ncibtep@nih.gov

Bioinformatics Training and Education Program

BTEP Seminar Series

2024 Seminar Series

Version control with Git

  • When: May 23, 2024
  • Delivery: Online
  • Presented By: Desiree Tillo (GAU, BTEP)
  • Versioning enables researchers to track changes in coding projects. This Coding Club introduces Git (https://git-scm.com), an open-source software used to perform versioning on a personal computer. At the end of this class, participants will:

    • Understand the importance of versioning
    • Describe Git
    • Know how to access Git
      • Be aware of resources that helps with Git installation on personal computer
      • Be aware of the availability of Git on Biowulf, the NIH high performance computing system
    • Define repository
    • Know the steps involved in the versioning process including
      • Initiating a new repository
      • Understanding the difference between tracked and untracked files
      • Excluding files from being tracked
      • Staging files with changes
      • Commiting changes and writing commit messages
      • Viewing commit logs
    • Compare between versions of code
    • Revert to a previous version of code
    Meeting link:
    https://cbiit.webex.com/cbiit/j.php?MTID=m8d56b3aff91ddd2e6df839d05dda6a8f
     
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    2319 013 9531
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Multimodal Data Integration: From Biomarkers to Mechanisms

  • When: May 23, 2024
  • Delivery: Online
  • Presented By: Caroline Uhler, Ph.D. (MIT)
  • An exciting opportunity at the intersection of the biomedical sciences and machine learning stems from the growing availability of large-scale multi-modal data (imaging-based and sequencing-based, observational and perturbational, at the single-cell level, tissue-level, and organism-level). Traditional representation learning methods, although often highly successful in predictive tasks, do not generally elucidate underlying causal mechanisms. Dr. Uhler will present initial ideas towards building a statistical and computational framework for causal representation learning and its applications towards identifying novel disease biomarkers as well as inferring gene regulation in health and disease.

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    2312 523 4308
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The CCBR Single-cell RNA-seq Workflow on NIDAP

  • When: May 29, 2024
  • Delivery: Online
  • Presented By: Joshua Meyer (CCBR)
  • This talk will cover a scRNA-seq workflow available to NCI researchers on NIDAP. NIDAP, the NIH Integrated Data Analysis Platform, is a cloud-based and collaborative data aggregation and analysis platform that hosts user-friendly bioinformatics workflows. This platform allows researchers to use many of the open-source tools discussed in this seminar series without necessitating coding experience. This seminar will focus on the capabilities of this workflow for QC, annotation, and visualization of single-cell RNA-seq data.


A More Comprehensive Landscape of RNA Alterations in Cancer with Long-read Sequencing

  • When: June 6, 2024
  • Delivery: Online
  • Presented By: Angela Brooks, Ph.D., (UCSC)
  • The Brooks Lab developed a computational tool called FLAIR (Full-Length Alternative Isoform Analysis of RNA) to produce confident transcript isoforms from long-read RNA-seq data with the aim of alternative isoform detection and quantification. With an increase in the usage of long-read RNA-seq, there is a growing need for a systematic evaluation of this approach. We are part of an international community effort called the Long-read RNA-seq Genome Annotation Assessment Project (LRGASP) to perform such an evaluation. The Brooks Lab is extending FLAIR to incorporate sequence variation, RNA editing, and RNA modification in isoform detection as well as detection of complex gene fusions from long-read sequencing data.

     
    Meeting number:
    2311 656 4503
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Statistical Methods for Single-Cell RNA-Seq Analysis and Spatial Transcriptomics

  • When: June 20, 2024
  • Delivery: Online
  • Presented By: Rafael Irizarry, Ph.D. (Harvard)
  • Dr. Irizarry will share findings demonstrating limitations of current
    workflows that are popular in single cell RNA-Seq data analysis.
    Specifically, he will describe challenges and solutions to dimension
    reduction, cell-type classification, and statistical significance
    analysis of clustering. Dr. Irizarry will end the talk describing some of his
    work related to spatial transcriptomics. Specifically, he will describe
    approaches to cell type annotation that account for presence of
    multiple cell-types represented in the measurements, a common
    occurrence with technologies such as Visium and SlideSeq. He will
    demonstrate how this approach facilitates the discovery of spatially
    varying genes.
    Meeting link:
    https://cbiit.webex.com/cbiit/j.php?MTID=m9dcd9ce21f4fa6b1a8e2d998a88c2c2b 
     
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    2317 712 9095
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Faraz Faghri

  • When: June 27, 2024
  • Delivery: Online
  • Presented By: Faraz Fahri, Ph.D. (CARD)
  • CARD is a collaborative initiative of the National Institute on Aging and the National Institute of Neurological Disorders and Stroke that supports basic, translational, and clinical research on Alzheimer’s disease and related dementias. CARD’s central mission is to initiate, stimulate, accelerate, and support research that will lead to the development of improved treatments and preventions for these diseases.

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    2310 497 7985
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Kerry Goetz, Ph.D.

  • When: July 25, 2024
  • Delivery: Online
  • Presented By: Kerry Goetz, Ph.D., (NEI)
  • Kerry Goetz, Ph.D.

    Meeting number:
    2302 034 0947
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Genomes, Avatars and AI: The Future of Personalized Medicine

  • When: August 8, 2024
  • Delivery: Online
  • Presented By: Olivier Elemento, Ph.D. (Weill Cornell Medicine)
  • The Elemento lab combines Big Data analytics with experimentation to develop entirely new ways to help prevent, diagnose, understand, treat and ultimately cure disease. Our research involves routine use of ultrafast DNA sequencing, proteomics, high-performance computing, mathematical modeling, and artificial intelligence/machine learning. We’re revolutionizing healthcare by developing innovative approaches to better predict, diagnose, treat, and prevent disease to improve clinical care for every patient.  

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Clinical and Computational Molecular Profiling in Pediatric Cancer Diagnostics

  • When: August 29, 2024
  • Delivery: Online
  • Presented By: Elaine Mardis, Ph.D. (Nationwide Children's Hospital)
  • Dr. Mardis is an internationally recognized expert in cancer genomics, with ongoing interests in the integrated characterization of cancer genomes, defining DNA-based somatic and germline interactions and RNA-based pathways, and immune microenvironments that lead to cancer onset and progression, specifically involving pediatric cancers. Most recently, her research has been oriented toward translational aspects of cancer genomics, specifically identifying how the cancer genome changes with treatment, including acquired resistance, the use of genomics in understanding immune therapy response, and the clinical benefit of cancer molecular profiling in the pediatric setting.

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    2312 714 2024
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Rachel O'Neill

  • When: September 12, 2024
  • Delivery: Online
  • Presented By: Rachel O'Neill, Ph.D. (Univ. of Connecticut)
  • Dr. O'Neill's research programs employ molecular genetics, genomics and computational approaches to study the mechanisms that maintain, and disrupt, genome stability with a particular focus on repetitive elements. Projects include studying: retroelement transcription and centromere function; novel small RNA biogenesis pathways; and global chromosome and genome changes during instability (such as in cancer and hybrid dysgenesis). In addition, we use a diverse set of rapidly evolving next generation sequencing (NGS) technologies and novel library preparation and computational methodologies for drafting and characterizing genome sequences in efforts to establish broad eukaryotic species as models for studying genome biology. Recently, Dr. O'Neill's lab has expanded their efforts towards applying broad NGS techniques to both model and non-model systems to understand the dynamic response of the genome to environmental queues, such as global warming.

    Meeting number:
    2315 524 3558
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AI: Baris Turkbey - AIR

  • When: September 26, 2024
  • Delivery: Online
  • Presented By: Ismail Baris Turkbey, M.D. (NCI CCR AIR)
  • The goal of Artificial Intelligence Resource (AIR) is to make AI tools available to Center for Cancer Research (CCR) investigators. The strength of AI is that algorithms can be trained to seek specific information that may be scientifically or clinically important.  AIR will mainly focus on “Computer Vision” which analyzes medical images, such as radiologic, digital pathology, video/endoscopy, and optical imaging among others.  Examples of potential projects include developing better screening, detection methods or predictive markers, or improving procedures among many others. Both clinical and laboratory-based imaging projects will be considered. Please refer to our ongoing projects and prior publications for more information.

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Building and Rebuilding the Vertebrate Retina, One Cell at a Time

  • When: November 7, 2024
  • Delivery: Online
  • Presented By: Seth Blackshaw, Ph.D. (Johns Hopkins)
  • Dr. Blackshaw's work examines the molecular basis of neuronal and glial cell fate specification and survival, focusing on characterizing the network of genes that control specification of different cell types within the retina and hypothalamus, two structures that arise from the embryonic forebrain.  The ultimate goal is to use insights gained from learning how individual cell types are specified to understand how these cells contribute to the regulation of behavior, and how they can be replaced in neurodegenerative disease.

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    2312 437 6963
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David Reif, Ph.D.

  • When: November 14, 2024
  • Delivery: Online
  • Presented By: David Reif, Ph.D. (NIEHS)
  • David M. Reif, Ph.D., joined the NIEHS in 2022 as Chief of the Predictive Toxicology Branch (PTB) in the Division of Translational Toxicology (DTT). In this role, he will leverage expertise of the branch in data science, toxicogenomics, spatiotemporal exposures and toxicology, computational methods development, and new approach methods (NAMs) to advance predictive toxicology applications with partners across NIEHS, the interagency Tox21 Program and the Interagency Coordinating Committee on the Validation of Alternative Methods (ICCVAM).

    Meeting number:
    2318 207 2771
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Pre-clinical Evaluation of Targeted Therapies for Pediatric Cancer

  • When: November 21, 2024
  • Delivery: Online
  • Presented By: Carol Bult, Ph.D., (The Jackson Lab)
  • The primary theme of Dr. Bult's personal research program is “bridging the digital biology divide,” reflecting the critical role that informatics and computational biology play in modern biomedical research. Dr. Bult is a Principal Investigator in the Mouse Genome Informatics (MGI) consortium that develops knowledge-bases to advance the laboratory mouse as a model system for research into the genetic and genomic basis of human biology and disease. Recent research initiatives in Dr. Bult's research group include computational prediction of gene function in the mouse and the use of the mouse to understand genetic pathways in normal lung development and disease.

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    2309 763 3797
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Differential Expression Analysis with Seurat Archived

  • When: May 22, 2024
  • Delivery: Online
  • Presented By: Nathan Wong (CCBR)
  • This seminar provides an overview of differential expression testing with Seurat. Topics to be covered include preparing data for differential gene expression, differential gene analysis between specific groups, differential gene analysis for cluster classification, SingleR for cell type annotation, and visualizing genes of interest.  

     

     


Transforming Medicine with AI: From TrialGPT to GeneAgent Archived

  • When: May 2, 2024
  • Delivery: Online
  • Presented By: Dr. Zhiyong Lu (NCBI)
  • The explosion of biomedical big data and information in the past decade or so has created new opportunities for discoveries to improve the treatment and prevention of human diseases. As such, the field of medicine is undergoing a paradigm shift driven by AI-powered analytical solutions. This talk explores the benefits (and risks) of AI and ChatGPT, highlighting their pivotal roles in revolutionizing biomedical discovery, patient care, diagnosis, treatment, and medical research. By demonstrating their uses in some real-world applications such as improving biomedical literature searches (Nature Biotechnology 2018; Nature 2020; Nature Genetics 2023), accelerating patient trial matching (TrialGPT, in collaboration with NCI clinicians), and assisting gene set analysis (GeneAgent, in collaboration with NCI researchers), we underscore the potential of AI and ChatGPT in enhancing clinical decision-making, personalizing patient experiences, and accelerating knowledge discovery.

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    2300 950 8025
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Getting Started with Seurat: QC to Clustering Archived

  • When: May 1, 2024
  • Delivery: Online
  • Presented By: Alex Emmons (BTEP)
  • This lesson reviews many of the standard steps in a scRNA-Seq workflow: QC filtering, normalization, scaling, and clustering. 


Introduction to scRNA-Seq with R (Seurat) Archived

  • When: April 24, 2024
  • Delivery: Online
  • Presented By: Alex Emmons (BTEP)
  • This seminar provides an introduction to R in the context of single cell RNA-Seq analysis with Seurat.  In this seminar, attendees will learn about options for analyzing scRNA-Seq data, resources for learning R, how to import scRNA-Seq data, and how to create, examine, and access data stored in a Seurat object.  


SCAF: Overview of Cell Ranger output files and single cell data analysis quality control Archived

  • When: April 17, 2024
  • Delivery: Online
  • Presented By: Kimia Dadkhah (SCAF)
  • Kimia Dadkhah, bioinformatics analyst (SCAF), will talk about Cell Ranger output and essential quality control metrics in single cell data analysis, how to interpret these and make informed decisions, and other considerations to keep in mind when assessing the quality of returned data from SCAF.  


Engineering Serendipity: Computational Methods for Large-Scale Data Extraction Archived

  • When: April 11, 2024
  • Delivery: Online
  • Presented By: Casey Greene, Ph.D., (CU Anschutz)
  • Informaticians aim to bring the right information to the forefront at the right time to improve decision-making. Dr. Greene's  lab develops computational methods that integrate distinct large-scale datasets to extract the rich and intrinsic information embedded in such integrated data. Dr. Greene will discuss how this can reveal underlying principles of an organism’s genetics, its environment, and its response to that environment. Dr. Greene will also discuss work in the CU Anschutz Center for Personalized Medicine that brings genetics to the point of care.

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    2304 252 4992
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Introduction to single cell RNA-Seq Archived

  • When: April 10, 2024
  • Delivery: Online
  • Presented By: Charlie Seibert, Saeed Yadranji Aghdam
  • Single cell RNA sequencing (scRNA-Seq) is becoming increasingly more common in biomedical research, but what is scRNA-Seq? How does it differ from other transcriptomic approaches (e.g., bulk RNA-Seq), and what are the potential applications, technologies, and workflows? This presentation will introduce learners to scRNA-Seq, answering the above and touching on additional topics such as methodological challenges, concerns, and best practices.  


Explainable Artificial Intelligence (XAI) and Single Cell Genomics to Understand the Cellular Complexity of the Human Brain Archived

  • When: April 4, 2024
  • Delivery: Online
  • Presented By: Richard Scheuermann, Ph.D. (NLM)
  • Although generative artificial intelligence (AI), a’la ChatGPT, is receiving a lot of “attention” these days, there are many other options for using AI to support biomedical research.  In order to help analyze and interpret single cell genomics data, we have found that AI approaches that retain “explainability” are especially useful in providing functional insights into the underlying biological systems being studied, in this case, the human brain.

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    2319 134 3591
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The CCR Single Cell Analysis Facility (SCAF): An Overview Archived

  • When: April 3, 2024
  • Delivery: Online
  • Presented By: Mike Kelly (SCAF)
  • The Single Cell Analysis Facility (SCAF) is a CCR facility dedicated to the application of single-cell technologies in cancer research. Based on the NIH Bethesda main campus, SCAF aims to provide the broadest range of project support from consultation on experimental design, sequencing, and data analysis. Learn more about SCAF and the single-cell genomics technologies available to CCR investigators in this overview presentation. 


An Introduction to DAVID for Functional Enrichment Analysis Archived

  • When: March 27, 2024
  • Delivery: Online
  • Presented By: Brad Sherman, Weizhong Chang
  • 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.  In this BTEP Coding Club session, developers from DAVID (Weizhong Chang and Brad Sherman) will give an overview of DAVID and provide training on key tools including functional annotation tools (table, chart, and clustering), gene functional classification, gene ID conversion, gene name batch viewer, and the newly developed ortholog conversion tool.

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How Large Language Models (LLMs) Accelerate Data Discovery and Harmonization Archived

  • When: March 21, 2024
  • Delivery: Online
  • Presented By: Mike Nalls Ph.D. (CARD)
  • Context-aware AI implemented to facilitate data discovery and harmonization has significantly accelerated some of the common bottlenecks in the collaborative research process. Pilot work has shows major time and cost savings compared to current completely manual processes.

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    2314 904 4579
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Artificial Intelligence in the Biomedical Sciences Archived

  • When: February 29, 2024
  • Delivery: Online
  • Presented By: Brian Ondov, Ph.D. (NLM)
  • Artificial Intelligence (AI) is becoming increasingly ubiquitous in biomedical research, enabled by large datasets, new algorithms, and hardware improvements. In this session, Dr. Brian Ondov will introduce the basic principles of AI and describe how its various forms can help researchers in different ways, including image classification, sequence-based prediction, generative models, and language understanding. 

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Version control using Git (Cancelled) Archived

  • When: February 28, 2024
  • Delivery: Online
  • Presented By: Joe Wu (BTEP)
  • Versioning enables researchers to track changes in coding projects. This Coding Club session will introduce Git (https://git-scm.com), an open-source software used to perform versioning locally and enables users to upload code to web repositories such as GitHub. At the end of this class, participants will

    • Be able to describe Git
    • Be able to use Git to
      • Create coding projects 
      • Save and track changes to code
      • Upload code to GitHub
      • Revert to/view previous versions of code
      • Perform basic collaboration tasks

     

    Installation of software is not needed to participate.

    Meeting information:

    Meeting link:
    https://cbiit.webex.com/cbiit/j.php?MTID=meadb08ed71552393fe486073a7a7ffc5 
    Meeting number:
    2308 646 3414
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Version control using Github Archived

  • When: February 21, 2024
  • Delivery: Online
  • Presented By: Joe Wu (BTEP), Nadim Rizk (CBIIT)
  • Versioning enables researchers to track changes in coding projects. This Coding Club session will introduce the versioning tool GitHub (https://github.com). At the end of this class, participants will

    • Become familiar with options available for using GitHub at NCI
    • Be able to use GitHub to
      • Create coding projects 
      • Track changes in code
      • Revert to a previous version of code
      • Collaborate with the project team

     

    Installation of software is not needed to participate.

    This class will be followed by one addressing versioning using Git on February 28, 2024 from 11 AM to 12 PM. See https://bioinformatics.ccr.cancer.gov/btep/classes/version-control-using-git for information and registration.

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    Meeting link:
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    Meeting number:
    2308 646 3414
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Documenting Your Analysis with Quarto Archived

  • When: January 24, 2024
  • Delivery: Online
  • Presented By: Alex Emmons (BTEP)
  • Documenting your data analysis is a crucial step toward making your research reproducible. In this session of the BTEP Coding Club, we will learn how to get started using Quarto with RStudio for report generation. 

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2023 Seminar Series

Creating R / Python templates for the NIH Integrated Data Analysis Platform (NIDAP) Archived

  • When: December 6, 2023
  • Delivery: Online
  • Presented By: Alexei Lobanov (CCBR)
  • NIDAP, the NIH Integrated Data Analysis Platform, is a cloud-based and collaborative data aggregation and analysis platform. The NIDAP platform hosts user-friendly bioinformatics workflows (Bulk RNA-Seq, scRNA-Seq, Digital Spatial Profiling) and other component analysis and visualization tools that have been created and maintained by the NCI developer community based on open-source tools.
     
    In this BTEP Coding Club session, Alexei Lobanov, bioinformatics analyst with CCBR, will demonstrate how to create NIDAP templates, GUI-like environments that allow users to run the same code on new datasets using a point-and-click approach, from source code (R or python).
     
    Why create a NIDAP template? 1) “Templatizing” your code is easy and allows users / collaborators with no coding skills to efficiently use your code. 2) Pre-made templates encourage efficiency and reproducibility. Templates allow the user to easily create custom workflows and pipelines that can be shared with collaborators and/or applied to future data sets.
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Visualizing multi-dimensional omics data with circular plots in R package OmicCircos Archived

  • When: November 15, 2023
  • Delivery: Online
  • Presented By: Chunhua Yan (CBIIT CGBB), Ying Hu (CBIIT CGBB)
  • This session introduces two versions of the R/ Bioconductor package OmicCircos to generate high-quality circular plots for visualizing multi-dimensional omics data:

    1. coding in the R environment for programmers;
    2. point-and-click OmicCircos R Shiny app on the Cancer Genomics Cloud (CGC) for non-programmers. 

     

    Meeting number:2310 050 3184

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Translating Single Cell Genomics for use in Patients after Blood and Marrow Transplantation Archived

  • When: November 2, 2023
  • Delivery: Online
  • Presented By: Scott Furlan (Fred Hutchinson Cancer Center)
  • In this seminar, Dr. Furlan will share data using single cell genomic technologies after hematopoietic cell transplantation including the molecular approaches and computational tools they have used and developed as they relate to this field.

    Meeting number:
    2302 366 1547
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Accessing data from and Submitting data to the Gene Expression Omnibus (GEO) Archived

  • When: October 18, 2023
  • Delivery: Online
  • Presented By: Joshua Meyer (CCBR)
  • This October session of the BTEP Coding club will feature a tutorial on how to access data from GEO as well as how to submit data to GEO. 

     

     


CANCELLED EVENT: Precisely Practicing Medicine from 700 Trillion Points of Data Archived

  • When: October 5, 2023
  • Delivery: Online
  • Presented By: Atul Butte, MD (UCSF)
  • There is an urgent need to take what we have learned in our new data-driven era of medicine, and use it to create a new system of precision medicine, delivering the best, safest, cost-effective preventative or therapeutic intervention at the right time, for the right patients.  Dr. Butte's teams at the University of California build and apply tools that convert trillions of points of molecular, clinical, and epidemiological data -- measured by researchers and clinicians over the past decade and now commonly termed “big data” -- into diagnostics, therapeutics, and new insights into disease.  Dr. Butte, a computer scientist and pediatrician, will highlight his center’s recent work on integrating electronic health records data from over 8 million patients across the entire University of California, and how analytics on this “real world data” can lead to new evidence for drug efficacy, new savings from better medication choices, and new methods to teach intelligence – real and artificial – to more precisely practice medicine.

     
     
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Whole Embryo Developmental Genetics at Single Cell Resolution Archived

  • When: September 28, 2023
  • Delivery: Online
  • Presented By: Cole Trapnell (Univ. of Washington)
  • The Trapnell Lab at the University of Washington's Department of Genome Sciences studies how genomes encode the program of vertebrate development and how that program goes awry in disease. We build new tools, technologies, and software for decoding this program from large-scale single-cell experiments.

    Meeting number:
    2305 942 7068
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Using rMATS for differential alternative splicing detection Archived

  • When: September 20, 2023
  • Delivery: Online
  • Presented By: Alexei Lobanov (CCBR)
  • This session of the BTEP Coding Club will focus on the tool rMATS for differential alternative splicing event detection from RNA-Seq data. This 1-hour demo will provide a detailed overview of rMATS including why you may want to use it, how to use it, and how to interpret and further use resulting outputs. 

    https://rnaseq-mats.sourceforge.io/

    Multivariate Analysis of Transcript Splicing (MATS)

    MATS is a computational tool to detect differential alternative splicing events from RNA-Seq data. The statistical model of MATS calculates the P-value and false discovery rate that the difference in the isoform ratio of a gene between two conditions exceeds a given user-defined threshold. From the RNA-Seq data, MATS can automatically detect and analyze alternative splicing events corresponding to all major types of alternative splicing patterns. MATS handles replicate RNA-Seq data from both paired and unpaired study design.


Hematopoietic stem cell-intrinsic and -extrinsic contribution to aging and clonal hematopoiesis Archived

  • When: September 14, 2023
  • Delivery: Online
  • Presented By: Jennifer Trowbridge (The Jackson Lab)
  • While there is a positive correlation between cancer and aging, the mechanisms underlying this relationship remain unclear. Clonal hematopoiesis, a benign condition that is both associated with aging and predisposes to increased risk of development of blood cancers, presents an opportunity to understand the connection between cancer and aging. This seminar will discuss emerging discoveries of mechanisms acting within the hematopoietic stem cells as well as alterations in the bone marrow microenvironment that promote clonal hematopoiesis and transformation to blood cancers.

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Using EnhancedVolcano and ComplexHeatmap to visualize -omics data Archived

  • When: August 16, 2023
  • Delivery: Online
  • Presented By: Joe Wu (BTEP)
  • Heatmaps and volcano plots are common data visualizations in bioinformatic analyses of genomic data, such as bulk RNA-seq. While both plot types can be used to visualize gene expression, heatmaps can be used to examine expression data across samples, and in combination with clustering techniques, reveal potential patterns in the data. Volcano plots demonstrate the direction, distribution, and statistical significance of gene expression between experimental conditions (example tumor vs. non-tumor, or drug treated vs. non-treated). In this coding club, we will demonstrate how to construct these plots using the R/Bioconductor tools ComplexHeatmap and EnhancedVolcano.

     

     


A Beginners Guide to Troubleshooting R Code Archived

  • When: July 19, 2023
  • Delivery: Online
  • Presented By: Alex Emmons (BTEP)
  • This session of the BTEP Coding Club will focus on strategies for overcoming errors, warnings, and other common problems with R code. In this 1-hour tutorial targeting beginner R users, we will discuss commonly observed errors, how to find help, and how to approach and debug R code. 


Single Cell Annotation with SingleR: Macrophage-fibroblast crosstalk in lung fibrosis Archived

  • When: June 22, 2023
  • Delivery: Online
  • Presented By: Mallar Bhattacharya, M.D. (UCSF)
  • The Bhattacharya Lab at the UCSF Parnassus Campus is focused on the functional role of monocyte-derived macrophages in the onset and persistence of fibrosis in the lung. We are addressing the following major questions, with a goal of discovering new targets for therapy for acute lung injury and fibrosis:

    • What molecules released by monocyte-derived macrophages and other immune cells signal to and activate pro-fibrotic programs in parenchymal cell types such as fibroblasts and epithelial cells?
    • What reciprocal signals derive from these parenchymal cells to modify the immune response?
    • How can this pathologic crosstalk be reversed to combat fibrosis and restore lung health?
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BTEP Coding Club: Submitting Scripts to the Biowulf Batch System Archived

  • When: June 21, 2023
  • Delivery: Online
  • Presented By: Joe Wu (BTEP)
  • Biowulf is the high-performance computing cluster (HPC) at NIH. In addition to its vast compute power, Biowulf has hundreds of bioinformatics tools and databases for analyzing Next Generation Sequencing (NGS) data. This coding club will provide participants the foundations for harnessing Biowulf’s computing power to analyze NGS data. Participants will learn to request computing resources on and to submit scripts to the Biowulf system. This class is not hands-on so no need to obtain a Biowulf account prior to attending.

     

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CellTypist v2.0: Automatic Cell Type Harmonization and Integration in Single Cell Data Archived

  • When: June 1, 2023
  • Delivery: Online
  • Presented By: Chuan Xu, Ph.D. (Teichmann Lab)
  • 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.

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Learning and Transferring Cellular State in Single Cell Atlases Archived

  • When: May 25, 2023
  • Delivery: Online
  • Presented By: Fabian Theis (Helmholtz Munich)
  • Single-cell technologies, such as single-cell RNA sequencing (scRNA-seq), have increased the resolution achieved in the study of cellular phenotypes, allowing measurements of thousands of different genes in thousands of individual cells. This has created an opportunity to begin understanding the dynamics of the prime biological processes undergone by cells, while requiring unique computational tools. In our lab, we develop novel and innovative computational methods for single-cell data analysis. - Theis Lab

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Functional Enrichment Analysis with clusterProfiler Archived

  • When: May 17, 2023
  • Delivery: Online
  • Presented By: Alex Emmons (BTEP)
  • Functional enrichment analysis is used to understand the biological context of gene lists or differential expression results. There are a multitude of tools available for this purpose. clusterProfiler is a popular R / Bioconductor package supporting over-representation analysis (ORA) and gene set enrichment analysis (GSEA) using up-to-date biological knowledge of genes and biological processes (GO and KEGG) and support for thousands of organisms. The latest version of clusterProfiler (v. 4.6.2) also provides a tidy interface for visualizing resulting output.

    This May 2023 session of the BTEP Coding Club will provide an overview and demo of many of the key features of the clusterProfiler R package. 


The Power of Connection: How the Cancer Research Data Commons enables researchers to connect data, computational tools, and collaborators to accelerate discovery Archived

  • When: May 4, 2023
  • Delivery: Online
  • Presented By: Brandi Davis-Dusenbery (Velsera)
  • The National Cancer Insitute (NCI) Cancer Research Data Commons (CRDC) includes petabytes of genomic, proteomic, imaging and other data that can be immediately accessed and analyzed by approved users in a secure cloud environment. In this webinar, attendees will learn how the CRDC is transforming cancer research by streamlining collaboration, democratizing access to data and increasing accessibility of complex computational algorithms. We will include a live demonstration of the Seven Bridges Cancer Genomics cloud as well as case studies of research performed in the CRDC. 
     
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Documenting Data Analysis with Jupyter Lab Archived

  • When: April 19, 2023
  • Delivery: Online
  • Presented By: Joe Wu (BTEP)
  • This BTEP coding club will introduce beginners to Jupyter Notebook, a platform to organize code and analysis steps in one place. Jupyter Notebook can be easily installed or run in a web browser, and supports several languages such as R and Python. It provides a way to keep track of all steps in an analysis and a place for collaboration. Come learn what Jupyter Notebook can do for you. This class will not be hands-on so need to install anything to attend.


Rahul Satija: (Azimuth) Annotation of Cell Types in Single Cell Analysis of Cancer Archived

  • When: April 6, 2023
  • Delivery: Online
  • Presented By: Rahul Satija (NYU)
  • Azimuth is a web application that uses an annotated reference dataset to automate the processing, analysis, and interpretation of a new single-cell RNA-seq experiment. Azimuth leverages a 'reference-based mapping' pipeline that inputs a counts matrix of gene expression in single cells, and performs normalization, visualization, cell annotation, and differential expression (biomarker discovery). All results can be explored within the app, and easily downloaded for additional downstream analysis. - Satija Lab

    The development of Azimuth is led by the New York Genome Center Mapping Component as part of the NIH Human Biomolecular Atlas Project (HuBMAP).

    This webinar will be recorded and made available on the BTEP web site: https://bioinformatics.ccr.cancer.gov/btep/btep-video-archive-of-past-classes/ within 48 hours after the event ends. 

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AI Models of Cancer in Precision Medicine: Trey Ideker Archived

  • When: March 30, 2023
  • Delivery: Online
  • Presented By: Trey Ideker (UCSD)
  • AI Models of Cancer and Precision Medicine: Building a Mind for Cancer

    The long-term objective of the Ideker Lab is to create artificially intelligent, mechanistic models of cancer and neurodegenerative diseases for translation of patient data to precision diagnosis and treatment. We seek to advance this goal by addressing fundamental questions in the field: What are the genetic and molecular networks that promote disease, and how do we best chart these? How do we use knowledge of these networks in intelligent systems for predicting the effects of genotype on phenotype? – Ideker Lab, https://idekerlab.ucsd.edu/research/cancer/

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    This webinar will be recorded and made available on the BTEP web site: https://bioinformatics.ccr.cancer.gov/btep/btep-video-archive-of-past-classes/ within 48 hours after the event ends. 

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VLOOKUP in excel and the R programming equivalent Archived

  • When: March 15, 2023
  • Delivery: Online
  • Presented By: Alex Emmons (BTEP)
  • Do you use excel's VLOOKUP function often to merge tables or search for subsets of data in large NGS data files? If so, you may be interested in a more programmatic solution. Join us for a lesson on performing VLOOKUP in excel followed by a more reproducible solution with R programming. Whether you are interested in merging a list of gene ids with a table of functional annotations or searching for unique matches of known T-Cell Receptor sequences among output from a 10X TCR sequencing run, this tutorial will likely be useful to you.  

    This tutorial will kick off the BTEP Coding Club, which features monthly 1-hour tutorials of bioinformatics tools, software, or skills. Email us at ncibtep@nih.gov if you would like to see a topic featured by the BTEP Coding Club. 

2022 Seminar Series

A 500 Year Plan for Genetics, Epigenetics and Cell Engineering Archived

  • When: September 22, 2022
  • Delivery: Online
  • Presented By: Christopher Mason (Weill Cornell Medicine)
  • The avalanche of easy-to-create genomics data has impacted almost all areas of medicine and science, from cancer patients and microbial diagnostics to molecular monitoring for astronauts in space. In this lecture, new discoveries from RNA- and DNA-sequencing with the FDA’s SEQC study show the ability of single-molecule methods to reveal rare alleles and provide more comprehensive epigenomics maps of patients and cancers. Also, recent technologies and algorithms from our laboratory and others demonstrate that an integrative, cross-kingdom view of patients (precision metagenomics) holds unprecedented biomedical potential to discern risk, improve diagnostic accuracy, and to map both genetic and epigenetic states, as well as clonal changes in mutations with clonal hematopoiesis. Finally, these methods and molecular tools work together to guide comprehensive, longitudinal, multi-omic views of human astronaut physiology and biology in the NASA Twins Study and several other missions with SpaceX and Axiom, which lay the foundation for future, long-duration spaceflight, including sequencing, quantifying, and engineering genomes to survive on other planets over the next 500 years (https://mitpress.mit.edu/books/next-500-years).

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Decoding Breast Cancer Progression with Single Cell Genomics Archived

  • When: July 14, 2022
  • Delivery: Online
  • Presented By: Nicholas Navin (MD Anderson Cancer Center)
  • The efforts of our laboratory are split evenly between experimental and computational biology.  We develop new experimental methods to sequence single cells and isolate rare subpopulations and develop new analytical approaches to detect variants and apply statistical methods to these data sets.  We focus mainly on breast cancer to understand the role of clonal diversity in the evolution of invasion, metastasis and response to chemotherapy.  We are also using these tools to study rare tumor cell subpopulations including circulating tumor cells and cancer stem cells.  Our goal is to understand the role of clonal diversity in tumor evolution so that we can exploit this diversity for therapeutic vulnerabilities and improve diagnostic tools and the early detection of cancer.  We fully expect that applying these tools to human patients will lead to reduced morbidity in breast cancer.

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Mapping the Human Body One Cell at a Time Archived

  • When: June 16, 2022
  • Delivery: Online
  • Presented By:
  • Sarah Teichmann is co-founder and principal leader of the Human Cell Atlas (HCA) international consortium. The International Human Cell Atlas initiative aims to create comprehensive reference maps of all human cells to further understand health and disease.

    The 37 trillion cells of the human body have a remarkable array of specialized functions, and must cooperate and collaborate in time and space to construct a functioning human. In this talk I will describe my lab’s efforts to understand this cellular diversity through a programme of cell atlasing. Harnessing cutting edge single cell genomics, imaging and computational technologies, we investigate development, homeostasis and disease states, at scale and in 3D, with a particular focus on immunity. I will illustrate the relevance of cell atlas-ing for engineering organoids and regenerative medicine, and will share new results providing insights into pacemaker cells from the sinoatrial node of this heart. Overall I hope to illustrate the power of single cell approaches in unlocking fundamental knowledge about the human body.

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Realizing Data Interoperability Across Basic Research, Clinical Care, and Patients Archived

  • When: April 21, 2022
  • Delivery: Online
  • Presented By: Melissa Haendel (CU Anschutz)
  • Making data reusable for discovery and shared analytics across domains is a laborious, specific-skill requiring task that most data providers do not have the resources, expertise, or perspective to perform. Equally challenged are the data re-users, who function in a landscape of bespoke schemas, formats, and coding – when they can get past understanding the licensing and access control issues. Making the most of our collective data requires partnerships between basic researchers, clinicians, patients, and informaticians, as well as sophisticated strategies to address a myriad of interoperability issues. This talk will review different communities endeavors towards these ends from across the translational spectrum.

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Integrated Analysis of Single Cell Data Across Technologies and Modalities Archived

  • When: February 17, 2022
  • Delivery: Online
  • Presented By: Rahul Satija (NYU)
  • Our goal is to understand how cellular heterogeneity encodes the molecular structure, function, and regulation of complex biological systems. Primarily using single cell genomics, we analyze systems by profiling their most fundamental units individually – a ‘bottom-up’ approach that allows us to study how diverse groups of cells work together to drive biological processes and behaviors. – Satija Lab

    Since Dr. Satija will be presenting unpublished work in this webinar, it will not be recorded or distributed.

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2024 Seminar Series

Multimodal Data Integration: From Biomarkers to Mechanisms

  • When: May 23, 2024
  • Delivery: Online
  • Presented By: Caroline Uhler, Ph.D. (MIT)
  • An exciting opportunity at the intersection of the biomedical sciences and machine learning stems from the growing availability of large-scale multi-modal data (imaging-based and sequencing-based, observational and perturbational, at the single-cell level, tissue-level, and organism-level). Traditional representation learning methods, although often highly successful in predictive tasks, do not generally elucidate underlying causal mechanisms. Dr. Uhler will present initial ideas towards building a statistical and computational framework for causal representation learning and its applications towards identifying novel disease biomarkers as well as inferring gene regulation in health and disease.

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A More Comprehensive Landscape of RNA Alterations in Cancer with Long-read Sequencing

  • When: June 6, 2024
  • Delivery: Online
  • Presented By: Angela Brooks, Ph.D., (UCSC)
  • The Brooks Lab developed a computational tool called FLAIR (Full-Length Alternative Isoform Analysis of RNA) to produce confident transcript isoforms from long-read RNA-seq data with the aim of alternative isoform detection and quantification. With an increase in the usage of long-read RNA-seq, there is a growing need for a systematic evaluation of this approach. We are part of an international community effort called the Long-read RNA-seq Genome Annotation Assessment Project (LRGASP) to perform such an evaluation. The Brooks Lab is extending FLAIR to incorporate sequence variation, RNA editing, and RNA modification in isoform detection as well as detection of complex gene fusions from long-read sequencing data.

     
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Statistical Methods for Single-Cell RNA-Seq Analysis and Spatial Transcriptomics

  • When: June 20, 2024
  • Delivery: Online
  • Presented By: Rafael Irizarry, Ph.D. (Harvard)
  • Dr. Irizarry will share findings demonstrating limitations of current
    workflows that are popular in single cell RNA-Seq data analysis.
    Specifically, he will describe challenges and solutions to dimension
    reduction, cell-type classification, and statistical significance
    analysis of clustering. Dr. Irizarry will end the talk describing some of his
    work related to spatial transcriptomics. Specifically, he will describe
    approaches to cell type annotation that account for presence of
    multiple cell-types represented in the measurements, a common
    occurrence with technologies such as Visium and SlideSeq. He will
    demonstrate how this approach facilitates the discovery of spatially
    varying genes.
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Genomes, Avatars and AI: The Future of Personalized Medicine

  • When: August 8, 2024
  • Delivery: Online
  • Presented By: Olivier Elemento, Ph.D. (Weill Cornell Medicine)
  • The Elemento lab combines Big Data analytics with experimentation to develop entirely new ways to help prevent, diagnose, understand, treat and ultimately cure disease. Our research involves routine use of ultrafast DNA sequencing, proteomics, high-performance computing, mathematical modeling, and artificial intelligence/machine learning. We’re revolutionizing healthcare by developing innovative approaches to better predict, diagnose, treat, and prevent disease to improve clinical care for every patient.  

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Clinical and Computational Molecular Profiling in Pediatric Cancer Diagnostics

  • When: August 29, 2024
  • Delivery: Online
  • Presented By: Elaine Mardis, Ph.D. (Nationwide Children's Hospital)
  • Dr. Mardis is an internationally recognized expert in cancer genomics, with ongoing interests in the integrated characterization of cancer genomes, defining DNA-based somatic and germline interactions and RNA-based pathways, and immune microenvironments that lead to cancer onset and progression, specifically involving pediatric cancers. Most recently, her research has been oriented toward translational aspects of cancer genomics, specifically identifying how the cancer genome changes with treatment, including acquired resistance, the use of genomics in understanding immune therapy response, and the clinical benefit of cancer molecular profiling in the pediatric setting.

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Rachel O'Neill

  • When: September 12, 2024
  • Delivery: Online
  • Presented By: Rachel O'Neill, Ph.D. (Univ. of Connecticut)
  • Dr. O'Neill's research programs employ molecular genetics, genomics and computational approaches to study the mechanisms that maintain, and disrupt, genome stability with a particular focus on repetitive elements. Projects include studying: retroelement transcription and centromere function; novel small RNA biogenesis pathways; and global chromosome and genome changes during instability (such as in cancer and hybrid dysgenesis). In addition, we use a diverse set of rapidly evolving next generation sequencing (NGS) technologies and novel library preparation and computational methodologies for drafting and characterizing genome sequences in efforts to establish broad eukaryotic species as models for studying genome biology. Recently, Dr. O'Neill's lab has expanded their efforts towards applying broad NGS techniques to both model and non-model systems to understand the dynamic response of the genome to environmental queues, such as global warming.

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Building and Rebuilding the Vertebrate Retina, One Cell at a Time

  • When: November 7, 2024
  • Delivery: Online
  • Presented By: Seth Blackshaw, Ph.D. (Johns Hopkins)
  • Dr. Blackshaw's work examines the molecular basis of neuronal and glial cell fate specification and survival, focusing on characterizing the network of genes that control specification of different cell types within the retina and hypothalamus, two structures that arise from the embryonic forebrain.  The ultimate goal is to use insights gained from learning how individual cell types are specified to understand how these cells contribute to the regulation of behavior, and how they can be replaced in neurodegenerative disease.

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    2312 437 6963
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Pre-clinical Evaluation of Targeted Therapies for Pediatric Cancer

  • When: November 21, 2024
  • Delivery: Online
  • Presented By: Carol Bult, Ph.D., (The Jackson Lab)
  • The primary theme of Dr. Bult's personal research program is “bridging the digital biology divide,” reflecting the critical role that informatics and computational biology play in modern biomedical research. Dr. Bult is a Principal Investigator in the Mouse Genome Informatics (MGI) consortium that develops knowledge-bases to advance the laboratory mouse as a model system for research into the genetic and genomic basis of human biology and disease. Recent research initiatives in Dr. Bult's research group include computational prediction of gene function in the mouse and the use of the mouse to understand genetic pathways in normal lung development and disease.

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Engineering Serendipity: Computational Methods for Large-Scale Data Extraction Archived

  • When: April 11, 2024
  • Delivery: Online
  • Presented By: Casey Greene, Ph.D., (CU Anschutz)
  • Informaticians aim to bring the right information to the forefront at the right time to improve decision-making. Dr. Greene's  lab develops computational methods that integrate distinct large-scale datasets to extract the rich and intrinsic information embedded in such integrated data. Dr. Greene will discuss how this can reveal underlying principles of an organism’s genetics, its environment, and its response to that environment. Dr. Greene will also discuss work in the CU Anschutz Center for Personalized Medicine that brings genetics to the point of care.

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2023 Seminar Series

Translating Single Cell Genomics for use in Patients after Blood and Marrow Transplantation Archived

  • When: November 2, 2023
  • Delivery: Online
  • Presented By: Scott Furlan (Fred Hutchinson Cancer Center)
  • In this seminar, Dr. Furlan will share data using single cell genomic technologies after hematopoietic cell transplantation including the molecular approaches and computational tools they have used and developed as they relate to this field.

    Meeting number:
    2302 366 1547
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CANCELLED EVENT: Precisely Practicing Medicine from 700 Trillion Points of Data Archived

  • When: October 5, 2023
  • Delivery: Online
  • Presented By: Atul Butte, MD (UCSF)
  • There is an urgent need to take what we have learned in our new data-driven era of medicine, and use it to create a new system of precision medicine, delivering the best, safest, cost-effective preventative or therapeutic intervention at the right time, for the right patients.  Dr. Butte's teams at the University of California build and apply tools that convert trillions of points of molecular, clinical, and epidemiological data -- measured by researchers and clinicians over the past decade and now commonly termed “big data” -- into diagnostics, therapeutics, and new insights into disease.  Dr. Butte, a computer scientist and pediatrician, will highlight his center’s recent work on integrating electronic health records data from over 8 million patients across the entire University of California, and how analytics on this “real world data” can lead to new evidence for drug efficacy, new savings from better medication choices, and new methods to teach intelligence – real and artificial – to more precisely practice medicine.

     
     
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Hematopoietic stem cell-intrinsic and -extrinsic contribution to aging and clonal hematopoiesis Archived

  • When: September 14, 2023
  • Delivery: Online
  • Presented By: Jennifer Trowbridge (The Jackson Lab)
  • While there is a positive correlation between cancer and aging, the mechanisms underlying this relationship remain unclear. Clonal hematopoiesis, a benign condition that is both associated with aging and predisposes to increased risk of development of blood cancers, presents an opportunity to understand the connection between cancer and aging. This seminar will discuss emerging discoveries of mechanisms acting within the hematopoietic stem cells as well as alterations in the bone marrow microenvironment that promote clonal hematopoiesis and transformation to blood cancers.

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The Power of Connection: How the Cancer Research Data Commons enables researchers to connect data, computational tools, and collaborators to accelerate discovery Archived

  • When: May 4, 2023
  • Delivery: Online
  • Presented By: Brandi Davis-Dusenbery (Velsera)
  • The National Cancer Insitute (NCI) Cancer Research Data Commons (CRDC) includes petabytes of genomic, proteomic, imaging and other data that can be immediately accessed and analyzed by approved users in a secure cloud environment. In this webinar, attendees will learn how the CRDC is transforming cancer research by streamlining collaboration, democratizing access to data and increasing accessibility of complex computational algorithms. We will include a live demonstration of the Seven Bridges Cancer Genomics cloud as well as case studies of research performed in the CRDC. 
     
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AI Models of Cancer in Precision Medicine: Trey Ideker Archived

  • When: March 30, 2023
  • Delivery: Online
  • Presented By: Trey Ideker (UCSD)
  • AI Models of Cancer and Precision Medicine: Building a Mind for Cancer

    The long-term objective of the Ideker Lab is to create artificially intelligent, mechanistic models of cancer and neurodegenerative diseases for translation of patient data to precision diagnosis and treatment. We seek to advance this goal by addressing fundamental questions in the field: What are the genetic and molecular networks that promote disease, and how do we best chart these? How do we use knowledge of these networks in intelligent systems for predicting the effects of genotype on phenotype? – Ideker Lab, https://idekerlab.ucsd.edu/research/cancer/

    Meeting number:
    2301 489 7073
    Password:
    JVmmuxM*744
    Host key:
    809371
    Cohost:
    Alex Emmons; Amy Stonelake; Desiree Tillo; Peter Fitzgerald; Joe Wu; Carl McIntosh
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    This webinar will be recorded and made available on the BTEP web site: https://bioinformatics.ccr.cancer.gov/btep/btep-video-archive-of-past-classes/ within 48 hours after the event ends. 

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2022 Seminar Series

A 500 Year Plan for Genetics, Epigenetics and Cell Engineering Archived

  • When: September 22, 2022
  • Delivery: Online
  • Presented By: Christopher Mason (Weill Cornell Medicine)
  • The avalanche of easy-to-create genomics data has impacted almost all areas of medicine and science, from cancer patients and microbial diagnostics to molecular monitoring for astronauts in space. In this lecture, new discoveries from RNA- and DNA-sequencing with the FDA’s SEQC study show the ability of single-molecule methods to reveal rare alleles and provide more comprehensive epigenomics maps of patients and cancers. Also, recent technologies and algorithms from our laboratory and others demonstrate that an integrative, cross-kingdom view of patients (precision metagenomics) holds unprecedented biomedical potential to discern risk, improve diagnostic accuracy, and to map both genetic and epigenetic states, as well as clonal changes in mutations with clonal hematopoiesis. Finally, these methods and molecular tools work together to guide comprehensive, longitudinal, multi-omic views of human astronaut physiology and biology in the NASA Twins Study and several other missions with SpaceX and Axiom, which lay the foundation for future, long-duration spaceflight, including sequencing, quantifying, and engineering genomes to survive on other planets over the next 500 years (https://mitpress.mit.edu/books/next-500-years).

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Decoding Breast Cancer Progression with Single Cell Genomics Archived

  • When: July 14, 2022
  • Delivery: Online
  • Presented By: Nicholas Navin (MD Anderson Cancer Center)
  • The efforts of our laboratory are split evenly between experimental and computational biology.  We develop new experimental methods to sequence single cells and isolate rare subpopulations and develop new analytical approaches to detect variants and apply statistical methods to these data sets.  We focus mainly on breast cancer to understand the role of clonal diversity in the evolution of invasion, metastasis and response to chemotherapy.  We are also using these tools to study rare tumor cell subpopulations including circulating tumor cells and cancer stem cells.  Our goal is to understand the role of clonal diversity in tumor evolution so that we can exploit this diversity for therapeutic vulnerabilities and improve diagnostic tools and the early detection of cancer.  We fully expect that applying these tools to human patients will lead to reduced morbidity in breast cancer.

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Mapping the Human Body One Cell at a Time Archived

  • When: June 16, 2022
  • Delivery: Online
  • Presented By:
  • Sarah Teichmann is co-founder and principal leader of the Human Cell Atlas (HCA) international consortium. The International Human Cell Atlas initiative aims to create comprehensive reference maps of all human cells to further understand health and disease.

    The 37 trillion cells of the human body have a remarkable array of specialized functions, and must cooperate and collaborate in time and space to construct a functioning human. In this talk I will describe my lab’s efforts to understand this cellular diversity through a programme of cell atlasing. Harnessing cutting edge single cell genomics, imaging and computational technologies, we investigate development, homeostasis and disease states, at scale and in 3D, with a particular focus on immunity. I will illustrate the relevance of cell atlas-ing for engineering organoids and regenerative medicine, and will share new results providing insights into pacemaker cells from the sinoatrial node of this heart. Overall I hope to illustrate the power of single cell approaches in unlocking fundamental knowledge about the human body.

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Realizing Data Interoperability Across Basic Research, Clinical Care, and Patients Archived

  • When: April 21, 2022
  • Delivery: Online
  • Presented By: Melissa Haendel (CU Anschutz)
  • Making data reusable for discovery and shared analytics across domains is a laborious, specific-skill requiring task that most data providers do not have the resources, expertise, or perspective to perform. Equally challenged are the data re-users, who function in a landscape of bespoke schemas, formats, and coding – when they can get past understanding the licensing and access control issues. Making the most of our collective data requires partnerships between basic researchers, clinicians, patients, and informaticians, as well as sophisticated strategies to address a myriad of interoperability issues. This talk will review different communities endeavors towards these ends from across the translational spectrum.

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Integrated Analysis of Single Cell Data Across Technologies and Modalities Archived

  • When: February 17, 2022
  • Delivery: Online
  • Presented By: Rahul Satija (NYU)
  • Our goal is to understand how cellular heterogeneity encodes the molecular structure, function, and regulation of complex biological systems. Primarily using single cell genomics, we analyze systems by profiling their most fundamental units individually – a ‘bottom-up’ approach that allows us to study how diverse groups of cells work together to drive biological processes and behaviors. – Satija Lab

    Since Dr. Satija will be presenting unpublished work in this webinar, it will not be recorded or distributed.

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2023 Seminar Series

Whole Embryo Developmental Genetics at Single Cell Resolution Archived

  • When: September 28, 2023
  • Delivery: Online
  • Presented By: Cole Trapnell (Univ. of Washington)
  • The Trapnell Lab at the University of Washington's Department of Genome Sciences studies how genomes encode the program of vertebrate development and how that program goes awry in disease. We build new tools, technologies, and software for decoding this program from large-scale single-cell experiments.

    Meeting number:
    2305 942 7068
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Single Cell Annotation with SingleR: Macrophage-fibroblast crosstalk in lung fibrosis Archived

  • When: June 22, 2023
  • Delivery: Online
  • Presented By: Mallar Bhattacharya, M.D. (UCSF)
  • The Bhattacharya Lab at the UCSF Parnassus Campus is focused on the functional role of monocyte-derived macrophages in the onset and persistence of fibrosis in the lung. We are addressing the following major questions, with a goal of discovering new targets for therapy for acute lung injury and fibrosis:

    • What molecules released by monocyte-derived macrophages and other immune cells signal to and activate pro-fibrotic programs in parenchymal cell types such as fibroblasts and epithelial cells?
    • What reciprocal signals derive from these parenchymal cells to modify the immune response?
    • How can this pathologic crosstalk be reversed to combat fibrosis and restore lung health?
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CellTypist v2.0: Automatic Cell Type Harmonization and Integration in Single Cell Data Archived

  • When: June 1, 2023
  • Delivery: Online
  • Presented By: Chuan Xu, Ph.D. (Teichmann Lab)
  • 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.

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Learning and Transferring Cellular State in Single Cell Atlases Archived

  • When: May 25, 2023
  • Delivery: Online
  • Presented By: Fabian Theis (Helmholtz Munich)
  • Single-cell technologies, such as single-cell RNA sequencing (scRNA-seq), have increased the resolution achieved in the study of cellular phenotypes, allowing measurements of thousands of different genes in thousands of individual cells. This has created an opportunity to begin understanding the dynamics of the prime biological processes undergone by cells, while requiring unique computational tools. In our lab, we develop novel and innovative computational methods for single-cell data analysis. - Theis Lab

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Rahul Satija: (Azimuth) Annotation of Cell Types in Single Cell Analysis of Cancer Archived

  • When: April 6, 2023
  • Delivery: Online
  • Presented By: Rahul Satija (NYU)
  • Azimuth is a web application that uses an annotated reference dataset to automate the processing, analysis, and interpretation of a new single-cell RNA-seq experiment. Azimuth leverages a 'reference-based mapping' pipeline that inputs a counts matrix of gene expression in single cells, and performs normalization, visualization, cell annotation, and differential expression (biomarker discovery). All results can be explored within the app, and easily downloaded for additional downstream analysis. - Satija Lab

    The development of Azimuth is led by the New York Genome Center Mapping Component as part of the NIH Human Biomolecular Atlas Project (HuBMAP).

    This webinar will be recorded and made available on the BTEP web site: https://bioinformatics.ccr.cancer.gov/btep/btep-video-archive-of-past-classes/ within 48 hours after the event ends. 

    Join information

    Meeting link:
    https://cbiit.webex.com/cbiit/j.php?MTID=m1ff4bc9a56dbdc18375eecaed1c280fb 
     
    Meeting number:
    2304 561 2241
    Password:
    JXrwyY4j85@
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    183061
    Cohost:
    Alex Emmons; Amy Stonelake; Desiree Tillo; Peter Fitzgerald; Joe Wu; Carl McIntosh
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2024 Seminar Series

Version control with Git

  • When: May 23, 2024
  • Delivery: Online
  • Presented By: Desiree Tillo (GAU, BTEP)
  • Versioning enables researchers to track changes in coding projects. This Coding Club introduces Git (https://git-scm.com), an open-source software used to perform versioning on a personal computer. At the end of this class, participants will:

    • Understand the importance of versioning
    • Describe Git
    • Know how to access Git
      • Be aware of resources that helps with Git installation on personal computer
      • Be aware of the availability of Git on Biowulf, the NIH high performance computing system
    • Define repository
    • Know the steps involved in the versioning process including
      • Initiating a new repository
      • Understanding the difference between tracked and untracked files
      • Excluding files from being tracked
      • Staging files with changes
      • Commiting changes and writing commit messages
      • Viewing commit logs
    • Compare between versions of code
    • Revert to a previous version of code
    Meeting link:
    https://cbiit.webex.com/cbiit/j.php?MTID=m8d56b3aff91ddd2e6df839d05dda6a8f
     
    Meeting number:
    2319 013 9531
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An Introduction to DAVID for Functional Enrichment Analysis Archived

  • When: March 27, 2024
  • Delivery: Online
  • Presented By: Brad Sherman, Weizhong Chang
  • 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.  In this BTEP Coding Club session, developers from DAVID (Weizhong Chang and Brad Sherman) will give an overview of DAVID and provide training on key tools including functional annotation tools (table, chart, and clustering), gene functional classification, gene ID conversion, gene name batch viewer, and the newly developed ortholog conversion tool.

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Version control using Git (Cancelled) Archived

  • When: February 28, 2024
  • Delivery: Online
  • Presented By: Joe Wu (BTEP)
  • Versioning enables researchers to track changes in coding projects. This Coding Club session will introduce Git (https://git-scm.com), an open-source software used to perform versioning locally and enables users to upload code to web repositories such as GitHub. At the end of this class, participants will

    • Be able to describe Git
    • Be able to use Git to
      • Create coding projects 
      • Save and track changes to code
      • Upload code to GitHub
      • Revert to/view previous versions of code
      • Perform basic collaboration tasks

     

    Installation of software is not needed to participate.

    Meeting information:

    Meeting link:
    https://cbiit.webex.com/cbiit/j.php?MTID=meadb08ed71552393fe486073a7a7ffc5 
    Meeting number:
    2308 646 3414
    Password:
    VRjdm9A5y$4

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Version control using Github Archived

  • When: February 21, 2024
  • Delivery: Online
  • Presented By: Joe Wu (BTEP), Nadim Rizk (CBIIT)
  • Versioning enables researchers to track changes in coding projects. This Coding Club session will introduce the versioning tool GitHub (https://github.com). At the end of this class, participants will

    • Become familiar with options available for using GitHub at NCI
    • Be able to use GitHub to
      • Create coding projects 
      • Track changes in code
      • Revert to a previous version of code
      • Collaborate with the project team

     

    Installation of software is not needed to participate.

    This class will be followed by one addressing versioning using Git on February 28, 2024 from 11 AM to 12 PM. See https://bioinformatics.ccr.cancer.gov/btep/classes/version-control-using-git for information and registration.

    Meeting information:

    Meeting link:
    https://cbiit.webex.com/cbiit/j.php?MTID=meadb08ed71552393fe486073a7a7ffc5 
    Meeting number:
    2308 646 3414
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Documenting Your Analysis with Quarto Archived

  • When: January 24, 2024
  • Delivery: Online
  • Presented By: Alex Emmons (BTEP)
  • Documenting your data analysis is a crucial step toward making your research reproducible. In this session of the BTEP Coding Club, we will learn how to get started using Quarto with RStudio for report generation. 

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2023 Seminar Series

Creating R / Python templates for the NIH Integrated Data Analysis Platform (NIDAP) Archived

  • When: December 6, 2023
  • Delivery: Online
  • Presented By: Alexei Lobanov (CCBR)
  • NIDAP, the NIH Integrated Data Analysis Platform, is a cloud-based and collaborative data aggregation and analysis platform. The NIDAP platform hosts user-friendly bioinformatics workflows (Bulk RNA-Seq, scRNA-Seq, Digital Spatial Profiling) and other component analysis and visualization tools that have been created and maintained by the NCI developer community based on open-source tools.
     
    In this BTEP Coding Club session, Alexei Lobanov, bioinformatics analyst with CCBR, will demonstrate how to create NIDAP templates, GUI-like environments that allow users to run the same code on new datasets using a point-and-click approach, from source code (R or python).
     
    Why create a NIDAP template? 1) “Templatizing” your code is easy and allows users / collaborators with no coding skills to efficiently use your code. 2) Pre-made templates encourage efficiency and reproducibility. Templates allow the user to easily create custom workflows and pipelines that can be shared with collaborators and/or applied to future data sets.
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Visualizing multi-dimensional omics data with circular plots in R package OmicCircos Archived

  • When: November 15, 2023
  • Delivery: Online
  • Presented By: Chunhua Yan (CBIIT CGBB), Ying Hu (CBIIT CGBB)
  • This session introduces two versions of the R/ Bioconductor package OmicCircos to generate high-quality circular plots for visualizing multi-dimensional omics data:

    1. coding in the R environment for programmers;
    2. point-and-click OmicCircos R Shiny app on the Cancer Genomics Cloud (CGC) for non-programmers. 

     

    Meeting number:2310 050 3184

    Password:3sfNDMBq*66

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Accessing data from and Submitting data to the Gene Expression Omnibus (GEO) Archived

  • When: October 18, 2023
  • Delivery: Online
  • Presented By: Joshua Meyer (CCBR)
  • This October session of the BTEP Coding club will feature a tutorial on how to access data from GEO as well as how to submit data to GEO. 

     

     


Using rMATS for differential alternative splicing detection Archived

  • When: September 20, 2023
  • Delivery: Online
  • Presented By: Alexei Lobanov (CCBR)
  • This session of the BTEP Coding Club will focus on the tool rMATS for differential alternative splicing event detection from RNA-Seq data. This 1-hour demo will provide a detailed overview of rMATS including why you may want to use it, how to use it, and how to interpret and further use resulting outputs. 

    https://rnaseq-mats.sourceforge.io/

    Multivariate Analysis of Transcript Splicing (MATS)

    MATS is a computational tool to detect differential alternative splicing events from RNA-Seq data. The statistical model of MATS calculates the P-value and false discovery rate that the difference in the isoform ratio of a gene between two conditions exceeds a given user-defined threshold. From the RNA-Seq data, MATS can automatically detect and analyze alternative splicing events corresponding to all major types of alternative splicing patterns. MATS handles replicate RNA-Seq data from both paired and unpaired study design.


Using EnhancedVolcano and ComplexHeatmap to visualize -omics data Archived

  • When: August 16, 2023
  • Delivery: Online
  • Presented By: Joe Wu (BTEP)
  • Heatmaps and volcano plots are common data visualizations in bioinformatic analyses of genomic data, such as bulk RNA-seq. While both plot types can be used to visualize gene expression, heatmaps can be used to examine expression data across samples, and in combination with clustering techniques, reveal potential patterns in the data. Volcano plots demonstrate the direction, distribution, and statistical significance of gene expression between experimental conditions (example tumor vs. non-tumor, or drug treated vs. non-treated). In this coding club, we will demonstrate how to construct these plots using the R/Bioconductor tools ComplexHeatmap and EnhancedVolcano.

     

     


A Beginners Guide to Troubleshooting R Code Archived

  • When: July 19, 2023
  • Delivery: Online
  • Presented By: Alex Emmons (BTEP)
  • This session of the BTEP Coding Club will focus on strategies for overcoming errors, warnings, and other common problems with R code. In this 1-hour tutorial targeting beginner R users, we will discuss commonly observed errors, how to find help, and how to approach and debug R code. 


BTEP Coding Club: Submitting Scripts to the Biowulf Batch System Archived

  • When: June 21, 2023
  • Delivery: Online
  • Presented By: Joe Wu (BTEP)
  • Biowulf is the high-performance computing cluster (HPC) at NIH. In addition to its vast compute power, Biowulf has hundreds of bioinformatics tools and databases for analyzing Next Generation Sequencing (NGS) data. This coding club will provide participants the foundations for harnessing Biowulf’s computing power to analyze NGS data. Participants will learn to request computing resources on and to submit scripts to the Biowulf system. This class is not hands-on so no need to obtain a Biowulf account prior to attending.

     

    Meeting link:
    https://cbiit.webex.com/cbiit/j.php?MTID=m39e6aa973e1500fbac8d3516e23cfaf8


    Meeting number:
    2317 419 7733
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    Access code: 2317 419 7733
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Functional Enrichment Analysis with clusterProfiler Archived

  • When: May 17, 2023
  • Delivery: Online
  • Presented By: Alex Emmons (BTEP)
  • Functional enrichment analysis is used to understand the biological context of gene lists or differential expression results. There are a multitude of tools available for this purpose. clusterProfiler is a popular R / Bioconductor package supporting over-representation analysis (ORA) and gene set enrichment analysis (GSEA) using up-to-date biological knowledge of genes and biological processes (GO and KEGG) and support for thousands of organisms. The latest version of clusterProfiler (v. 4.6.2) also provides a tidy interface for visualizing resulting output.

    This May 2023 session of the BTEP Coding Club will provide an overview and demo of many of the key features of the clusterProfiler R package. 


Documenting Data Analysis with Jupyter Lab Archived

  • When: April 19, 2023
  • Delivery: Online
  • Presented By: Joe Wu (BTEP)
  • This BTEP coding club will introduce beginners to Jupyter Notebook, a platform to organize code and analysis steps in one place. Jupyter Notebook can be easily installed or run in a web browser, and supports several languages such as R and Python. It provides a way to keep track of all steps in an analysis and a place for collaboration. Come learn what Jupyter Notebook can do for you. This class will not be hands-on so need to install anything to attend.


VLOOKUP in excel and the R programming equivalent Archived

  • When: March 15, 2023
  • Delivery: Online
  • Presented By: Alex Emmons (BTEP)
  • Do you use excel's VLOOKUP function often to merge tables or search for subsets of data in large NGS data files? If so, you may be interested in a more programmatic solution. Join us for a lesson on performing VLOOKUP in excel followed by a more reproducible solution with R programming. Whether you are interested in merging a list of gene ids with a table of functional annotations or searching for unique matches of known T-Cell Receptor sequences among output from a 10X TCR sequencing run, this tutorial will likely be useful to you.  

    This tutorial will kick off the BTEP Coding Club, which features monthly 1-hour tutorials of bioinformatics tools, software, or skills. Email us at ncibtep@nih.gov if you would like to see a topic featured by the BTEP Coding Club. 

2024 Seminar Series

Faraz Faghri

  • When: June 27, 2024
  • Delivery: Online
  • Presented By: Faraz Fahri, Ph.D. (CARD)
  • CARD is a collaborative initiative of the National Institute on Aging and the National Institute of Neurological Disorders and Stroke that supports basic, translational, and clinical research on Alzheimer’s disease and related dementias. CARD’s central mission is to initiate, stimulate, accelerate, and support research that will lead to the development of improved treatments and preventions for these diseases.

    Alternative Meeting Information: 
    Meeting number:
    2310 497 7985
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Kerry Goetz, Ph.D.

  • When: July 25, 2024
  • Delivery: Online
  • Presented By: Kerry Goetz, Ph.D., (NEI)
  • Kerry Goetz, Ph.D.

    Meeting number:
    2302 034 0947
    Password:
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AI: Baris Turkbey - AIR

  • When: September 26, 2024
  • Delivery: Online
  • Presented By: Ismail Baris Turkbey, M.D. (NCI CCR AIR)
  • The goal of Artificial Intelligence Resource (AIR) is to make AI tools available to Center for Cancer Research (CCR) investigators. The strength of AI is that algorithms can be trained to seek specific information that may be scientifically or clinically important.  AIR will mainly focus on “Computer Vision” which analyzes medical images, such as radiologic, digital pathology, video/endoscopy, and optical imaging among others.  Examples of potential projects include developing better screening, detection methods or predictive markers, or improving procedures among many others. Both clinical and laboratory-based imaging projects will be considered. Please refer to our ongoing projects and prior publications for more information.

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David Reif, Ph.D.

  • When: November 14, 2024
  • Delivery: Online
  • Presented By: David Reif, Ph.D. (NIEHS)
  • David M. Reif, Ph.D., joined the NIEHS in 2022 as Chief of the Predictive Toxicology Branch (PTB) in the Division of Translational Toxicology (DTT). In this role, he will leverage expertise of the branch in data science, toxicogenomics, spatiotemporal exposures and toxicology, computational methods development, and new approach methods (NAMs) to advance predictive toxicology applications with partners across NIEHS, the interagency Tox21 Program and the Interagency Coordinating Committee on the Validation of Alternative Methods (ICCVAM).

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Transforming Medicine with AI: From TrialGPT to GeneAgent Archived

  • When: May 2, 2024
  • Delivery: Online
  • Presented By: Dr. Zhiyong Lu (NCBI)
  • The explosion of biomedical big data and information in the past decade or so has created new opportunities for discoveries to improve the treatment and prevention of human diseases. As such, the field of medicine is undergoing a paradigm shift driven by AI-powered analytical solutions. This talk explores the benefits (and risks) of AI and ChatGPT, highlighting their pivotal roles in revolutionizing biomedical discovery, patient care, diagnosis, treatment, and medical research. By demonstrating their uses in some real-world applications such as improving biomedical literature searches (Nature Biotechnology 2018; Nature 2020; Nature Genetics 2023), accelerating patient trial matching (TrialGPT, in collaboration with NCI clinicians), and assisting gene set analysis (GeneAgent, in collaboration with NCI researchers), we underscore the potential of AI and ChatGPT in enhancing clinical decision-making, personalizing patient experiences, and accelerating knowledge discovery.

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Explainable Artificial Intelligence (XAI) and Single Cell Genomics to Understand the Cellular Complexity of the Human Brain Archived

  • When: April 4, 2024
  • Delivery: Online
  • Presented By: Richard Scheuermann, Ph.D. (NLM)
  • Although generative artificial intelligence (AI), a’la ChatGPT, is receiving a lot of “attention” these days, there are many other options for using AI to support biomedical research.  In order to help analyze and interpret single cell genomics data, we have found that AI approaches that retain “explainability” are especially useful in providing functional insights into the underlying biological systems being studied, in this case, the human brain.

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How Large Language Models (LLMs) Accelerate Data Discovery and Harmonization Archived

  • When: March 21, 2024
  • Delivery: Online
  • Presented By: Mike Nalls Ph.D. (CARD)
  • Context-aware AI implemented to facilitate data discovery and harmonization has significantly accelerated some of the common bottlenecks in the collaborative research process. Pilot work has shows major time and cost savings compared to current completely manual processes.

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Artificial Intelligence in the Biomedical Sciences Archived

  • When: February 29, 2024
  • Delivery: Online
  • Presented By: Brian Ondov, Ph.D. (NLM)
  • Artificial Intelligence (AI) is becoming increasingly ubiquitous in biomedical research, enabled by large datasets, new algorithms, and hardware improvements. In this session, Dr. Brian Ondov will introduce the basic principles of AI and describe how its various forms can help researchers in different ways, including image classification, sequence-based prediction, generative models, and language understanding. 

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2024 Seminar Series

The CCBR Single-cell RNA-seq Workflow on NIDAP

  • When: May 29, 2024
  • Delivery: Online
  • Presented By: Joshua Meyer (CCBR)
  • This talk will cover a scRNA-seq workflow available to NCI researchers on NIDAP. NIDAP, the NIH Integrated Data Analysis Platform, is a cloud-based and collaborative data aggregation and analysis platform that hosts user-friendly bioinformatics workflows. This platform allows researchers to use many of the open-source tools discussed in this seminar series without necessitating coding experience. This seminar will focus on the capabilities of this workflow for QC, annotation, and visualization of single-cell RNA-seq data.


Differential Expression Analysis with Seurat Archived

  • When: May 22, 2024
  • Delivery: Online
  • Presented By: Nathan Wong (CCBR)
  • This seminar provides an overview of differential expression testing with Seurat. Topics to be covered include preparing data for differential gene expression, differential gene analysis between specific groups, differential gene analysis for cluster classification, SingleR for cell type annotation, and visualizing genes of interest.  

     

     


Getting Started with Seurat: QC to Clustering Archived

  • When: May 1, 2024
  • Delivery: Online
  • Presented By: Alex Emmons (BTEP)
  • This lesson reviews many of the standard steps in a scRNA-Seq workflow: QC filtering, normalization, scaling, and clustering. 


Introduction to scRNA-Seq with R (Seurat) Archived

  • When: April 24, 2024
  • Delivery: Online
  • Presented By: Alex Emmons (BTEP)
  • This seminar provides an introduction to R in the context of single cell RNA-Seq analysis with Seurat.  In this seminar, attendees will learn about options for analyzing scRNA-Seq data, resources for learning R, how to import scRNA-Seq data, and how to create, examine, and access data stored in a Seurat object.  


SCAF: Overview of Cell Ranger output files and single cell data analysis quality control Archived

  • When: April 17, 2024
  • Delivery: Online
  • Presented By: Kimia Dadkhah (SCAF)
  • Kimia Dadkhah, bioinformatics analyst (SCAF), will talk about Cell Ranger output and essential quality control metrics in single cell data analysis, how to interpret these and make informed decisions, and other considerations to keep in mind when assessing the quality of returned data from SCAF.  


Introduction to single cell RNA-Seq Archived

  • When: April 10, 2024
  • Delivery: Online
  • Presented By: Charlie Seibert, Saeed Yadranji Aghdam
  • Single cell RNA sequencing (scRNA-Seq) is becoming increasingly more common in biomedical research, but what is scRNA-Seq? How does it differ from other transcriptomic approaches (e.g., bulk RNA-Seq), and what are the potential applications, technologies, and workflows? This presentation will introduce learners to scRNA-Seq, answering the above and touching on additional topics such as methodological challenges, concerns, and best practices.  


The CCR Single Cell Analysis Facility (SCAF): An Overview Archived

  • When: April 3, 2024
  • Delivery: Online
  • Presented By: Mike Kelly (SCAF)
  • The Single Cell Analysis Facility (SCAF) is a CCR facility dedicated to the application of single-cell technologies in cancer research. Based on the NIH Bethesda main campus, SCAF aims to provide the broadest range of project support from consultation on experimental design, sequencing, and data analysis. Learn more about SCAF and the single-cell genomics technologies available to CCR investigators in this overview presentation.