tv.qiagenbioinformatics.com

Leveraging QIAGEN OmicSoft for scRNA-Seq in Pharma - Mike Dufault - Sanofi

Mon, 25 Aug 2025 10:47:26 GMT

Supporting Biomarker Discovery One Cell at a Time - Introduction to QIAGEN...

Mon, 25 Aug 2025 10:45:44 GMT

Single-cell gene expression analysis helps biologists and bioinformaticians reveal complex and rare cell populations, uncover regulatory relationships among genes and analyze and visualize gene expression differences among different cell types, or within a unique cell type. In this talk we will explore new tools for analyzing, interpreting and explore scRNA-seq data and the underlying biology. We will also show how to integrate ‘omics datasets from different platforms to gain insights into the biology and molecular drivers of specific cell populations.
Objectives:
How to analyze scRNA-seq data without a bioinformatician or learning code.
How to leverage automatic cell annotation to streamline your workflow.
How to quickly comb millions of cells to identify

Click here to learn more.

Public single cell RNA-seq data investigation using Omicsoft and Ingenuity...

Mon, 25 Aug 2025 10:42:08 GMT

Slides from this training:
https://qiagen.showpad.com/share/qm9IZA718x6x5h6pfsiTa

Single cell lands tutorials: https://omicsoftdocs.github.io/ArraySuiteDoc/tutorials/SingleCellLand/Gene_Views/

Single cell RNA-sequencing (scRNA-seq) has been widely used to investigate tissue heterogeneity, identify novel cell types, study pathogenic mechanisms, development of targeted therapy (including immunotherapy) and more. Accordingly tremendous amount of scRNA-seq data has been deposited to public domains like GEO.

In this training, attendees will learn how to

· Locate public single cell studies of their interest using Omicsoft Single Cell Lands

· Study different cell types by dimension reduction plots (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 Ingenuity Pathway Analysis

Investigating public scRNA data using OmicSoft and QIAGEN IPA

Mon, 25 Aug 2025 10:41:38 GMT

In this training, attendees will learn how to

· Locate public single cell studies of their interest using Omicsoft Single Cell Lands

· Study different cell types by dimension reduction plots (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 Ingenuity Pathway Analysis

Single cell RNA-seq – data upload & analysis in Ingenuity Pathway Analysis...

Tue, 02 Apr 2024 14:53:00 GMT

This training is generated based on feedback from recent “Single Cell RNA-Seq, Cell Hashing, and Spatial Transcriptomics” training. Some registrants requested below topics to be covered in more details.
• How to upload single cell RNA-seq data in IPA and start an analysis?
• How to do above if you don’t have CLC Genomics Workbench?
• How to do above if you do have CLC Genomics Workbench?
• Tips and tricks regarding single cell RNA-seq data in IPA
• Possibly other topics based on user feedback

Single Cell RNA-Seq, Cell Hashing, and Spatial Transcriptomics

Tue, 26 Mar 2024 14:46:00 GMT

In this training, you will learn how to analyze and interpret your own single cell RNA-seq data using QIAGEN CLC Genomics Workbench starting with either FASTQ or matrix files.

Using CLC Genomics Workbench, you will learn how to perform secondary analysis on your single cell RNA-seq data. Specifically, you will learn how to:
• Import your raw FASTQ or processed cell-matrix files.
• Use pre-configured but customizable pipelines/workflows for single cell RNA-seq data.
• Generate high resolution visuals and other files from your analysis for publications and biopharmaceutical discoveries.
o Dimension reduction (UMAP, t-SNE) plots
o Differential expression table for clusters, cell types, or combination of both
o Heat map
o Dot plots
o Violin plots
• Learn how to use “Create Cell Annotations from Hashtags” for cell hashing (i.e., CITE-seq).
• Dive into spatial transcriptomic analysis, the latest feature in the single cell RNA-seq module.

Public single-cell RNA-seq data investigation using QIAGEN OmicSoft and...

Tue, 27 Feb 2024 08:42:00 GMT

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

In this training, you will learn how to

· Locate public single-cell studies of interest 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 Ingenuity Pathway Analysis (IPA)

Exploring pan-cancer immunomodulators for biomarker discovery and validation...

Thu, 12 Oct 2023 18:00:00 GMT

Cancer outcome is influenced by both the tumor microenvironment and host immune response. Using QIAGEN OmicSoft Studio to access public data from The Cancer Genome Atlas (TCGA) and our human Single Cell Lands collection, you’ll learn how to:

• View host immune response clusters across TCGA samples
• Identify differentially expressed immunomodulators across sample groups
• Visualize single-cell dimension reduction maps and overlay expression data
• Identify potential biomarkers whose expression correlates or anti-correlates with targets genes
• Validate new biomarkers using custom queries and TCGA survival data

Part I: Single-cell RNA sequencing data analysis using QIAGEN CLC Genomics...

Mon, 21 Aug 2023 20:06:25 GMT

This two-part series will walk you through single-cell RNA sequencing (scRNA-seq) analysis starting with a matrix file or FASTQ files and ending with a deep understanding of key pathways, regulators and cell type signatures within your data.

This session is for part I of this training. In this session, you'll learn to use QIAGEN CLC Genomics Workbench to perform secondary analysis on your scRNA-seq data. Specifically, you will learn how to:
• Import your raw FASTQ or processed cell-matrix files
• Use pre-configured but customizable pipelines/workflows for scRNA-seq data
• Generate high-resolution visuals and other files from your analysis for publications and biopharmaceutical discoveries. These include:

o UMAP, t-SNE plots
o Differential expression table for clusters, cell types, or a combination of both
o Heat map
o Dot plots
o Violin plots

Part II of this training takes place on Wednesday, Aug. 16. It focuses on interpreting scRNA-seq data using QIAGEN Ingenuity Pathway Analysis (IPA) to understand key pathways, regulators and cell type signatures within your data. Click here to watch Part II: https://tv.qiagenbioinformatics.com/video/87882212/part-ii-single-cell-rna-sequencing

Part II: Single-cell RNA sequencing data interpretation using QIAGEN...

Mon, 21 Aug 2023 20:05:53 GMT

In this session, we'll explore how you can take your scRNA-seq differential expression results produced from QIAGEN CLC Genomics Workbench (or from another software/package) and upload them into QIAGEN Ingenuity Pathway Analysis (IPA) to uncover a deep understanding of the biology in your experiment by exploring enrichment and activity prediction for pathways, regulators and more.

Specifically, you'll learn how to:
• Import data using the QIAGEN IPA plugin from QIAGEN CLC or data generated from a different software/pipeline/package
• Explore canonical pathway enrichment and predicted activity for your comparisons
• Find key regulators that may be responsible for the biology in your experiment
• Compare multiple core analyses and see side-by-side results for various cell types, clusters and more
• Compare the expression patterns for pathways and regulators in your dataset with over 135,000 precomputed public analyses in IPA
• Compare your complete analysis signature with over 135,000 precomputed public analyses in IPA

Part I focuses on the secondary analysis of scRNA-seq data using QIAGEN CLC Genomics Workbench. You'll learn to explore differential expression, UMAP, dot plot and more. Click here to watch Part I: https://tv.qiagenbioinformatics.com/video/87882199/part-i-single-cell-rna-sequencing

Extracting novel hypotheses and insights from single cell data

Fri, 20 May 2022 15:37:45 GMT

Follow us on a journey of single cell data exploration. See how you can Process, Analyze, Compare, and Contextualize, your results to identify novel biological relationships and drive new hypotheses. In this presentation, Dr. Jean-Noel Billaud, PhD, will take you from data to biological insight using human single cell fetal liver data.

Participants will learn:
• Process: Which tools and workflows are best suited to process scRNA-seq data
• Analyze: How to analyze, highlight and identify cell types of interest
• Compare: How you can effortlessly compare and discover similar biology phenomena
• Contextualize: Provide context from other tissues and diseases to unlock hidden biology

Speaker:

Jean-Noel Billaud, PhD

Dr. Jean-Noel Billaud. Jean-Noël is a Senior Principal Scientist at QIAGEN Digital Insights. Before joining QIAGEN, he was part of Ingenuity Systems since 2008 as a staff scientist. Dr, Billaud holds a Ph.D. in Blood Cell Biology from Paris and did his post-doctoral work at the Scripps Research Institute (San Diego, CA). He previously worked at the Vaccine Research Institute of San Diego and co-developed a universal vaccine platform to target infectious disease, metabolic diseases, and cancer.

Single Cell ATAC sequence analysis

Mon, 25 Apr 2022 16:15:11 GMT

scATAC-seq (Single-Cell Assay for Transposase-Accessible Chromatin using sequencing) is a technique used in molecular biology to assess chromatin accessibility. Now with QIAGEN CLC Genomics Workbench Premium, we put the power of this growing technology at your fingertips.

In this webinar training, our QIAGEN Field Application Scientist will walk you through a typical scATAC-seq workflow. Topics covered will include:
• Read QC and deduplication
• Peak calling
• Finding nearby genes and transcription factor (TF) motif scans
• Automatically prediction of cell types and cluster
• Comprehensive QC report
• Various other visualization, such as UMAP plot, Dot plots, heat map, and Violin Plots