tv.qiagenbioinformatics.com

This 90-minute training session will show you how QIAGEN Ingenuity Pathway Analysis (IPA) helps visualize molecular intricacies and variations at multiple levels, such as transcriptome, proteome and metabolome. Through a series of brief technical vignettes, we will demonstrate how to:

• - Generate associations among molecular signatures obtained via integrating multi-omics data

• - Extract mechanisms from multi-omics data for precision medicine

• - Disease stratification based on multi-omics profiles

• - Map disease networks among targets and indications

The early stages of drug development are inherently high-risk; molecule screening, target evaluation and lead refinement can take years and cost millions of dollars – often have little to show for the effort. Indication expansion and drug repurposing can open new avenues of possibility, after careful evaluation of the relationships between the drug, its targets and the new disease context. These connections can be uncovered by mining curated, causal knowledge graphs, which inform smarter target identification.

Learn how to evaluate targets and drugs in this oncology-focused webinar, which examines BRAF as a target in multiple myeloma. Also, we’ll evaluate different drugs in clinical trials with an analysis that covers the GOT-IT assessment blocks for drug evaluation. These blocks, developed by the GOT-IT (Guidelines On Target Assessment for Innovative Therapeutics) working group, are part of a target assessment framework that supports robust, reproducible data.

We’ll cover how to:

• - Apply the GOT-IT framework to target evaluation and indication expansion

• - Uncover causal relationships between existing drugs and new diseases with our curated knowledge graphs

• - Make informed decisions based on concrete data, including toxicity, adverse events and competing drugs in clinical trials

In this video, we demonstrate the import and association of metadata with sample files.

  https://resources.qiagenbioinformatics.com/manuals/clcgenomicsworkbench/current/index.php?manual=Metadata.html

In this video, we demonstrate how to view details of specific data points in plot views using the synchronized table view. See how you can easily access the list of genes that overlap in a Venn diagram for RNA-seq. This functionality is also available for other types of plots like track lists, expression browsers and volcano plots, to name a few.

Starting with CLC version 26, workflow control can be simplified using fork collections.

https://resources.qiagenbioinformatics.com/manuals/clcgenomicsworkbench/current/index.php?manual=Fork.html#SECTION001425230000000000000

In this 90-minute training using Inflammatory Bowel Disease (IBD) public data from NCBI GEO through Omicsoft DiseaseLand, attendees will learn how to:

In three separate 60-minute trainings, attendees will learn how to use basic expression analysis functionalities in QIAGEN OmicSoft OncoLand, DiseaseLand and OmicSoft Studio. QIAGEN OmicSoft Single Cell Land will also be discussed in OncoLand and DiseaseLand trainings, focusing on public single-cell data.

Day 2: Biomarker

Leverage

• Discover and validate biomarker

Single-cell gene expression analysis starting from either FASTQ or expression data is now supported by QIAGEN CLC Genomics Workbench Premium, the scalable cross-platform desktop software for NGS data analysis. In this webinar, we will re-analyze data from a study on transcriptional profiling of the mouse heart (Skelly et al., 2018), starting from FASTQ and ending with detecting sexually dimorphic genes within different cell types.

Reference: Skelly, Daniel A., et al. (2018) Single-cell transcriptional profiling reveals cellular diversity and intercommunication in the mouse heart. Cell reports 22.3: 600-610.

Topics covered: