Skip to main content
An official website of the United States government
NIH Websites Are Changing
Per Executive Order 14434, federal agencies are now using "Super Intelligence" (SI) in place of "Artificial Intelligence" (AI). You may see both terms across NIH content during this transition.

Email

Training Guide Library

Here at CBIIT, we want to support your data science learning journey because the next generation of cancer researchers have big data problems to solve. Here we list several recordings and resources that our CBIIT staff organized, created, or led. Whether you’re trying to perform multi-omics research, evaluate the use and limitations of super intelligence (SI), or improve your data visuals for a publication, you can use these resources to develop your basic data science skills!

Data Generation and Collection

Identify and gather the data you need to address a problem.

  • Beginner
    • [Video Tutorial] EVS Explore Tutorial: How to Search For Terms | Find out how you can use advanced search capabilities to find common data elements and standards in NCI’s Enterprise Vocabulary Service’s (EVS) Explore tool. | Posted Sept. 22, 2026
    • [Training Video Recording] Genomic Data Commons Data Portal | Watch a tutorial on how this web-based platform allows you to search, analyze, and download data from cancer genomics studies. | Posted Nov. 7, 2024
    • [Training Video Recording] Unlocking Insights from Clinical Notes with the EMERSE Text Processing Tool | Use this tool to identify key data within free-text clinical notes from electronic health records systems. | Recorded Sept. 30, 2024
    • [Training Video Recording] The Cancer Proteome Atlas | Get an introduction to RPPA (a high-throughput, antibody-based technique for protein profiling); receive an overview of the bioinformatics resource, “The Cancer Proteome Atlas” (or TCPA); and learn more about TCPA’s chatbot, “TCPAplus.” | Recorded Sept. 13, 2024
    • [Training Video Recording] GARDE: Open-Source Platform for Population-based Genetic Testing of Hereditary Cancer Syndromes | Learn how to facilitate population-based genetic testing with the GARDE software platform, which harnesses algorithms and chatbots to identify individuals eligible for genetic testing for hereditary cancer syndromes. | Recorded Jul. 25, 2024
    • [Training Video Recording] WebMeV | Receive a demonstration on how this web-based software for genomic data analysis can upload data and perform various analyses such as normalization, clustering, and principal component analysis. | Recorded Apr. 26, 2024

Data Exploration and Analysis

Study your data, then form a hypothesis.

  • Beginner
    • [Training Video Recording] Geneious Prime: A Closer Look | Learn about a powerful collection of tools for transforming raw DNA and protein sequence data into meaningful visualizations. No coding experience necessary. | Recorded Sept. 24, 2026
    • [Training Video Recording] Multiomic Data Analysis with Illumina | Learn about the “Illumina Connected Multiomics” tool and see how it can help you calculate statistics and create interactive visualizations, regardless of your bioinformatics experience level. | Recorded Aug. 13, 2026
    • [Training Video Recording] Unveiling FlowJo Version 11 | Discover FlowJo with a modern language code base. This version makes visual comparisons faster to access, it comes with more built-in automation tools, and it’s built on a foundation compatible with cloud computer. | Recorded Jan. 8, 2026
    • [Training Video Recording] Introduction to FlowJo™ Software | Learn about FlowJo’s workspace—including how to load files, evaluate sample quality, draw gates, and generate tabular and graphical layouts to perform single-cell flow cytometry analysis. | Recorded Sept. 18, 2024
    • [Training Video Recording] An Introduction to Bioconductor for Genomic Data Science | Learn the basics of integrative data containers for genome-scale experiments and components of analytic workflows for transcriptomics and epigenetics. You will also discover resources for annotation of genomic data. | Recorded Aug. 23, 2024
    • [Training Video Recording] RNAseq Data Analysis in Qlucore | Import and analyze RNA-sequencing data in Qlucore Omics Explorer—software that visualizes the data in 3D plots and can help you identify hidden structures and patterns. | Recorded Aug. 14, 2024
    • [Training Video Recording] XNAT | Learn about this open source imaging informatics software platform that enables data ingestion, curation, annotation, quality control, and computational workflows using Docker containers. | Recorded Apr. 22, 2024
  • Advanced

Predictive Modeling

Use computational tools like machine learning models to make predictions with your data.

Data Visualization

Communicate your data findings using interactive images, plots, and charts.

  • Beginner
  • Advanced
    • [Training Video Recording] Data Visualization with R | Learn how to use the ggplot2 package in the programming language R to graph plots that can form the basis of analysis. Note: This video is one of four videos that make up a course series exclusive to NCI staff and provided by the Bioinformatics Training and Education Program. In this recording, R Studio is accessed via Biowulf. | Recorded Jan. 8, 2026
    • [Training Video Recording] Next-Generation Clustered Heat Maps (NG-CHMs) | Learn how NG-CHMs can help you navigate large omic databases, zoom in on patterns, access external metadata resources, produce high-resolution graphics, and save metadata for later use. NG-CHMs play a valuable role in NIH projects, encompassing phenotypic and genotypic data at DNA, RNA, protein, and metabolite levels in bulk and single-cell studies. | Recorded Jun. 20, 2024
    • [Training Video Recording] DNASTAR Lasergene Software | Learn about this software and its applications in molecular biology, including topics such as enzyme labels, primer design, cloning methodologies, and Sanger sequence alignment. | Recorded Jun. 4, 2024

Data Sharing

Accelerate discovery by making your data available to others.

Share Ideas

Help us help you! If you believe content is missing or needs modifying, email NCI CBIIT.

  • Updated:

If you would like to reproduce some or all of this content, see Reuse of NCI Information for guidance about copyright and permissions. In the case of permitted digital reproduction, please credit the National Cancer Institute as the source and link to the original NCI product using the original product's title; e.g., “Training Guide Library was originally published by the National Cancer Institute.”

Email