Skip to Main Content

HSLS MolBio Workshops

Information & resources for hands-on bioinformatics classes.

Objective

This is a two-part workshop. Part-1, starts with a presentation from the Genomics Research Core on best practices in sample handling, followed by a brief introduction to techniques, platforms, and methods used in bulk RNA-Seq experiments.  Part-2, focuses on software demonstration using the HSLS-licensed CLC Genomics Workbench.

Participants will learn how to

  • access the CLCbio Genomics Server hosted on the HTC Cluster by Pitt CRC
  • import RNA-Seq FASTQ reads from a GEO dataset
  • assess the quality of RNA-Seq data
  • align reads to a reference genome
  • estimate known gene and transcript expression
  • perform differential expression analysis
  • visualize data by generating PCA and heatmaps

Target Audience

Experimental biologists seeking to analyze bulk RNA-Seq data generated through experiments or retrieved from a repository such as GEO. The software covered in the workshop operates through a user-friendly, point-and-click graphical user interface, so neither programming experience nor familiarity with the command line interface is required.

Workshop Materials

Powerpoints

Lecture Videos

Data Download

Software Registration

Tutorials and Documentations

Databases and Tools

References

Publications citing CLC-Genomics Workbench from Pitt researchers (279 as of June 14, 2022)

 

Attribution

Please include the following statement in the acknowledgments section for all publications, posters, and presentations: 

CLC Genomics Workbench software licensed through the Molecular Biology Information Service of the Health Sciences Library System, University of Pittsburgh  (RRID:SCR_011975) was used for data analysis.

If you used the Pitt-CRC server for CLC Genomics Workbench, then please also include the following text in the acknowledgments section for all publications, posters, and presentations: 

This research was supported in part by the University of Pittsburgh Center for Research Computing through the resources provided.