Bioinformatics Training & Education Program

Welcome to Learning Unix on Biowulf. This course consists of four one-hour lessons that will run weekly on Tuesdays from 1 -2 PM starting May 16. Subsequent lessons will be held on May 23, May 30, and June 6. Registering for the first lesson will enroll you for all lessons, you do not need to register for each lesson separately. An optional help session will follow each lesson from 2 – 3 PM. Everyone will use a Biowulf Student Account for this course, you do not need to have your own Biowulf account. All lessons will be recorded and made available on the BTEP website.

In this course, participants will

• Learn to log onto Biowulf (lesson 1, May 16)
• Learn to navigate the folder and file (directory) structure on Biowulf (lesson 2, May 23)
• Learn to work with very large Next Generation Sequencing (NGS) files on a Unix system (lesson 3, May 30)
• Learn how to run interactive, swarm and batch jobs as well as work with bioinformatics modules on Biowulf (lesson 4, June 6)

Meeting information:

Meeting link:
https://cbiit.webex.com/cbiit/j.php?MTID=m6c624a110f8fbdb607345593cf9c624f
Meeting number:
2318 574 8744
Password:
bmV565kRGp*

Join by video system
Dial 23185748744@cbiit.webex.com
You can also dial 173.243.2.68 and enter your meeting number.
Join by phone
1-650-479-3207 Call-in number (US/Canada)
Access code: 2318 574 8744

Global call-in numbers:
https://cbiit.webex.com/webappng/sites/cbiit/meeting/info/81852c4726654806992d399ac523771d#

Join this introductory session to learn how to sign up and access complimentary SAS training resources available to NIH and HHS employees. Get pointers on how to navigate complimentary tutorials, programming courses, and eLearning. In this session, the trainer will demonstrate how to enroll in recommended SAS 9.4 trainings and courses.

CellTypist was first developed as a platform for exploring tissue adaptation of cell types using scRNA-seq semi-automatic annotations. Now it's an open source tool for automated cell type annotations as well as a working group in charge of curating models and ontologies.

This is the first class in the NIH Library Introduction to R Series. This class provides 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. The R class series is a comprehensive collection of training sessions offered by the NIH Library Data Services and Bioinformatics programs that is designed to teach non-programmers how to write modular code and to introduce best practices for using R for data analysis and data visualization. Each class uses both evidence-based best practices for programming and practical hands-on lessons.

By the end of this class, students should be able to: list reasons for using R; describe the purpose of the RStudio Script, Console, Environment, and Plots panes; describe the various methods for finding help on R and RStudio; organize files and directories for a set of analyses as an R Project; define the following terms as they relate to R: object, assign, comment, call, function, and arguments; and assign values to objects in R.

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

Welcome to Learning Unix on Biowulf. This course consists of four one-hour lessons that will run weekly on Tuesdays from 1 -2 PM starting May 16. Subsequent lessons will be held on May 23, May 30, and June 6. Registering for the first lesson will enroll you for all lessons, you do not need to register for each lesson separately. An optional help session will follow each lesson from 2 – 3 PM. Everyone will use a Biowulf Student Account for this course, you do not need to have your own Biowulf account. All lessons will be recorded and made available on the BTEP website.

In this course, participants will

• Learn to log onto Biowulf (lesson 1, May 16)
• Learn to navigate the folder and file (directory) structure on Biowulf (lesson 2, May 23)
• Learn to work with very large Next Generation Sequencing (NGS) files on a Unix system (lesson 3, May 30)
• Learn how to run interactive, swarm and batch jobs as well as work with bioinformatics modules on Biowulf (lesson 4, June 6)

Meeting information:

Meeting link:
https://cbiit.webex.com/cbiit/j.php?MTID=m6c624a110f8fbdb607345593cf9c624f

Meeting number:
2318 574 8744
Password:
bmV565kRGp*


Join by video system
Dial 23185748744@cbiit.webex.com
You can also dial 173.243.2.68 and enter your meeting number.

Join by phone
1-650-479-3207 Call-in number (US/Canada)
Access code: 2318 574 8744

Global call-in numbers:
https://cbiit.webex.com/webappng/sites/cbiit/meeting/info/81852c4726654806992d399ac523771d#

Dr. Maximilian Haeussler is the co-PI for the UCSC Genome Browser, an interactive website offering access to genome sequence data from a variety of vertebrate and invertebrate species and major model organisms, integrated with a large collection of aligned annotations. Dr. Melissa Cline is program manager of the UCSC BRCA Exchange, a project which aims to advance the understanding of the genetic basis of breast, ovarian, pancreatic, and other cancers by pooling data on BRCA1/2 genetic variants and corresponding clinical data from around the world. In this webinar, Drs. Haeussler and Cline will discuss these programs and data resources for clinical variant interpretation.

In this webinar, participants will learn how to tell a story with their data using notebook-style live scripts and how to integrate MATLAB with Python code. Attendees will also learn how to share code and take advantage of MATLAB community tools such as File Exchange and GitHub. Finally, the participants will find out how they can host MATLAB offerings at their High-Performance Computing Centers or a Science Gateway. This session is for beginners; no software installation required.

This one-hour session builds on the Introduction to R & RStudio class. The session begins by introducing and identifying different categories of data. Participants will examine data types, create vectors, and assign values to vectors. They will also learn how to import data into RStudio, and examine those data frames for further cleaning, analysis and visualization. Participants will learn the differences between numeric, character, and logical data and how to change data types in R. They will also be able to create subsets and export project data for future use.

Data Wrangling is another class in the NIH Library Introduction to R and RStudio Series. A basic understanding of using R and RStudio to manage data is expected. This one-hour class will introduce the R tidyverse package and how to use it to manipulate, analyze and export data. This class will explore options for using the tidyverse functions select, filter, pipes, mutate, head, is.na, and export. Learning these functions will enable users to have well formatted data frames for future clean and consistent analysis and visualizations.

This class focuses on using Git and GitHub, with RStudio.  Using integrated RStudio tools, learners will have a chance to experiment with this integration and understand its advantages for collaboration and version control. This intermediate-level class is designed to be relevant to participants from different disciplines. Some familiarity or experience in R and RStudio is recommended. Participants are encouraged to install R and RStudio before the class.  Participants will need to download the class data before the class.

Partek Flow is your start-to-finish solution for analyzing high dimensional multi-omics sequencing data. It is a point-and-click software and is suitable for those who wish to avoid the steep learning curve associated with analyzing sequencing data through command line and/or code. In this training session, you will learn to analyze bulk RNA sequencing data using Partek Flow. This class is not hands-on.

Meeting link: https://cbiit.webex.com/cbiit/j.php?MTID=m6da28111eefd3ab12d0d59477796d6bb

Meeting number: 2309 032 9788

Password: pxJpAyn7*49

Host key: 652701

Join by video system:
Dial 23090329788@cbiit.webex.com
You can also dial 173.243.2.68 and enter your meeting number.

Join by phone:
1-650-479-3207 Call-in number (US/Canada)br>Access code: 2309 032 9788
Access code: 2309 032 9788

Global call-in numbers

Generative modeling is an artificial intelligence (AI) technique that creates unique content (such as text, graphics, audio, and video) by first analyzing training examples. Generative AI includes ChatGPT, which generates text in a dialogue format, and DALL·E 2, which can create images based on natural language description. Generative AI is a rapidly expanding field that offers many possible applications for biomedical researchers and support staff. Join this roundtable discussion to learn about Generative AI and discuss possible applications and potential ethical concerns and issues with the use of Generative AI within scientific research and publishing.

This class is designed for those who want to learn the basic of R Markdown and apply those skills in Quarto. Quarto is an open-source scientific and technical publishing system that offers multilingual programming language support to create dynamic and static documents, books, presentations, blogs, and other online resources.  In this intermediate-level class participants will learn the basics of creating markdown documents. Some familiarity or experience in R and RStudio is recommended. Participants are encouraged to install R and RStudio before the class.

Data Wrangling is another class in the NIH Library Introduction to R and RStudio Series. A basic understanding of using R and RStudio to manage data is expected. This one-hour class will build on the introduction provided in Data Wrangling Part 1 to further explore the R tidyverse package and how to use it to manipulate, analyze and export data. This class will explore options for using the tidyverse functions group_by, summarize, count, arrange, pivot_wider, pivot_longer, and export. Learning these functions will enable users to have well formatted data frames for future clean and consistent analysis and visualizations.

In partnership with the NIH Clinical Center's Biostatistics and Clinical Epidemiology Service (BCES), the NIH Library is offering classes geared to cover general concepts behind statistics and epidemiology. This four-part lecture series will help participants better understand statistical and epidemiological features in biomedical research, interpret results and findings, design and prepare studies, and understand/critically review the results in published literature.

Part 1 will address fundamental statistical concepts including hypothesis testing, p-values and confidence intervals, types of data and their distributional importance, and bias and confounding. During the class, time will be devoted to questions from attendees and references will be provided for in-depth self-study.

Although you may attend any part of this series by itself, attending all four parts will provide a more comprehensive review of important statistical and epidemiological considerations that build on each other. You must register separately for each part of this class series.

This class is designed for those who want to extend the basics of R Markdown and apply those skills in Quarto. Quarto is an open-source scientific and technical publishing system that offers multilingual programming language support to create dynamic and static documents, books, presentations, blogs, and other online resources. In this intermediate-level class, participants will learn how to render documents in multiple format, and format citations and bibliographies using Zotero. Zotero is a free, easy-to-use tool to help collect, organize, annotate, cite, and share research. Some familiarity or experience in R and RStudio is recommended. Participants are encouraged to install R and RStudio before the class.

Scientists and educators from many different fields need to find and understand chemical data to perform their work. As such, understanding PubChem, the world’s largest collection of freely accessible chemical information, is a powerful skill for researchers, clinicians, and more. For educators, using PubChem in the classroom can facilitate active learning and exploration related to chemistry principles. In this workshop, participants will have access to NCBI experts and be introduced to the functionality of the PubChem Database.

In this online, interactive workshop, we will learn:

• Best practices of searching in PubChem
• Where to find molecular and chemical safety information
• How to use the PubChem Sketcher to find information about your chemical structure
• How to find a possible inhibitor for your gene

Note: This workshop is designed for life scientists, including educators and students, without exhaustive training in chemistry. Additionally, materials used for this workshop will remain available after the course for your use in research projects and curriculum development. More advanced PubChem workshops will be available in the future.

Due to curricular and technical limits, we’ve capped the number of spots to provide the best workshop experience. If you register to apply, you will be notified of your application status approximately 2 weeks before the scheduled event.

We recommend having access to a stable internet connection and modern web browser on a laptop or desktop computer to be able to successfully participate in the hands-on exercises.

Please see our FAQs page for more information and if you still have questions about the NCBI Outreach Events program or this specific workshop, email us at workshops@ncbi.nlm.nih.gov .

Galaxy is a scientific workflow, data integration, data analysis, and publishing platform that makes computational biology accessible to research scientists that do not have computer programming experience. This training will introduce ChIP sequencing data analysis followed by a tutorial showing ChIP-seq analysis workflow.  This workshop will be taught by NCI staff and is open to NIH and HHS staff.

This class is a mixture of lecture and hands-on exercises. By the end of this class, students will be able to: independently run basic ChIP-seq analysis for peak calling, run quality control on ChIP-seq data, map raw reads to a reference genome, generate alignment statistics and check mapping quality, call peaks using MACS, annotate peaks, and visualize the enriched regions.

MATLAB provides two-way integration with many programming languages such as Python, which allows for greater collaboration between investigators. This webinar will cover how to call MATLAB from Python and how to call Python libraries from MATLAB. Attendees will learn how to use MATLAB’s Python integration to improve the compatibility and usability of their code. This webinar will be helpful for participants who have collaborators using Python with MATLAB, or for attendees who want to integrate MATLAB’s capabilities in a Python program. This session is for beginners; no software installation required.

When it comes to data analysis and visualization, technical professionals who use Excel often encounter functional limitations. MATLAB supplements the capabilities of Excel by providing access to pre-built mathematical and analysis functions, visualization tools, and the ability to automate analysis workflows. Attendees will learn the main steps required for performing data analysis with MATLAB, including data access and pre-processing, modeling, and deployment. Attendees will gain an understanding of how to efficiently apply data analysis techniques using the MATLAB platform. This session is for beginners; no software installation required.