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Bioinformatics Training and Education Program

Qiagen IPA Pathway Analysis Online Webinars and Training in March

These trainings are offered by Qiagen, not BTEP, and are listed here for your convenience. (Last updated Mar 9) Let’s edit this

  • Mar 8 @ 1 PM,  New user training: Large dataset analysis and knowledge base queries using QIAGEN Ingenuity Pathway Analysis (IPA)

Register here

Users will learn how to:
• Upload their dataset (RNA-seq, scRNA-seq, proteomics, metabolomics and more) and perform interactive core/pathway analysis in IPA
• Understand the different result types produced (pathways, key regulators, impact on biological functions/diseases and more)
• Compare different experimental conditions (treatments, timepoints, single-cell clusters, disease types and more) and identify similarities and contrasts
• Generate a network even without a dataset or experimental design for hypothesis generation

Offered on the 1st and 3rd Tuesdays of every month at 1:00 PM ET

  •  Mar 15 @ 1 PM, Long-read sequencing analysis in the QIAGEN CLC Genomics Workbench

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This tutorial is an introduction to working with the tools in the Long Read Support (beta) plugin. The Long Read Support (beta) plugin is a collection of tools developed for working with long, error-prone reads such as those produced by the single-molecule sequencing technologies of Pacific Biosciences or Oxford Nanopore Technologies.

Participants will take away how to:

• Download Plugin for Long read support
• Import data required for the analysis
• De novo assembly of a microbial sized genome using long, error-prone reads
• Improve a de novo assembly from long reads by polishing with short, high-quality reads
• Map long reads to a reference and visualizing an assembly
• Correct raw long reads for further analysis

  • Mar 22 @ 1 PM, QIAGEN IPA deep-dive and new features training (Americas)

Register here

As requested by many users, your QIAGEN Digital Insights team is excited to introduce QIAGEN Ingenuity Pathway Analysis (IPA) deep-dive trainings. In these three-hour training sessions, we will discuss the following topics:

Part 1: Deep dive into QIAGEN IPA core and comparison analyses

Part 2: Deeper dive into how to use QIAGEN IPA even without user data

Agenda: https://qiagen.showpad.com/share/a3C2w9D6U58SJdlTAKXDj

  • Mar 24 @ 11 AM, COSMIC: Combining expert-curation with scientific innovation in a gold-standard database for precision oncology

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Key to precision oncology is the development of expert databases that organize and standardize information on cancer-related genetic variants, as well as their associated diagnostic, prognostic, and therapeutic implications, in a way that is easily accessible to multiple users. COSMIC, the Catalogue of Somatic Mutations in Cancer, was established nearly 20 years ago, and has been a gold-standard resource for this dataever since. Today, COSMIC is used on a daily basis in research labs, cancer centers, biotech, and pharmaceutical companies, where it comes into play as one of the keytrusted sources to analyze genomic data.
In this webinar, Dr. Zbyslaw Sondka, COSMIC’s Senior Scientist, and Rebecca White, COSMIC’s Scientific Communications Manager, will walk you through 3 key-aspects of the industry leading somatic mutation database.
At the conclusion of this session, participants will be able to:
  • Apply the breadth and depth of COSMIC’s high-quality somatic mutation data to identify proteins, biological processes, and pathways driving disease, which can be used to design new therapeutic approaches that precisely target causes of the malignancy on a molecular level.
  • Use tools and resources within COSMIC to bring actionable meaning to genomic data, such as the identification of driver mutations, functional biological consequences, and clinically significant somatic variants, which can aid diagnostics and treatment decisions.
  • Explain how COSMIC’s expert curation process enables the accumulation and integration of data on rare cancers (over 1500 unique cancer types have been recorded to date), and how this data could enable the development of cross-cutting solutions based on molecular behaviors and genetic similarities between cancers rather than their origin-location.