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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 March 5,2024)
  • Mar. 6 @ 1 PM, New user training: Large dataset analysis and knowledge base queries using QIAGEN Ingenuity Pathway Analysis (IPA)

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Join us for a 120-minute training session for new users of QIAGEN IPA. In this training, you’ll learn how to:
• Upload your 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, time points, 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.
 
For those with IPA license,
To install IPA before or after this training, please use below installer. https://qiagen.showpad.com/share/CBv30blCPKFDUYHRWtAvI
 
  • Mar. 7 @ 11 AM, Using COSMIC to predict, identify, and avoid mutational consequences of cancer therapies during early drug development and in patients

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Whether your lab is researching and developing targeted cancer therapies or you are analyzing and interpreting diagnostic tests at the point-of-care, a critical part of your workflow is understanding the structural and functional impact of cancer-related mutations. 

The Catalogue Of Somatic Mutations In Cancer (COSMIC) is an expert-curated database encompassing a wide variety of somatic mutation mechanisms causing human cancer. Containing more than 24 million somatic variants with detailed information on mutation distribution, effects, and signatures, COSMIC helps users better predict the cancer-driving effects of mutations and identify available drugs that target specific variants. COSMIC continues to expand its utility with continuous updates to its Mutational Signatures, the Cancer Mutation Census, and Mutation Actionability in Precision Oncology products.

To illustrate key applications of these features, this webinar will focus on how COSMIC can be used to avoid mutational consequences in cancer drug development and to profile the mutational signatures of cancer therapies in clinical samples.

Through these clinical and discovery use cases, attendees will learn:

  • How to evaluate genomic loci using the comprehensive coding and non-coding variant annotations within COSMIC
  • How to integrate these variants with curated findings and summaries of mutational impact and clinical actionability
  • How mutational signatures could be useful for clinical diagnosis and drug development applications now and in the future
Speakers:
 
Kyle Nilson, PhD
   Field Software Trainer, QIAGEN Digital Insights (QDI)
Kyle Nilson, Ph.D. 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 assits with software training, implementation, and optimization. He received his Ph.D. in molecular and cellular biology from the University of Iowa, studying the regulation of RNA polymerase II transcription and co-transcriptional mRNA processing. Dr. Nilson went on to complete his postdoctoral training at Penn State and Cornell University, where he focused exclusively on next-generation sequencing method development to study chromatin.
 
Steven Jupe, PhD
   Principal Curator for COSMIC Actionability, Wellcome Sanger Institute
Steve joined COSMIC as the Principal Curator for Actionability in 2018. His extensive career in biology and bioinformatics includes 7 years as a postdoctoral molecular biologist, 13 years in the bioinformatics group at GlaxoSmithKline (GSK), and 9 years curating biological pathways for the Reactome project at EMBL-EBI.
 
  • Mar. 14 @ 1 PM,  ATCC cell line data utilization for cell line selection, validation and other applications

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Cancer cell line models have been a cornerstone of cancer research for decades. Profiling cancer cell lines can be a powerful tool to identify gene alterations or cancer-related pathways and aid in discovering putative drug targets. In this webinar, we’ll use QIAGEN OmicSoft Lands and QIAGEN Ingenuity Pathway Analysis (IPA) to help you select cell lines and translate insights from your cell line experiments for drug target discovery.
 
During this 90-minute discussion, we’ll explore how you can use these software tools to:
• Select appropriate cancer cell lines for a variety of applications such as drug discovery, precision disease modeling, understanding gene function in cancer, immune-oncology research and more
• Examine various ‘omics data for genes of interest for expression, mutation, hotspots and gene dependency data
• Generate networks for hypotheses and test them in silico to improve the translation of insights derived from cell line models to the drug target identification
• Integrate analyses of public ‘omics data and drug response phenotypes using cell line model systems by exploring data from the Library of Integrated Network-Based Cellular Signatures (LINCS)
• Prioritize drug targets and profile phenotypic/downstream effects of drug action by overlaying public data on user-generated networks.
 
Our system uses millions of curated literature findings from QIAGEN Knowledge Base and the OmicSoft digital warehouse. This discussion is intended for both those familiar with QIAGEN IPA and newcomers interested in learning more.
 
  • Mar. 21 @ 11 AM,  Virtual Roundtable: Advances in Genomic Testing for Rare Disease Diagnostics: Detection, Interpretation, Access

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Over the past decade, whole-exome and whole-genome sequencing have transformed the diagnosis of patients with suspected rare genetic diseases. However, despite recent advancements, a large number of patients with rare genetic diseases remains undiagnosed for years because they have limited access to comprehensive genomic testing.

In this virtual roundtable of leading rare disease experts, panelists will discuss:

  • The state of clinical genomic testing at their institutions.
  • How recent advances in sequencing technology and data analysis, including artificial intelligence (AI), are increasing diagnostic rate.
  • How barriers to patient access to testing can be removed to improve the care of all people living with rare genetic diseases.
Speakers:
 
Danny E. Miller, MD, PhD
   Assistant Professor, Department of Pediatrics, Division of Genetic Medicine, University of Washington.
Danny Miller’s laboratory uses long-read DNA and RNA sequencing to identify missing disease-causing genetic changes that are difficult to detect using standard genetic testing, including those challenging to resolve with short-read sequencing and variants in regions of the genome that were inaccessible to prior technologies. His group is interested in developing long-read sequencing-based clinical tests to simplify clinical genetic testing, increase the diagnostic rate, and shorten the time required to arrive at a genetic diagnosis. Clinically, he is an attending physician in the Department of Pediatrics, Division of Genetic Medicine, and he sees patients in both general genetics and skeletal dysplasia clinics at Seattle Children’s Hospital.
 
Vaidehi Jobanputra, PhD, FACMG
   Associate Professor of Pathology and Cell Biology, Columbia University Medical Center.
Vaidehi Jobanputra is the chief diagnostics officer at the New York Genome Center and also holds an academic appointment as associate professor of pathology and cell biology at Columbia University Medical Center. She obtained a bachelor’s degree in biology from New Delhi University, a doctorate in genetics from the All India Institute of Medical Sciences, and a master’s in biostatistics from Columbia University. She was previously assistant medical director of the Clinical Cytogenetics Laboratory at New York Presbyterian Hospital and the Laboratory of Personalized Genomic Medicine in the Department of Pathology at Columbia University Medical Center.

At the NYGC, Jobanputra oversees all clinical testing at NYGC and leads a team of 16 individuals, including clinical technologists, bioinformatics scientists, and supporting staff. Jobanputra has been responsible for setting up the clinical laboratory, overseeing the validation and launch of the constitutional exome, genome, and targeted variant assays, as well as reference sequencing.She is also responsible for the validation and oversight of the oncology genome, exome, and transcriptome sequencing assays. Jobanputra’s research focuses on genomic and transcriptome studies of rare undiagnosed diseases and cancer.

Gilad D. Evrony, MD, PhD
   Assistant Professor, Departments of Pediatrics and Neuroscience and Physiology, NYU School of Medicine
Gilad Evrony is an assistant professor at NYU School of Medicine’s Center for Human Genetics and Genomics, and the Departments of Pediatrics and Neuroscience and Physiology. He received his undergraduate degree in brain and cognitive sciences from MIT and served in the Israel Defense Forces before receiving a medical degree and doctorate at Harvard Medical School. His graduate research in the lab of Chris Walsh at Boston Children’s Hospital and subsequent work developing new single-cell genomics technologies has been recognized by several awards, including the Eppendorf andScience MagazinePrize for Neurobiology and the MIT Technology Review Top Innovators Under 35 award. Evrony joined NYU after clinical training in pediatrics at Mount Sinai Hospital, where he co-founded an Undiagnosed Diseases Program that identified genetic diagnoses for children with severe illnesses that were unsolved despite extensive prior medical evaluations.
 
Malte Spielmann, MD, PhD
   Professor of Human Genetics, University Hospital Schleswig-Holstein, German
Malte Spielmann is a professor of human genetics and director of the Institute of Human Genetics at University Hospital Schleswig-Holstein. He studied medicine in Witten-Herdecke, Bochum, and Boston. Previously, he was a group leader at the Max-Planck-Institute for Molecular Genetics in Berlin, and before that, a group leader at the Institute for Medical Genetics and Human Genetics at Charité in Berlin. He also spent time at the University of Washington working with Jay Shendure. His research focuses on the role of noncoding mutations and structural variants in hereditary human disease. He is a human geneticist by training and holds a lead role in the nationwide implementation of high-throughput sequencing in clinical genetics in Germany.
  • Mar. 26 @ 11 AM,  Agilent Alissa to QCI Interpret: How can your lab reduce the stress and complexity of transitioning to a new clinical information platform?

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In 2023, Agilent announced the discontinuation of their Alissa Interpret clinical informatics platform by the end of 2024. As a result, many of their current customers need to transition to a new variant interpretation and reporting software within a tight timeframe. However, when evaluating new interpretation solutions, clinical labs must consider a variety of factors, including: 

  • Content quality for clinical reporting
  • Flexibility to adapt current workflows to a new platform 
  • Retaining historical content and comments 
  • Ease of personnel training

In this webinar, learn about QCI Interpret, a panel- and sequencer-agnostic clinical informatics platform for NGS variant interpretation and reporting of germline and somatic tests. Our experts will address the concerns of current Alissa users and discuss what sets QCI Interpret apart from other interpretation solutions. In addition, we will show you how seamless it is to transition your historical data and comments into QCI Interpret, as well as provide a live demonstration of the industry-leading and reliable software that has been used to analyze and interpret more than 3.5 million patient test cases worldwide.

Speakers:
 
Neha Jalan
   Professional Services Solution Manager, QIAGEN
Neha Jalan is a Professional Services Solutions Manager at QIAGEN Digital Insights in North America. Neha has spent over a decade working in genomics, bioinformatics and microbiology; while interacting with scientists and providing solutions for their research concerns. Prior to joining QIAGEN, Neha gained her experience at Eurofins Scientific and Altria. Dr. Jalan earned her Ph.D. In Microbiology and Cell Science from the University of Florida and MSc in Microbiology from University of Mumbai.
 
Bryony Brown
   Customer Solutions Manager, QIAGEN Digital Insights
Bryony Brown is a Customer Solutions Manager who has assisted with QIAGEN Clinical Insight products since 2021. After graduating from the University of Pittsburgh, Bryony focused on growing her lab experience and sales experience at Magee Women’s Research Institute and Thermo Fisher Scientific. Working within the clinical lab space for the past decade has given Bryony an extensive knowledge on the daily struggles for reference labs, hospitals, and any other labs tackling the need for quality and fast patient reporting.
  • Mar. 26 @ 1 PM, Single Cell RNA-Seq, Cell Hashing, and Spatial Transcriptomics

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A slide illustrating some of the many result types/graphics you will be able to generate after this training. https://qiagen.showpad.com/share/jYTCDPNfz1SdIMPQPSPYS

Description: 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. Specifically, 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.

o Dimension reduction (UMAP, t-SNE) plots o Differential expression table for clusters, cell types, or combination of both

o Heat map

o Dot plots

o 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.

  • Mar. 28 @ 1 PM, Multi-omics (metabolomics, proteomics, transcriptomics) analysis using QIAGEN Ingenuity Pathway Analysis

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This 90-minute training session is about how QIAGEN Ingenuity Pathway Analysis (IPA) allows visualization of molecular intricacy and variations at multiple levels such as transcriptome, proteome, and metabolome. Through a series of brief technical vignettes, it is demonstrated 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