Classes & Events

This three hour online training will focus on getting started on using QIAGEN’s Ingenuity Pathway Analysis (IPA). IPA enables you to quickly identify biological relationships, mechanisms, pathways, functions and diseases most relevant to experimental datasets. The training will demonstrate how to explore IPA's knowledge & discovery tools to relate the most recent literature findings to your research. 

By the end of this training, attendees will be able to:

• Demonstrate how to access IPA from the NIH Library
• Upload multiple dataset types and perform interactive core/pathway analysis in IPA
• Interpret different results, including pathways, key regulators, impact on biological functions/diseases and more
• Compare different experimental conditions and identify similarities and contrasts
• Generate a network for hypothesis generation, even without a dataset or experimental design
• Leverage Public Data to identify key regulators across datasets (ex. tissues, diseases, cell types, etc.)

Registrants will receive an email with information and instructions to install IPA before the training. If you register the day before the training, you may not have time to download and properly install IPA. If you do not have the software installed, this training will be demo only

This one-hour online training will cover a basic overview of the functionality of R programming language and RStudio. R is a programming language and open-source environment for statistical computing and graphics.  

By the end of this training, attendees will be able to:  

• Describe the purpose of R and RStudio 

• Organize files and directories for a set of analyses as an R Project 

• Define key terms as they relate to R: object, assign, comment, call, function, and arguments 

• Find help and learning resources related to R and RStudio 

Attendees are not expected to have any prior knowledge of R/RStudio to be successful in this training. 

Students are encouraged to install R and RStudio before the class so that they can follow along with the instructor. 

This one-hour online training will cover the fundamentals, applications, and ethical considerations of Artificial Intelligence (AI). Attendees will explore key topics such as machine learning, deep learning, data handling, and real-world AI applications across various industries. The session will also delve into the ethical implications of AI and provide insights on becoming AI literate. Whether you're a seasoned professional or just starting your AI journey, this session will equip you with essential knowledge to navigate the AI landscape effectively and make informed decisions in our data-driven world.

By the end of this training, attendees will be able to: 
• Understand the core concepts of AI 
• Recognize the significance of ethical considerations in AI 
• Begin the journey toward AI literacy

Attendees are not expected to have any prior knowledge of AI to be successful in this training. 

This two-hour online workshop will focus on data wrangling using tidy data principles. Tidy data describes a standard way of storing data that facilitates analysis and visualization within the tidyverse ecosystem. There will be a discussion of what makes data "tidy," and methods for reshaping your data using dplyr and tidyr functions. 

By the end of this training, attendees will be able to demonstrate how to:

• Describe the purpose of the dplyr and tidyr packages
• Select certain columns and rows in a data frame
• Add new columns to a data frame that are functions of existing columns
• Use the split-apply-combine concept for data analysis

Prior to attending this training, you will need to have:

1. Installed R and RStudio
2. Taken the Introduction to R and RStudio training. If not, here are some resources for getting started:
   • Intro to RStudio Projects: Reproducibility
   • Intro to RStudio Projects: Creating a Project
   • Intro to RStudio Projects: Organizing Projects

Registrants will receive an email with information and instructions to install and verify access to R, RStudio and required packages before the class. If you register the day before the class, you may not have time to download and properly install the necessary software. If you do not have the software installed, this training will be demo only.

The "Data Visualization in R" series focuses on using ggplot and the broader tidyverse ecosystem to create insightful and customizable visualizations. It covers key principles of data visualization, from basic plots to advanced techniques, emphasizing the flexibility and power of ggplot within a tidy data workflow. By the end of the series, participants will be proficient in building plots using the tidyverse ecosystem.

This hour and half online training will explore the topics of perception and cognition, and how these apply to data visualization. This training will also teach you how to visualize your data using ggplot2. We will start by creating a simple scatterplot and use that to introduce aesthetic mappings and geometric objects, the fundamental building blocks of ggplot2. You must have taken Introduction to R and RStudio training to be successful in this training.

By the end of this training, participants should be able to:

1. Describe how perception and cognition inform visualizations
2. Discuss the visual properties that “pop-out," and how these inform visualizations
3. Distinguish between aesthetic mappings and geometric objects, the fundamental building blocks of ggplot
4. Create a simple scatterplot
5. Create a plot and save it in a high-resolution format

Attendees are expected to have a basic understanding of R and RStudio. In order to proceed, attendees should have done the following:  

1. Installed R and RStudio 
2. Taken Introduction to R and RStudio training. If not, here are some resources for getting started: 
   • Intro to RStudio Projects: Reproducibility
   • Intro to RStudio Projects: Creating a Project
   • Intro to RStudio Projects: Organizing Projects

You can register for the trainings in this series via the link below: 

• Data Visualization in R:  introduction to ggplot Part 1 of 2
• Data Visualization in R: Customizations Part 2 of 2

This three hour online training covers QIAGEN’s CLC Genomics Workbench enables researchers to analyze NGS data without the use of command line and is a powerful tool for determining differential expression. In this workshop students will explore the usage of CLC Genomics Workbench for taking raw NGS data and performing QC, processing, statistical analyses, and visualizations. The training will focus on the identifying differentially expressed genes from RNA-seq and how those results can be passed to Ingenuity Pathway Analysis (IPA) for biological interpretation. 

By the end of this training, attendees will be able to: 

• Import FASTQ files and metadata 
• how to download references
• Map reads to a reference genome and generate gene and transcript counts and QC reports displaying % mapped reads, knee plots, etc.
• Generate visualizations of results, such as heatmaps, differential expression tables, PCA/PCOA plots, Venn diagrams and others
• Easily customize RNA-seq workflows
• Export publication-quality graphics, tables and report
• Send differential expression tables to QIAGEN Ingenuity Pathway Analysis directly from QIAGEN CLC Genomics Workbench to analyze and interpret relevant pathways

Registrants will receive an email with information and instructions to install CLC Genomics before the training. If you register the day before the training, you may not have time to download and properly install CLC Genomics. If you do not have the software installed, this training will be demo only.

AI in Medicine: Focus on Deep Learning in Medical Genomics

This series invites Principal Investigators, Senior Scientists, and Senior Clinicians  to share cutting-edge research and developments in their fields. Each session includes a 20-30 minute presentation followed by a Q&A or journal club discussion, fostering deeper insights and scholarly exchange. Pizza is provided on a first come first served basis. 

AI is already dramatically changing biomedical research and the practice of medicine. Using the field of medical genomics as an example, this talk will (relatively informally) describe how deep learning, a particularly powerful type of AI, is used and studied.

The "Data Visualization in R" series focuses on using ggplot and the broader tidyverse ecosystem to create insightful and customizable visualizations. It covers key principles of data visualization, from basic plots to advanced techniques, emphasizing the flexibility and power of ggplot within a tidy data workflow. By the end of the series, participants will be proficient in building plots using the tidyverse ecosystem.

This one hour and half online training builds on the topics covered in the Data Visualization in ggplot training. It provides an overview of options for working with dates, times, and options for customizing a ggplot graph.  You must have taken Data Visualization in R: Introduction to ggplot: Part 1 of 2 training to be successful in this training. 

By the end of this training, attendees should be able to: 

• Create a scatterplot in ggplot
• Learn how to facet a plot
• Demonstrate options for customizing the title and axis
• Apply different ggplot themes

Attendees are expected to have a basic understanding of R and RStudio. In order to proceed, attendees should have the done following:  

1. Installed R and RStudio 
2. Taken Introduction to R and RStudio training. If not, here are some resources for getting started: 
   • Intro to RStudio Projects: Reproducibility
   • Intro to RStudio Projects: Creating a Project
   • Intro to RStudio Projects: Organizing Projects

You can register for the training in this series via the link below: 

• Data Visualization in R:  introduction to ggplot Part 1 of 2
• Data Visualization in R: Customizations Part 2 of 2

Registrants will receive an email with information and instructions to install and verify access to R, RStudio and required packages before the training. If you register the day before the training, you may not have time to download and properly install the necessary software. If you do not have the software installed, this training will be demo only.

This one hour and half hour online training will equip participants with essential knowledge and skills for effective interactions with Large Language Models (LLMs), such as ChatGPT. Explore the intricacies of prompt engineering and its pivotal role in optimizing the conversational capabilities of LLMs. Emphasizing best practices and practical applications, this training features live demonstrations and group discussion, and provides valuable skills for the effective use of LLMs. 

By the end of this training, attendees will be able to:  

• Define LLMs, prompt patterns, and prompt engineering 

• Identify potential uses and issues to consider when using LLMs in the biomedical research field 

• Use a selection of prompt patterns to improve generated output from LLMs 

• Identify resources for learning more about prompt engineering in LLMs 

Attendees are not expected to have any prior knowledge of ChatGPT to be successful in this training.