.

Licensed under CC Attribution-ShareAlike 4.0 International according to these terms

Version 4.0 - published on 26 Jul 2021 doi:10.25334/XHW8-7189 - cite this

Keywords

  1. Lab
  2. bioinformatics
  3. NCBI
  4. mapping
  5. Undergraduate
  6. workflow
  7. NIBLSE
  8. Galaxy
  9. RNAseq
  10. gene expression
  11. Advanced
  12. Extended Project
  13. Arabidopsis
  14. C1. Role of bioinformatics
  15. C2. Computational concepts
  16. C3. Statistical concepts
  17. C5. Data retrieval
  18. Incubated at NIBLSE
  19. differentially expressed genes

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    Contents:
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    Description

    This resource involves downloading RNAseq data sets from the NCBI Sequence Read Archive (SRA) and using Galaxy tools to identify differentially expressed genes. Different data sets and experimental questions can be explored. Students are introduced to all major computational steps in RNAseq data analysis, including the concept of computational pipelines/workflows.

    Notes

    Revisions to previous version: The student instructions in Version 4 have been updated to work with current ENSEMBL, Galaxy, and Panther web sites as of June 2021. In addition, one embedded question was removed, and grammatical and mechanical errors were corrected throughout. Read mapping with HISAT2 was included in the PowerPoint presentation.

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