tv.qiagenbioinformatics.com

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

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

Have you ever tried to access the genomic profiles of cell lines before using them in your preclinical experiments just to come up empty-handed? Maybe you’ve scoured public databases for gene expression information on your cell line to find the reported genomic profile doesn't match the cell line data you recently purchased?

We understand that knowing the genomic identity of your cell lines is fundamental to the success of your preclinical experiments. Unfortunately, most publicly available sources have little or no cell line' omics data, leaving you to fend for yourself.

That's why we've teamed up with ATCC, the market leader in global biological materials and authenticated cell lines, to deliver you manually curated cell line ‘omics data from the most popular cell lines offered by ATCC. We've collected this data into ATCC Cell Line Land, our continually growing database of cell line 'omics data from both common and novel human and mouse cell lines, primary tissues and cells from ATCC. ATCC Cell Line Land gives you access to standardized, authenticated and reproducible cell line 'omics data characterizations which can be traced back to physical lots of cells in ATCC's biorepository.

Attend our joint webinar with ATCC to learn about and explore ATCC Cell Line Land, including:

The key limitations of public cell line data that drove its development

Who should attend? Biologists, preclinical researchers, bioinformaticians, data scientists

Click here to learn how.

In this 90-minute training, you’ll learn how to do drug treatment, toxicology and target safety assessment-related discoveries using QIAGEN Ingenuity Pathway Analysis (IPA) and QIAGEN Omicsoft Lands.

Using findings from peer-reviewed publications and other sources, attendees we’ll explore with you how to use QIAGEN IPA to:

In the rapidly evolving landscape of drug discovery, the ability to integrate high-quality research findings into knowledge graphs is paramount. For over twenty years, our scientists have curated the relationships between genes, drugs, diseases, and pathways to power Ingenuity Pathway Analysis. Now, these data are available via our QIAGEN Biomedical KB-HD, which provides direct access to flat files, SQL APIs in Python and R, and the ability to export knowledge graph objects for analysis in Neo4j.

In this talk, we will explore how to use this rich data resource to:

• Aggregate relevant findings across our comprehensive disease and gene ontologies

• Cross-reference clinical trial results to focus your research on genes upstream or downstream of known drug targets

• Filter causal relationships by the directionality of observed effects

• Combine the above methods to accelerate the drug discovery process

By demonstrating the underlying database live, we will show how the high-quality curated biomedical knowledge bases can be rapidly deployed, as well as how the underlying schema and ontologies could serve as a scaffold for integrating your own research. Overall, this demonstration will show the critical role of knowledge graphs in finding viable drug targets while avoiding potential adverse outcomes and toxicity.

Since the completion of the Human Genome Project over two decades ago, genomics has become progressively entrenched within the bedrock of the biomedical research enterprise. Capitalizing on the momentum of the project’s successful completion, the field of genomics has increasingly expanded and matured, such that genomics is now central and catalytic in basic and translational research, and studies now regularly demonstrate the vital role that genomic information can play in clinical care.

Looking ahead, the anticipated advances in technologies, biological insights, and clinical applications (among others) will lead to more widespread dissemination of genomics throughout biomedical research, a growing adoption of genomics into medical and public-health practices, and an increasing relevance of genomics in everyday life.

In this webinar, Eric Green, former director of the National Human Genome Research Institute at NIH, will discuss how the institute capitalizes on these opportunities by developing and leading initiatives that address the most pressing challenges at the forefront of genomics, with a particular emphasis on understanding the biological complexities of the human genome, on untangling the complex roles that genomic variants play in health and disease, and making genomics broadly and equitably integrated into medicine.

Speaker: Eric Green, MD, PhD

Former Director, National Human Genome Research Institute, National Institutes of Health

Eric Green is the former director of the National Human Genome Research Institute (NHGRI) at the National Institutes of Health (NIH). He was the third NHGRI director, having been appointed by NIH director Francis Collins in 2009.

Green was at NHGRI for more than 30 years, during which he held multiple key leadership roles prior to becoming the director. He served as the Institute’s scientific director for seven years, chief of the Genome Technology Branch for 13 years, and founding director of the NIH Intramural Sequencing Center for 12 years.

For just over two decades, Green directed an independent research program that included integral start-to-finish roles in the Human Genome Project and groundbreaking work on mapping, sequencing, and characterizing mammalian genomes.

Green earned his medical degree and doctorate in 1987 from Washington University in St. Louis — coincidentally, the word “genomics” was coined in that same year. Throughout his career, he has authored and co-authored more than 395 scientific publications. Green has earned multiple honors and awards, including election to the National Academy of Medicine in 2023.

Over two decades of research have uncovered over 100 genes with rare mutations linked to autism spectrum disorder (ASD), yet transcriptomic and epigenetic analyses reveal convergent dysregulation patterns in ASD brain tissue. In this webinar, learn how Dr. Dan Geschwind and his team at UCLA combine bioinformatics and experimental approaches to show that both common and rare genetic variations converge during early fetal cortical development. Using the largest hiPSC patient cohort and cortical organoid models, they identified shared transcriptional changes and created a resource of isogenic lines with over 100 ASD-associated mutations. Their integrative, network-based approach aims to clarify how genetic risk influences neurodevelopment through transcriptional regulation.

Speaker: Dan Geschwind, MD, PhD

Gordon and Virginia MacDonald Distinguished Professor of Neurology, Psychiatry and Human Genetics

Senior Associate Dean and Associate Vice Chancellor of Precision Health, Institute for Precision Health (IPH)

University of California Los Angeles (UCLA)

 IPA has broadly been adopted by the life science

Part 3: Search and Explore in IPA

Learn how IPA’s knowledge and discovery tools can accelerate

Interested in learning more or trying IPA? Click here.

Learn how to quickly and easily identify significant pathways, discover potential novel regulatory networks, and get the most out of your 'omics data!

IPA has broadly been adopted by the life science research

Part 1: Introduction to the IPA Core Analysis

Learn how to view and interpret Core Analysis results in IPA,

There is an almost incomprehensible amount of diverse, non-standardized ‘omics data deposited in different public sources such as GEO, SRA, TCGA, GTEx and others. Scientists who are interested in biomarker discovery and investigation using such data run into the challenge of finding time and resources to locate studies of their interest and then making it usable by cleaning and standardizing these data. Accordingly, this training is focused on how scientists facing the above challenges can use OmicSoft Lands which has manually curated, unified data which is flexibly accessed through both a web-based portal and APIs.

• Easily and effectively locate RNA and protein expression data of interest (specific diseases, drug treatments, tissues etc.) using the web-based portal as well as OmicSoft Lands APIs

• Conveniently generate charts comparing expression across different conditions of user interest (example disease vs normal, treated vs untreated, responders vs non responders and more)

• Export results in both tabular and graphical formats