Bioinformatics Training & Education Program

In partnership with the NIH Clinical Center's Biostatistics and Clinical Epidemiology Service (BCES), the NIH Library is offering a several trainings that cover general concepts behind statistics and epidemiology. These trainings will help participants better understand and prepare data, interpret results and findings, design and prepare studies, and understand the results in published literature. 

This six-hour online training will describe the basic concepts for using common statistical tests such as Chi-square, paired and two-sample t-tests, ANOVA, correlations, simple and multiple regression, logistic regression, and survival analysis. Time will be devoted to questions from attendees and references will be provided for in-depth self-study. 

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

• Explain the importance of study design and hypothesis 

• Describe types of data and their distributions 

• List common statistical tests, regression methods, and nonparametric tests used 

• Select the right tests and methods based on study needs 

The first part of the class will be 10:00 a.m. to 12:00 p.m. EST followed by a break from 12:00-1:00 p.m. The class resumes at 1:00 p.m. and concludes at 5:00 p.m. 

Skylar Chan and Nikhil Mattu will present on the FDA recently approved 'loss of pulse detection' for Google Pixel Watch 3, which can call emergency medical services if the wearer loses their pulse and becomes unresponsive. We will review a recent Nature preprint on the development and evaluation of the multimodal machine learning algorithm that powers this safety feature through continuous analysis of pulse data (photoplethysmography).

This one-hour training, provided by a presenter from SAS, will answer question about the most efficient capabilities and processes when using SAS 9.4. This training will offer a question-and-answer session, where participants can ask the presenter questions about SAS software and how to maximize its potential.

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

• Identify current use cases involving SAS software
• Describe how the SAS team can assist users with their work

Attendees are expected to have some working experience with SAS 9.4 or to have attended an introductory SAS class, such as SAS® Programming 1: Essentials. 

This class is not hands-on and will demonstrate to participants the use of IGV for visualizing alignment results from Next Generation Sequencing using RNA as an example. After this class, participants will be able to describe the differences in alignment results generated from splice versus non-splice aware aligners as well as know how to identify RNA splice junctions, potential genomic variants, gauge gene expression differences between samples, and generate visual snapshot for a genomic locus of interest.

Register at https://forms.office.com/g/0LfheEw1we

Meeting link:
https://cbiit.webex.com/cbiit/j.php?MTID=mf4e6636904a6cdeff6d57e6f097b3a55 
Meeting number:
2317 484 5724
Password:
pnD34CGu2F*

Join by video system
Dial 23174845724@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: 2317 484 5724

Host PIN: 2784

This one hour and a half online training provides an accessible introduction to artificial intelligence (AI) using MATLAB. Designed for beginners, the session covers fundamental concepts in AI and machine learning, introduces intuitive tools for building AI models, and demonstrates practical applications of AI techniques in data science. Participants will gain experience working with data preprocessing, model training, and evaluation. 

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

Understand basic concepts and terminology in artificial intelligence and machine learning 
Navigate MATLAB’s tools and workflows for AI, including data preparation, modeling, and evaluation 
Preprocess datasets to prepare for AI model training, including handling missing data and feature scaling 
Develop and evaluate simple supervised learning models (e.g., regression, classification)  
Visualize results and assess the performance of AI models 
Attendees are expected to be familiar with the basic functions of the MATLAB to be successful in this training.

Clinical Molecular Imaging AI

Partek Flow is a point-and-click software for analyzing multi-omics sequencing data including DNA, bulk and single cell RNA, spatial transcriptomics, ATAC and ChIP. Input options include FASTQ, BAM, or expression tables, thus enabling scientists to start analysis at any stage. Hosted on Biowulf, the NIH high performance computing system, this software is suitable for researchers who have no or limited expertise with command line or coding. This class will provide a high-level overview of Partek Flow using bulk RNA sequencing analysis as an example. After this class, participants will:

• Know who has and how to access Partek Flow.
• Become familiar with the Partek Flow user interface.
• Be aware of methods of transferring data to the Partek Flow server.
• Be able to create and import data into projects as well as perform analyses steps using bulk RNA sequencing as an example.
• Know where to get help.

This class is online, will be recorded an not hands-on. Experience with bioinformatics or Partek Flow is not required for participation. Participants do not need to have access to Partek Flow.

Meeting link:

https://cbiit.webex.com/cbiit/j.php?MTID=m45f43bb131519ac310b692056f285d28

AI Club is a weekly meeting that explores various topics relating to AI and deep learning in biomedical sciences, typically in a seminar, workshop, or journal club format. AI Club is intended to be accessible to experts and non-experts alike. We currently meet in the Building 10 Library Training Room on Mondays from 11 - 12. IT IS STRONGLY RECOMMENDED TO COME IN PERSON.

Agreement Across 10 Artificial Intelligence Models in Assessing HER2 in Breast Cancer Whole Slide Images: Findings from the Friends of Cancer Research Digital PATH Project

For more information, please contact Aniruddha Ganguly, Ph.D.

This session of the BTEP Coding Club will showcase NIH HPC OnDemand, a new interface for on-demand access to HPC resources via a web browser. HPC OnDemand simplifies access to graphical sessions and GUI applications such as RStudio, VSCode, and Jupyter Lab. This session, featuring Jonathan Goodson, a Computational Scientist with the NIH HPC Systems and maintainer of HPC OnDemand, will provide everything you need to know to get started using HPC OnDemand today.

Please note: Registration is required to get the Meeting Link for this event. Please pre-register.

Aviv Regev is head of Genentech Research and Early Development. Formerly, Regev was Chair of the Faculty and Core Member at the Broad Institute of MIT and Harvard, Professor of Biology at MIT, and a Howard Hughes Medical Institute Investigator. She is founding co-chair of the Human Cell Atlas and a leader in deciphering molecular circuits that govern cells, tissues, and organs in health and their malfunction in disease. She has pioneered foundational experimental and computational methods in single-cell genomics, enabling greater understanding of cell and tissue functions. Regev is a member of the National Academy of Sciences, National Academy of Medicine, American Academy of Arts and Sciences, and a Fellow of the International Society of Computational Biology. Her many honors include the ISCB Overton and Innovator Prizes, Paul Marks Prize, Lurie Prize in Biomedical Sciences, Keio Medical Science Prize, HFSP Nakasone Award, and L'Oréal-UNESCO for Women in Science Award.

This event will not be recorded at the speakers' request.

Whether you are measuring mRNA expression, protein expression, DNA methylation, expressed miRNAs, protein binding to DNA or RNA, etc., you will likely end up with a list of genes or gene products from which you would like to derive functional relationships. In the -omics world, functional enrichment analysis is an umbrella term encompassing approaches used to derive biological / functional meaning from gene lists. This lesson, which is the first of three lessons focused on "pathway analysis", introduces concepts, methods, tools, and databases related to functional enrichment and pathway analysis. This is NOT a hands-on lesson. 

DAVID (the Database for Annotation, Visualization and Integrated Discovery) provides a comprehensive set of functional annotation tools for investigators to understand the biological meaning behind large lists of genes acquired from high-throughput assays such as RNA-Seq, Proteomics, Microarray, etc. This hands-on lesson will show attendees how to use and interpret results from DAVID using an example gene list. 

AI Club is a weekly meeting that explores various topics relating to AI and deep learning in biomedical sciences, typically in a seminar, workshop, or journal club format. AI Club is intended to be accessible to experts and non-experts alike. We currently meet in the Building 10 Library Training Room on Mondays from 11 - 12. IT IS STRONGLY RECOMMENDED TO COME IN PERSON.

Reactome is a free, open-source, curated and peer-reviewed pathway database that includes bioinformatics tools for the visualization, interpretation and analysis of pathway knowledge. This lesson will showcase the capabilities of Reactome in garnering biological meaning from an example gene list derived from differential expression results. 

AI Club is a weekly meeting that explores various topics relating to AI and deep learning in biomedical sciences, typically in a seminar, workshop, or journal club format. AI Club is intended to be accessible to experts and non-experts alike. We currently meet in the Building 10 Library Training Room on Mondays from 11 - 12. IT IS STRONGLY RECOMMENDED TO COME IN PERSON.

What to bring:  Laptop capable of connecting to internet via NIH wifi

Are you looking to expand the reach of your sequencing to enable what long read technologies can provide?  Please join Oxford Nanopore Technologies (ONT) bioinformatics specialists on a deep dive into getting the most from your long read sequencing data.

This workshop will cover the details of analyzing single-cell RNA sequencing data using our EPI2ME pipeline wf-single-cell. This workflow provides access to industry standard tools for primary processing of single-cell data including deconvolution, quality control, gene and transcript identification, and data visualization. Participants will learn about the EPI2ME software, pipeline details, and work with an ONT bioinformatics expert in a hands-on data analysis training exercise.

This in-person, hands-on workshop gives learners the opportunity to learn the Nanopore Single Cell RNA-Seq Analysis Software Workflow. Taught by Nanopore personnel, with assistance from the CCR Genomics Core and BTEP, this session will run in the morning. Space is limited. If your plans change and you cannot attend, please cancel your registration. There will be no hybrid option for this class, it is in-person only. 

Participants should bring an internet-enabled laptop to access the tools and datasets used for the training. 

Agenda:

9:00-9:15 – Check in & distribute materials

9:15-9:30 – Data analysis intro from Oxford Nanopore Technologies (MinKNOW/EPI2ME/other advanced tools)

9:30-10:00 – Introduction to Single Cell RNA-seq data analysis with Oxford Nanopore Technologies

10:00-11:15 – Hands on data analysis: Single Cell EPI2ME App, nextflow command line, and Biowulf HPC demo

11:15-12:00 – Downstream analysis with Seurat

12:00-12:30 – Closing and Q&A

What to bring:  Laptop capable of connecting to internet via NIH wifi

Are you looking to expand the reach of your sequencing to enable what long read technologies can provide?  Please join Oxford Nanopore Technologies (ONT) bioinformatics specialists on a deep dive into getting the most from your long read sequencing data. 

This workshop will cover the details of analyzing human whole genome sequencing data using our EPI2ME pipeline wf-human-variation. This workflow provides users with tools to perform alignment and variant calling for single nucleotide, structural,  and copy number variants as well as clinically relevant short tandem repeats, and cytosine methylation. Participants will learn about the EPI2ME software, pipeline details, and work with an ONT bioinformatics expert in a hands-on data analysis training exercise.

This in-person, hands-on workshop gives learners the opportunity to learn the Nanopore Human Variation Data Analysis Software Workflow. Taught by Nanopore personnel, with assistance from the CCR Genomics Core and BTEP, this session will run in the afternoon. Space is limited. If your plans change and you cannot attend, please cancel your registration. There will be no hybrid option for this class, it is in-person only. 

Participants should bring an internet-enabled laptop to access the tools and datasets used for the training. 

 1:30-1:45 – Check in & distribute materials

1:45-2:15 – Data analysis intro from ONT (MinKNOW/EPI2ME/other advanced tools)

2:15-2:45 – Introduction to the Human Variation (WGS) pipeline

2:45-4:00 – Hands on data analysis: human variation EPI2ME App, nextflow command line, and Biowulf HPC demo

4:00-4:30 – Review result

4:30-5:00 – Closing/Q&A

What to bring:  Laptop capable of connecting to internet via NIH wifi

For questions or to register, please contact Eric Troop (eric.troop@nanoporetech.com)

Are you looking to expand the reach of your sequencing to enable what long read technologies can provide?  Please join Oxford Nanopore bioinformatics specialists on a deep dive into getting the most from your long read sequencing data.  In conjunction with the Frederick National Lab for Cancer Research (FNLCR), we are offering an in-depth workshop focusing to give you the tools and know how to delve deeper and gain further insight to your biological systems.

Oxford Nanopore Technologies offers data analysis solutions in our EPI2ME software platform tailored to the analysis of long read DNA and RNA sequencing data  from ONT devices. The Single Cell focus will cover the details of analyzing single-cell RNA sequencing data using our EPI2ME pipeline wf-single-cell. This workflow provides access to industry standard tools for primary processing of single-cell data including deconvolution, quality control, gene and transcript identification, and data visualization.

The Human Variation focus will cover the details of analyzing human whole genome sequencing data using our EPI2ME pipeline wf-human-variation. This workflow provides users with tools to perform alignment and variant calling for single nucleotide, structural,  and copy number variants as well as clinically relevant short tandem repeats, and cytosine methylation.

For both, participants will learn about the EPI2ME software, pipeline details, and work with an ONT bioinformatics expert in a hands-on data analysis training exercise.

AI Club is a weekly meeting that explores various topics relating to AI and deep learning in biomedical sciences, typically in a seminar, workshop, or journal club format. AI Club is intended to be accessible to experts and non-experts alike. We currently meet in the Building 10 Library Training Room on Mondays from 11 - 12. IT IS STRONGLY RECOMMENDED TO COME IN PERSON.

AI Club is a weekly meeting that explores various topics relating to AI and deep learning in biomedical sciences, typically in a seminar, workshop, or journal club format. AI Club is intended to be accessible to experts and non-experts alike. We currently meet in the Building 10 Library Training Room on Mondays from 11 - 12. It is strongly recommended to come in person.