tv.qiagenbioinformatics.com

Part II: Formatting and Uploading your Data into IPA

Tue, 01 Jul 2025 11:37:04 GMT

Learn how to format your own data and how to upload it into IPA. IPA can upload your experimental data to enable you to perform pathways visualization, literature searches on the molecules in the dataset, and to perform the many different types of analyses offered in IPA. In this webinar we will use phosphoproteomics data as an example dataset.

Interested in learning more?

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

Mon, 26 Aug 2024 16:01:12 GMT

A slide illustrating some of the many result types/graphics you will be able to generate after this training. https://qiagen.showpad.com/share/jYTCDPNfz1SdIMPQPSPYS

Analyze and interpret your own single-cell RNA-seq data using QIAGEN CLC Genomics Workbench, starting with either FASTQ or matrix files.

Learn how to perform the different steps of secondary analysis on your single-cell RNA-seq data, such as:

• Importing your raw FASTQ or processed cell-matrix files
• Using preconfigured but customizable pipelines/workflows for single-cell RNA-seq data.
• Generating high-resolution visuals and other files from your analysis, for publications and biopharmaceutical discoveries.
o Dimension reduction (UMAP, t-SNE) plots
o Differential expression tables for clusters, cell types or a combination of both
o Heat maps o Dot plots o Violin plots
• Using the “Create Cell Annotations from Hashtags” tool for cell hashing (e.g., CITE-seq).
• Applying spatial transcriptomic analysis, the latest feature in the single-cell RNA-seq module

Exploring RNA-seq data using the CLC Genomics Workbench: Expression Analysis...

Wed, 24 Jan 2024 13:17:00 GMT

In this webinar, we will present how to analyze RNA-seq data starting from raw sequencing reads. We will touch upon expression analysis, statistical comparison, visualization and functional enrichment of RNA-seq data using an actual dataset and a live demo.

During this webinar we will cover:
• Mapping of reads to the reference and abundance estimation
• Principal component analysis (PCA) of RNA-seq data
• Differential expression analysis
• Visualization of results using volcano plots, heatmaps and Venn diagrams
• Creating RNA-seq expression table and adding GO annotations
• Gene set enrichment analysis using hypergeometric test
• Ready-to-use Workflows for expression analysis
• Upload to Ingenuity Pathway Analysis (IPA)

Delving into public single-cell RNA-seq data using QIAGEN OmicSoft and...

Fri, 28 Jul 2023 16:34:04 GMT

Single-cell RNA-sequencing (scRNA-seq) is widely used to study tissue heterogeneity, identify novel cell types, study pathogenic mechanisms, develop targeted therapies (including immunotherapy) and more. Accordingly, scientists have deposited a tremendous amount of scRNA-seq data into public domains like GEO.

In this training, you will learn how to:

· Locate public single-cell studies of interest to you using QIAGEN Omicsoft Single Cell Lands

· Study different cell types by dimension reduction plots (for example, t-SNE, UMAP)

· Investigate expression of genes of interest across different cell types (Violin plots, overlay expression on cluster)

· Identify key pathways and regulators from scRNA-seq data using QIAGEN IPA