This workshop will cover processing single-cell RNA-seq data using the HSLS-licensed PartekFlow software. Participants will learn how to  

• import FASTQ/Count matrix files from scRNA-Seq experiments to PartekFlow software
• perform quality checks (QC) on single-cell data 
• filter and normalize the data 
• generate PCA and t-SNE plots to visualize data 
• identify cell populations, and biomarkers 
• compute differential gene expressions between two cell populations and/or multiple samples 

Target Audience

Experimental biologists seeking to analyze scRNA-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.

Partek flow

PowerPoints

• scRNA-seq data analysis using Partek Flow (September 18, 2024)

Lecture Videos

• Introduction to scRNA-seq Technologies and Applications 

• Basic ScRNASeq Analysis - scRNA seq data analysis with Single sample video 

• Advanced ScRNASeq Analysis - scRNA seq data analysis with Multiple samples video

Workshop Dataset 

• scRNA-Seq Multisample Data -
  • Human PBMC ScRNA-seq Dataset (Young, Old and Frail, Luo et al.)  -
    • Count Matrix
    • Metadata

Software Registration

• HSLS Software Registration for PartekFlow/CLC Genomics Workbench

Partek Flow Manual

Partek flow Webinars

Other useful Vidoes

ScRNASeq Analysis using CLC Genomics Software :

Powerpoint :  scRNA-seq data analysis using CLC Genomics Workbench (03/29/2022)

Lecture video : Introduction to scRNA-seq data analysis using CLC Genomics Workbench (offered on 11/17/2021) (3 hrs)

Additional Datasets :

GSE161267 (MEX); A single-cell atlas of human teeth

CLC Genomics Webinar

• Single-cell RNA-seq data analysis and interpretation

• *Multidimensional single-cell analysis of human peripheral blood reveals characteristic features of the immune system landscape in aging and frailty. Nat Aging. 2022 Apr

• A hitchhiker’s guide to single-cell transcriptomics and data analysis pipelines. Genomics 

• *Current best practices in single‐cell RNA‐seq analysis: a tutorial
• A practical guide to single-cell RNA-sequencing for biomedical research and clinical applications
• Tutorial: guidelines for the experimental design of single-cell RNA sequencing studies
• Single-cell RNA sequencing technologies and bioinformatics pipelines
• Massively parallel digital transcriptional profiling of single cells
• Single-cell RNA sequencing: Technical advancements and biological applications
• Stoeckius, M. et al. Simultaneous epitope and transcriptome measurement in single cells. Nat. Methods 14, 865–868 (2017).

• Assessing GPT-4 for cell type annotation in single-cell RNA-seq analysis

• scGPT: toward building a foundation model for single-cell multi-omics using generative AI

• Hao, Y. et al. Integrated analysis of multimodal single-cell data. Cell 184, 3573-3587.e29 (2021).
• Single-cell gene set enrichment analysis and transfer learning for functional annotation of scRNA-seq data

Attribution

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

[software name, such as CLC Genomics workbench, Partek Flow ] 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.

Feedback

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scRNA-seq data analysis using PartekFlow

Support

• Request for consultation w/ HSLS-MBIS
• Contact Partek Support Team