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Recently we have received some requests from CLC users (as well as CLC RNA-seq certification participants) to go over workflow construction and customization using CLC Genomics Workbench. Accordingly, we are hosting this training. The term workflow refers to bioinformatics secondary analysis pipelines such as DNA-seq, RNA-seq, OTU clustering, de novo assembly and more offered by CLC Genomics Workbench.

In this training, the trainer will go over

• The basics of workflow construction

• How to visualize different steps of the workflow and customize different settings

• How to edit workflows (add/remove steps, lock/unlock parameters and more)

• How to share workflows

• How to install workflows

• Other workflow related topics

Are you new to QIAGEN Ingenuity Pathway Analysis (IPA) or interested in expanding your skill set? Join us as we learn more on large dataset analysis and knowledge base queries using QIAGEN IPA.

You’ll learn to:

• Upload multiple dataset types (e.g., RNA-seq, proteomics, metabolomics) and perform interactive core/pathway analysis in IPA

• Learn how to interpret different results, including pathways, key regulators, impact on biological functions/diseases and more

• Compare different experimental conditions (e.g., single-cell clusters, disease types) and identify similarities and contrasts

• Generate a network for hypothesis generation, even without a dataset or experimental design

Already have an IPA license? Install IPA and start using it now:

https://qiagen.showpad.com/share/CBv30blCPKFDUYHRWtAvI

Learn more about IPA or request a free trial: https://digitalinsights.qiagen.com/ipa

This is a special session put together based on some of the questions we received in recent trainings. IPA allows you to take advantage of deep curate public data from sources such as GEO, GTEx, CPTAC, TCGA and more. This training will focus on below 2 questions mainly but possibly others we receive through the registration and during the live session.

1) How to locate pathway analysis of a deep curated public dataset? Example I am interested in 'disease vs normal' or 'treated vs untreated' or 'cell type 1 vs others' comparison from a study. How can I launch pathway analysis of such dataset through IPA project search?

2) I also want to investigate such studies and consortia at sample expression level. Example how is a specific gene or protein expressed in disease1 vs disease 2 vs normal tissue or treated vs untreated samples? For 2 genes can we generate a correlation plot?

The training may last only ~60min but reserving longer time in case we receive additional questions.

In this video, we show how to color cells based on the expression of genes of interest in a UMAP.  We also demonstrate how to examine expression values from the plot in a selected group of cells.

Recent training  webinar and tutorial that includes UMAP plot generation from single-cell data:

Single-cell RNA-seq, cell hashing and spatial transcriptomics

Tutorial: Perform Single-Cell RNA Expression and Velocity Analysis

Here are some quick tips on locating tools in CLC Genomics Workbench version 25+

How to  import and visualize spatial transcriptomics data in CLC

How to install the CLC network license manager, network licenses, and CLC Genomics Workbench on Windows

In this video, we demonstrate the different tools that can be launched directly from the UMAP plot with a simple right-click.

Recent training  webinar and tutorial that includes UMAP plot generation from single-cell data:

Single-cell RNA-seq, cell hashing and spatial transcriptomics

Tutorial: Perform Single-Cell RNA Expression and Velocity Analysis

Single cell expression matrices can be imported into CLC manually using the import single cell matrix tool or they can be imported automatically using workflows. https://resources.qiagenbioinformatics.com/manuals/clcsinglecellanalysis/current/index.php?manual=Import_Expression_Matrix.html