Assessing drug safety with QIAGEN Biomedical KB-AI
2024-07-23 13:00 - 14:00 (America/Halifax) | HSMD-screen-grab-2
Are you a healthcare professional, clinical researcher or data scientist interested in drug safety research? If so, you know how vital understanding a drug’s adverse effects is to maximize its effect while minimizing its risks. This webinar will show how the QIAGEN Biomedical KB-AI knowledge graph can be used to explore scientific and pharmacovigilance data. Focusing on immune checkpoint inhibitors (ICIs), we will also demonstrate how Neo4j and Python can be combined to query, visualize and analyze this data effectively.
We’ll cover the following:

Drug safety profiling in Biomedical KB-AI
Pharmacovigilance case study of ICIs: Pembrolizumab
Comparative analysis of ICIs for comprehensive safety monitoring

Checkpoint inhibitor and immuno-oncology investigation through OmicSoft Lands APIs
2024-07-24 13:00 - 14:30 (America/Halifax) | Virtual - Americas - EST, United States
While there is great interest in the scientific community to investigate drug targets and biomarkers from public immune-oncology data, such investigation is hindered by the difficulty in finding and combining related datasets to perform large-scale meta-analyses. This webinar will focus on how high quality curated genomic repositories such as the QIAGEN OmicSoft Lands database immediately allows in-depth investigations across diverse data-sources (GEO, CPTAC, TCGA, GTEx and many more) to discover and validate candidate checkpoint inhibitor drug targets and biomarker investigation.
In this webinar you will learn how to

Easily identify relevant samples using extensive manually curated clinical metadata
Visualize and identify checkpoint inhibition biology related drug target and biomarkers expression patterns in bulk and single cell RNA-seq studies.
Reveal how the expression of a group of biomarkers (or genes/proteins of interest) correlates in normal and disease tissue

IPA deep dive: miRNA investigation using QIAGEN Ingenuity Pathway Analysis (IPA)
2024-07-24 13:00 - 14:30, 2024-08-27 13:00 - 14:30 (America/Halifax) | Virtual - Americas - EST, United States
In this 90-minute training session, you will learn how to identify target mRNAs for your miRNAs of interest and associate them with pathways, diseases, biological functions, tissues and cell types.
Topics that will be covered include:

How to analyze miRNA-seq datasets alone or both miRNA and corresponding mRNA datasets together
How to use QIAGEN IPA without a dataset, using miRNA IDs
Introduction to databases and curated content specific to miRNA
How to effectively apply various filters and functionalities to identify biomarkers, key targets and biological mechanisms

Learn more about IPA or request for a trial.

Checkpoint inhibitor and immuno-oncology investigation through OmicSoft Lands APIs
2024-07-24 13:00 - 14:30 (America/Halifax) | HSMD-screen-grab-2

Probing OncoLand using OmicSoft Studio
2024-07-30 13:00 - 14:00 (America/Halifax) | Virtual - Americas - EST, United States
There's more than one way to probe our OncoLand data. With the OmicSoft Studio graphical user interface (GUI), you won't need a script to fetch the data you want. This training will show how high-quality curated genomic repositories, such as the QIAGEN OmicSoft Lands, immediately allow in-depth investigations across diverse oncology and normal tissues/cells data sources (GEO, CPTAC, TCGA, GTEx and many more) to discover and validate candidate checkpoint inhibitor drug targets and biomarker investigation.
You will learn to generate data for questions such as:

How is a gene (or a set of genes) expressed across different conditions (e.g., diseases, treatments, cell types)?
How is the expression of a gene correlated with the expression of other genes?
For a list of genes, can we generate a heatmap studying their expression across different conditions?
How do you get a list of biomarkers specific to a condition from public studies?

Probing OncoLand using OmicSoft Studio
2024-07-30 13:00 - 14:00 (America/Halifax) | HSMD-screen-grab-2

Discovery from sample-level public data (GEO, SRA and more) using IPA Land Explorer
2024-08-01 13:00 - 14:00 (America/Halifax) | Virtual - Americas - EST, United States
Within QIAGEN Ingenuity Pathway Analysis (IPA), public data sourced from OmicSoft is already processed and standardized, making it easy to jump to the actual research. In this training, we'll show how to effectively use sample-level public data and metadata from sources like GEO, SRA, TCGA, GTEx, Blueprint, CCLE and other sources using the IPA Analysis Match and Land Explorer features. We will walk through various use cases, such as biomarker discovery, drug target investigation, studying survival in custom patient cohorts, multi-gene correlation and more.
You will learn to answer questions such as:

How is a gene of interest expressed across different conditions (e.g. diseases, treatments, cell lines)?
Is there correlation in the expression for two genes or biomarkers of user interest for a given condition?
For a given condition of interest, can we derive a list of genes (e.g., genes specific to a disease, treatment or cell type)?
Can we generate custom cohorts of patients (e.g., example TP53 wt vs mutant or PDCD1 high vs low expression) and then, generate survival curves representing those cohorts? Can we generate p-values to see if there is significant difference?
Can we detect expression of a gene in different cell types from single cell data?

Discovery from sample-level public data (GEO, SRA and more) using IPA Land Explorer
2024-08-01 13:00 - 14:00 (America/Halifax) | HSMD-screen-grab-2

QIAGEN Ingenuity Pathway Analysis (IPA) new user training
2024-08-06 13:00 - 15:00 (America/Halifax) | Virtual - Americas - EST, United States
Are you new to QIAGEN 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 how 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

Do you already have an IPA license? Install IPA and start using it now.
Don't have a license? Learn more about IPA or request a free trial.

Sharing your analysis results with others in Ingenuity Pathway Analysis
2024-08-08 13:00 - 14:00 (America/Halifax) | Virtual - Americas - EST, United States
QIAGEN’s Ingenuity Pathway Analysis (IPA) is a powerful tool that allows you to upload your omics data and analyze it to identify key biological pathways and mechanisms and regulatory molecules. But did you know you can share your analysis results with others? In this 60-minute webinar, we’ll explore the Share Manager and the Collaboration Workspace in IPA and go over the many ways you can share your analysis results with other or how they can share their results with you.
Attendees will learn how to:

Share datasets and analysis with other IPA users
Use the Share with me feature
Email interactive pathways to other IPA users
Use a Collaboration Workspace (CWS)

Sharing your analysis results with others in Ingenuity Pathway Analysis
2024-08-08 13:00 - 14:00 (America/Halifax) | HSMD-screen-grab-2

Drug MOA and disease pathology investigation using QIAGEN Biomedical KB-HD
2024-08-13 13:00 - 14:00 (America/Halifax) | Virtual - Americas - EST, United States
Many research groups worldwide are investing significant time and resources in studying drug mechanism of action (MOA) and its impact on disease pathology. One critical challenge they encounter is access to a centralized source that contains high-quality, manually curated literature knowledge. To meet this need, we launched QIAGEN Biomedical KB-HD, the expert-curated database backing QIAGEN Ingenuity Pathway Analysis (IPA), to enable the scientific community and help accelerate drug discovery.
You will learn to use Biomedical KB-HD to:

Easily pull up relevant literature findings for a drug of interest
Generate a novel mechanism of action (MOA) for this drug and its effect on the disease indication of interest
Identify new applications for this drug (drug repurposing)
Investigate mutational impact on drug MOA

Leveraging high-quality public proteomics data for biomarker and drug-target investigation through OmicSoft Lands APIs
2024-08-15 13:00 - 14:00 (America/Halifax) | Virtual - Americas - EST, United States
Per feedback from recent trainings, we are hosting a training focused on biomarkers and drug target investigation through effectively utilizing high quality curated public proteomics expression data. OmicSoft Lands database is a high-quality curated repository which contains gene and protein expression data derived from a variety of sources such as CPTAC, TCGA, HPA, GTEx and more.
Using OmicSoft Lands APIs, you will learn how to:

Easily locate proteomics samples and projects (studies) of interest (example can we locate proteomics data related to the breast cancer or specific drug treatment?)
Check expression of a protein of interest (drug target or biomarkers) across different experimental groups or conditions (diseases, treatments, cell types and more) as well as across samples coming from different collections (example is a protein upregulated in breast cancer samples from TCGA and CPTAC but downregulated in normal samples from TCGA, GTEx and HPA?)
Correlate protein levels with RNA-seq expression data for the same samples, and compare differential expression results from proteomic and RNA-seq results
Investigate whether there is correlation in expression between two (or a group/list of proteins) across different experimental groups/conditions (example do two proteins of interest show correlation in expression in TNBC samples? Is protein and gene expression correlated as well?)
Derive a protein signature from conditions of interest (example are a group of protein upregulated in disease condition but downregulated upon drug treatment)
Perform Geneset Enrichment for a group of proteins

Leveraging high-quality public proteomics data for biomarker and drug-target investigation through OmicSoft Lands APIs
2024-08-15 13:00 - 14:00 (America/Halifax) | HSMD-screen-grab-2

Single Cell RNA-Seq, Cell Hashing, and Spatial Transcriptomics
2024-08-20 13:00 - 15:00 (America/Halifax) | Virtual - Americas - EST, United States
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.
See some of the many results/graphics you will be able to generate after this training.
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, including dimension reduction (UMAP, t-SNE) plots, differential expression table for clusters, cell types, or combination of both, heat maps, dot plots, 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.

Link prediction for biomedical innovation and drug discovery
2024-08-21 10:00 - 11:00 (America/Halifax) | Virtual - Americas - EST, United States
Are you interested in biomedical knowledge graphs, but don’t know where to start? This webinar will show you how to repurpose drugs and uncover hidden insights with knowledge graphs. Start learning the fundamentals of training embeddings and how to predict links in knowledge graphs. You’ll be able to apply that knowledge towards your biomedical discoveries with advanced machine learning techniques.
In this webinar, you will:

Meet QIAGEN Biomedical KB-HD, the manually curated knowledge base of over 24 million relationships that powers QIAGEN Ingenuity Pathway Analysis
Learn about methods for graph link prediction
Start applying link prediction to graph embeddings with PyKEEN
See the results of applying link prediction towards indication expansion for a TLR7 inhibitor

OmicSoft Studio: RNA-seq and expression data analysis
2024-08-22 13:00 - 14:30 (America/Halifax) | Virtual - Americas - EST, United States
In this 90-minute training, attendees will learn how to use basic expression analysis (example RNA-seq) functionalities in QIAGEN OmicSoft Studio and how that integrates with OncoLand, DiseaseLand and Single Cell Land. This webinar will focus on expression data analysis using QIAGEN OmicSoft Studio’s powerful analysis and visualization capabilities to explore your ‘omics data:

Accepted data formats (ex. fastq files, cell matrix files with raw or normalized counts, etc.)
Easily generating and flexibly customizing downstream outputs such as differential expression, heatmaps, counts, PCA/PCOA, etc.
Exporting high-resolution graphics as well as raw or filtered tables

To get most out of this training, please consider reviewing the below ahead of time (not a requirement to attend the training though).

Step-by-step local analysis
Step-by-step server analysis

Public single-cell expression data made easy with QIAGEN IPA
2024-08-29 13:00 - 14:00 (America/Halifax) | Virtual - Americas - EST, United States
Many QIAGEN Ingenuity Pathway Analysis (IPA) users have expressed interest in taking advantage of public single-cell expression data. Such data is readily available and easily accessible in IPA. We are hosting a 1hr training focused on some common use cases related to this topic.
You'll learn to:

Easily locate single-cell studies, samples or cell types of interest
Study pathways and networks pertaining to such projects to explore biological and cellular mechanisms
Investigate sample- and cell-level gene expression for biomarker investigation

Achieving Good Manufacturing Production (GxP) compliance with NGS (EMEA)
2024-09-04 10:00 - 10:30 (Europe/Helsinki) | Virtual - EMEA - CET
New guidelines for the viral safety evaluation of biotechnology products from the International Council for Harmonisation (ICH) recommend replacing multiple in vivo and in vitro assays with next-generation sequencing (NGS) to maintain good manufacturing practices.
If that sounds like a lot, we’ve got you covered. In this webinar, we’ll explore how you can easily apply NGS analysis to GxP with the QIAGEN CLC Genomics platform. Make compliance intrinsic to your workflow and ensure product quality, data integrity and patient safety.
You’ll learn how to:

Assess biosafety, ensure integrity and perform quality control in the biotech industry with NGS
Implement and maintain GxP with the QIAGEN CLC Genomics platform
Add your existing applications and extend their use through the CLC interface

Achieving Good Manufacturing Production (GxP) compliance with NGS (Americas)
2024-09-04 13:00 - 13:30 (America/Halifax) | Virtual - Americas - EST, United States

QIAGEN IPA new user training
2024-09-04 13:00 - 15:00, 2024-10-03 13:00 - 15:00 (America/Halifax) | Virtual - Americas - EST, United States
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.
Learn more about IPA or request a free trial.

Custom patient cohorts: Making discoveries with curated genomics data
2024-09-05 13:00 - 14:00 (America/Halifax) | Virtual - Americas - EST, United States
Are you interested in exploring how you can evaluate phenotypic differences between custom cohorts? You can learn more about drug response, survival, co-expressing biomarkers, mutations and more based on gene expression.
In this webinar, you'll learn how to investigate patient cohorts using high-quality curated genomic repositories like the QIAGEN OmicSoft Lands database. You'll be able to to perform in-depth investigations across diverse data-sources, including GEO datasets, TCGA and more.
In this webinar, attendees will learn how to

Easily locate studies of interest using OmicSoft Lands APIs
Generate custom cohorts based on expression levels of biomarker(s) of interest
Thoroughly investigate drug response and patient survival for these custom cohorts
Study variants/mutations present in these patient population and their association with disease pathology

QIAGEN presents poster at 2024 European Congress of Pathology
2024-09-07 08:00 - 2024-09-11 17:00 (Europe/Helsinki) | Florence, Italy
QIAGEN will be at the 36th European Congress of Pathology (ECP) in Florence from September 7-11, 2024, in Florence, Italy.
At the event, be sure to check out our poster that we are presenting in collaboration with a leading pharmaceutical company showing how our clinical decision support software, QCI Interpret, provides rapid and accurate interpretation of gBRCA genes in a clinical lab setting. In the study, 10 partner labs were asked to assess 48 retrospective analyses of BRCA variants and compare their variant classifications with the automated classifications computed by QCI Interpret. Results showed QCI Interpret was concordant with 93% of all cases.

Featured Poster: Spadolini Pavilion (Upper Floor)
Molecular Pathology Session | September, 10, 2024, 9:30–10:30 a.m.
Poster number: 009. Title: “QIAGEN clinical decision support software provides rapid and accurate interpretation of gBRCA variants in a clinical lab setting”

Metatranscriptome analysis, annotation and pathways investigations using CLC Genomics Workbench
2024-09-10 13:00 - 14:30 (America/Halifax) | Virtual - Americas - EST, United States
Using CLC Genomics Workbench, we will go through a pipeline for analyzing metatranscriptome NGS data from microbial communities and perform pathways interpretation on it.

Import "raw" NGS sequencing data and prepare the samples for analysis
Find relevant annotated genomes with a curated reference database while removing ribosomal RNA with the SILVA database (database of rRNAs)
De novo assemble the unclassified reads into contigs to also find transcripts of taxa not present in the reference database
Map the reads to the assembled contigs and database · Build a functional profile of the samples to get an abundance of GO-terms.
Statistical analysis of the groups
Pathway analysis on the differential abundance analysis using MetaCyc database.

Expanding neoantigen discovery with COSMIC
2024-09-12 11:00 - 12:00 UTC | Virtual - Americas - EST, United States
Neoantigens are among the newest promising targets for cancer treatment. Unlike tumor-associated antigens, neoantigens are produced only by tumor cells. These unique molecular markers are highly visible to the immune system, making them ideal for personalized immunotherapies. They may also be able to predict both tumor survival prognosis and immune checkpoint blockade responses. Neoantigens are presented by human leukocyte antigen class I molecules (HLA-I) to T cells, providing an ideal pathway for detection by shotgun proteomics. To identify these elusive targets, scientists often rely on whole exome sequencing (WES)-derived data. However, this approach can miss rare or low-frequency mutations, especially in cancers with a low tumor mutational burden (TMB).
The Catalogue of Somatic Mutations in Cancer (COSMIC) can bridge this gap by providing researchers with detailed information about somatic mutations in human cancer. Unlock the full potential of neoantigen-targeted therapies and enhance traditional approaches like WES with our comprehensive, expert-curated knowledge base.
In this webinar, we’ll learn to:

Uncover and validate potential neoantigens with a recent peer-reviewed study that uses COSMIC mutation data from human hepatocellular carcinoma (HCC), a low-TMB cancer
Apply the benchmarking results of neoantigen detection performance using HCC-specific variants from COSMIC or DepMap
Take full advantage of the breadth and accuracy of COSMIC data with downloaded content and other resources

COSMIC’s scientific and curation team will also answer your questions live during the webinar.

Speaker: Kyle Nilson, PhD
Kyle Nilson, PhD, is a sequencing-focused molecular biologist with a background in biochemistry and technical support. As a field software trainer at QIAGEN Digital Insights, Dr. Nilson works closely with QIAGEN’s global bioinformatics team to provide direct customer support and assist with software training, implementation, and optimization. He earned his Ph.D. in molecular and cellular biology from the University of Iowa, where he studied the regulation of RNA polymerase II transcription and co-transcriptional mRNA processing. Dr. Nilson then completed his postdoctoral training at Penn State and Cornell University, focusing exclusively on next-generation sequencing method development to study chromatin.

OmicSoft Diseaseland Training
2024-09-17 13:00 - 14:30 (America/Halifax) | Virtual - Americas - EST, United States
Per feedback of scientists interested in taking advantage of non-oncological diseases (inflammatory, infectious, metabolic and more) as well as normal tissues (example toxicology/target safety assessment) omics, we are hosting this training focused OmicSoft Diseaseland. OmicSoft Diseaseland is a repository which contain high quality curated ‘omic data (RNA-seq, scRNA-seq, microarray and more) from diverse data-sources (example GEO, SRA, GTEx and many more). While this training will be focused on leveraging public data, users can use this knowledge to navigate through their institution’s internal lands (omic data repositories) as well.
Attendees will learn to perform queries similar to below

How is a gene (or a set of genes) expressed across different conditions? (Conditions = diseases, tissues, treatments, cell types and more)
How is expression of a gene correlated with expression of other genes?
For a list of genes can we generate a heatmap studying their expression across different conditions?
How do you get a list of biomarkers specific to a condition from public studies?

Third Annual Clinical Hereditary Disease Diagnostics Summit "Exome experts: Improving the interpretation and integration of exome testing in routine clinical care"
2024-09-26 11:00 - 12:30 UTC | Virtual - Americas - EST, United States
Industry leaders discuss how to improve the speed, precision and cost-effectiveness of clinical exome testing for newborn screening and rare and undiagnosed diseases
Clinical exome testing is revolutionizing the diagnosis of rare and inherited diseases. Its ability to quickly pinpoint the genetic causes of complex conditions has made it a critical component of personalized medicine, leading to earlier diagnoses, targeted treatments and improved patient outcomes. However, without the right strategies, databases and informatics tools, clinical exome testing remains inaccessible for many small to mid-sized laboratories.
The Third Annual Clinical Hereditary Disease Diagnostics Summit hosted by QIAGEN Digital Insights will examine the incredible opportunities—and challenges—of brining clinical exome testing in-house. Join industry leaders as they discuss how labs, regardless of size, budget and experience, can integrate exome testing into routine clinical care with transformative impact for providers and their patients.
Featured topics will include:

Emerging trends and recent technological advancements in genetic testing
Overcoming challenges of interpreting complex genetic data from genome, exome, and next-generation sequencing panels
How to integrate genetic testing into clinical practice with consideration of efficiency, cost, and ethics
Future directions for the field and how to prepare your lab for innovation

Investigating biomarkers with bulk and single-cell RNA-seq expression data
2024-09-26 13:00 - 14:30 (America/Halifax) | Virtual - Americas - EST, United States
QIAGEN Ingenuity Pathway Analysis (IPA) is designed to help you analyze and compare different types of 'omics data. In this webinar, we’ll compare bulk RNA-seq and single-cell RNA-seq data to identify common regulators/targets and see how those regulators/targets associate with your phenotype of interest. We will also use sample-level public data to validate gene expression of common genes in tissues and/or cell type of interest.
You'll learn how to:

Generate a Comparison Analysis for bulk and single-cell RNA-seq
Identify significant common genes with the Compare feature
Build a custom network associating common genes to a phenotype
Examine sample- and cell-level expression in OmicSoft content
