HSLS MolBio Workshops

This page contains resources - PowerPoint slides, lecture videos, datasets for a software demonstration, etc. -  for HSLS molbio information service offered workshops on scRNA-seq data analysis using PartekFlow and CLC Genomics workbench.

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.

PowerPoints

• scRNA-seq data analysis using Partek Flow (03/15/2022)
• Genomics Core Presentation (11/03/2021)
• software demonstration on scRNA-seq data analysis using Partek Flow (11/03/2021) 
• scRNA-seq data analysis using CLC Genomics Workbench (03/29/2022)
• software demonstration on CITE-seq and spatial transcriptomics data analysis using Partek Flow (04/27/2022)

Lecture Videos

HSLS MBIS Workshop

scRNA-Seq

• 10X Single-Cell sequencing - Laboratory processing (45 min)  - Janette Lamb, Ph.D., Genomics Core Director (11/03/2021)

PartekFlow

• Part1, the morning session of the March 3, 2021 workshop (2 hrs) - covers Genomics Core presentation on best practices of the sample preparation, introduction to PartekFlow software, and an overview of basic steps for scRNA-seq data analysis.
• Part2, the afternoon session of the March 3, 2021 workshop (2 hrs) - covers a step-by-step guide on analyzing scRNA-seq data (Supercentenarian vs. control dataset, PNAS paper) using the HSLS licensed Partek Flow software.
• CITE-Seq analysis using Partek flow - covers CITE-Seq concepts and analysis pipeline using HSLS licensed Partek flow software.
• Spatial Transcriptomics analysis using Partek flow - covers Spatial Transcriptomics overview, concepts, and also analysis steps using Partek Flow software.

CLC Genomics Workbench

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

Data Download

• CITE-Seq - 
  • Datasets Summary - 5k Peripheral Blood Mononuclear Cells (PBMCs) from a Healthy Donor with a Panel of TotalSeq™-B Antibodies (v3 chemistry)
  • Feature/Cell matrix (HDF5)
• Spatial Transcriptomics - 
  • Normal Human Prostate (FFPE) Spatial Gene Expression Dataset by Space Ranger 1.3.0 
    • Datasets Summary - 
    • Feature / barcode matrix HDF5 (filtered)
    • Image file
  • Human Prostate Cancer, Adenocarcinoma with Invasive Carcinoma (FFPE)
    • Datasets Summary 
    • Feature / barcode matrix HDF5 (filtered)
    • Image file
• scRNA-Seq -
  • Human PBMC ScRNA-seq data (1K Cells) from a healthy donor are available at 10X Genomics site - FASTQ and Count Matrix
  • GSE125416  (HDF5; MEX); Single-Cell RNA-Sequencing of Human Embryonic Stem Cell Differentiation Delineates Adverse Effects of Nicotine on Embryonic Development
  • GSE161267 (MEX); A single-cell atlas of human teeth
  • Supercentenarian vs. control dataset (PNAS paper) - PartekFlow project file (zip)

Software Registration

• HSLS Software Registration for PartekFlow and CLC Genomics Workbench
• BioRender - Scientific illustrations creating tool

Partek  Webinars

• Basic scRNA-seq data analysis (1 hr) - single sample; PBMC 5K dataset
• Advanced scRNA-seq data analysis (1hr)- multi-samples; Supercentenarian vs. control dataset, PNAS pape
• Analyzing CITE-Seq Data

• Processing Cell Hashing Data ( How-to Video)
• Importing Multi Samples from GEO (How-to Video)
• Importing Multi-Omics Data (How-to Video)
• Trajectory Analysis in Partek Flow (Video)

CLC Genomics Webinar

• Single-cell RNA-seq data analysis and interpretation

Statistics

• PCA explained (StatQuest)
• t-SNE explained (StatQuest)

• A Guide to scRNA-Seq Normalization - BioTouring Blog

• The Essence of scRNA-Seq Clustering: Why and How to Do it Right - BioTouring Blog

• scRNA-Seq Cell Type Annotation: Common Approaches and Tools - BioTouring Blog

• Comparing UMAP vs t-SNE in Single-cell RNA-Seq Data Visualization, Simply Explained - BioTouring Blog

• The Why, When and How of 3D PCA - BioTouring Blog

• Partek Flow Manual
• CLC Genomics Workbench Manual 
• Introduction to single-cell RNA-seq technologies
• SequenceENG: an interactive learning resource for next-generation sequencing (NGS) techniques
• Babraham FastQC report : 
• 10X Genomics for single-cell gene expression
• The Human Cell Atlas
• RNA-seq Blog
• SEQanswers
• Biostars 
• BioRender - Scientific illustrations creating tool

Databases

• ASAP Automated Single-cell Analysis Pipeline
• Curated Database of published single cell transcriptomics
• Biotouring Browser
• Cell Marker
• Panglao db
• PanglaoDB_Cellmarkes (03/27/2020)
• scRNA-Seq Tools Database
• scRNASeqDB
• Single Cell Expression Atlas
• Single Cell Portal (Broad Institute)
• Tabula Muris 

Software

• Venn Diagram Creator
• Cell Ranger
• Space Ranger
• Cell Number Calculator 
• Azimuth - a tool for rapid mapping of query datasets to references
• Garnett - a tool for automated cell type classification
• Awesome-single-cell - List of software packages (and the people developing these methods) for single-cell data analysis, including RNA-seq, ATAC-seq, etc.
• BioRender - Scientific illustrations creating tool

• *Introduction to Single‐Cell RNA Sequencing
• *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
• *CellMarker: a manually curated resource of cell markers in human and mouse
• *PanglaoDB: a web server for exploration of mouse and human single-cell RNA sequencing data
• Integrative single-cell analysis
• Massively parallel digital transcriptional profiling of single cells
• Single-cell RNA sequencing: Technical advancements and biological applications
• Comparative analysis of differential gene expression analysis tools for single-cell RNA sequencing data 
• Stoeckius, M. et al. Simultaneous epitope and transcriptome measurement in single cells. Nat. Methods 14, 865–868 (2017).
• Hao, Y. et al. Integrated analysis of multimodal single-cell data. Cell 184, 3573-3587.e29 (2021).
• Larsson, L., Frisén, J. & Lundeberg, J. Spatially resolved transcriptomics adds a new dimension to genomics. Nat. Methods 18, 15–18 (2021).
• Method of the Year 2020: spatially resolved transcriptomics. Nat. Methods 18, 1 (2021).

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 was used for data analysis.

Feedback

Please evaluate the workshop

• CITE-Seq and Spatial Transcriptomics

Support

• Request for consultation w/ HSLS-MBIS
• Post questions or comments here