tv.qiagenbioinformatics.com

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 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 above challenges can use OmicSoft Lands which has manually curated, unified data which is flexibly accessed through both graphical user interface and APIs.

• Easily and effectively locate RNA and protein expression data of interest (specific diseases, drug treatments, tissues etc.) using graphical user interface 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) and customize them

• Export results in both tabular and graphical formats

In an era of near-limitless public experimental data but little standardization, meaningful insights are lost to noise. Large collections of quality experimental data are essential for big-picture discoveries that stand up to scrutiny.

In this webinar, you will learn how to feed your drug discovery programs by integrating connections mined from QIAGEN Biomedical Knowledge Base with deeply-curated disease datasets from QIAGEN OmicSoft Lands.

Combining unified 'omics datasets with contextual relationship evidence from our knowledge graph, we will address complex questions such as:

• Which genes aren't expressed in normal tissue, yet are expressed in diseases of interest, based on experimental evidence?

• Which of these proteins are cell surface proteins, with evidence for extracellular localization?

• How are these proteins related directly or indirectly to disease pathways, and can these be connected to known drug targets?

• Can we identify correlated biomarkers, mutation targets, clinical factors or other means of cohort selection?

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

When the Precision Medicine Initiative was launched in 2015, it completely transformed patient care in oncology. Now, individual differences in genetics, environment and lifestyle, along with the tumor’s genetic makeup, are accounted for when determining the best course of treatment for a patient. But, as with any great methodology shift, several challenges impede its widespread implementation. From cancer complexities such as tumor heterogeneity to bottlenecks in next-generation sequencing (NGS) data analysis and interpretation, high-quality and reliable systems are essential for a clinical lab to apply precision medicine effectively.

In this webinar, discover how trusted data curated by highly experienced variant experts can elevate your lab’s clinical NGS testing pipeline. Get acquainted with COSMIC (Catalogue Of Somatic Mutations In Cancer) and HSMD (Human Somatic Mutation Database), their content and ways you can navigate them to retrieve various information.

Specifically, you will:

• Do a digital walkthrough of COSMIC’s and HSMD’s user interfaces

• Explore the available content, including curated literature, annotations (CADD, PhyloP and more) and data from other resources, such as ClinVar and dbSNP

• Examine use cases such as Chernobyl radiation and papillary thyroid cancer

Now you can access and share the interpretative power of IPA in an easy-to-consume format – without installing any extra software.

IPA Interpret identifies and summarizes the biological themes in your results with the help of AI, creating a shareable, interactive report.

To learn more, visit https://digitalinsights.qiagen.com/products-overview/discovery-insights-portfolio/analysis-and-visualization/qiagen-ipa/qiagen-ipa-interpret/

Now you can access and share the interpretative power of IPA in an easy-to-consume format – without installing any extra software.

IPA Interpret identifies and summarizes the biological themes in your results with the help of AI, creating a shareable, interactive report.

To learn more, visit https://digitalinsights.qiagen.com/products-overview/discovery-insights-portfolio/analysis-and-visualization/qiagen-ipa/qiagen-ipa-interpret/