BTEP Coding Club Seminar Series

This session of the BTEP Coding Club introduces NIH CloudLab, a free 90-day sandbox environment partnered with AWS, Google Cloud, and Azure, and demonstrates how to run Nextflow pipelines, a powerful workflow management system for bioinformatics and data science, on Google Cloud Batch.

ggplot2 is a popular R package for data visualization that uses layers to build high quality plots. There are over 100 packages that extend the functionality of ggplot2. This session of the BTEP Coding Club will focus on the package ggpubr, which facilitates plot customization and statistical integration, making it much easier to create publication ready plots with ggplot2. Specifically, this lesson will demonstrate how to visualize the results of common statistical tests (e.g., t-tests, ANOVA, Pearson correlation).  

Meeting Information:

https://cbiit.webex.com/cbiit/j.php?MTID=md5545c8b063ac2e0996ac7390c1ffc65
Wednesday, November 20, 2024 11:00 AM | 1 hour | (UTC-04:00) Eastern Time (US & Canada)
Meeting number: 2310 921 8299
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In this session of the BTEP Coding Club, Emily Clough, PhD, GEO Curator, will explore updates to analysis tools available within the Gene Expression Omnibus (GEO), a public repository for gene expression and epigenomics data sets. In the past several years GEO has made major updates and additions to the online analysis tool GEO2R. Many new visualization plots have been added to explore results, and now human RNA-seq data are available for analysis.

Meeting link:
https://cbiit.webex.com/cbiit/j.php?MTID=m0b499a1174cc32a9355c87c395b5ac15

Meeting number:
2318 999 6974

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Partek Flow enables scientists to construct analysis workflows for multi-omics sequencing data including DNA, bulk and single cell RNA, spatial transcriptomics, ATAC and ChIP. It is hosted on Biowulf, the NIH high performance computing system and suitable for those with little command line knowledge to conduct analyses through a point-and-click interface utilizing Biowulf’s immense compute power, rather than a personal computer that may not have the power for analyzing large genomic datasets. This Coding Club helps scientists with no or limited experience get started using Partek Flow. Participants will learn to acquire access to, transfer data to, and import data into projects on the NIH Partek Flow server. A Partek Flow account is not required for participation.

Meeting link:
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Meeting number:
2310 377 6819
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The Cancer Genome Atlas (TCGA) was a landmark cancer genomics program that molecularly characterized over 20,000 primary cancer and matched normal samples spanning 33 cancer types. This resulted in a massive open-source dataset that continues to uncover revelations regarding the molecular underpinnings of various cancers. This BTEP Coding Club session demonstrates how to access and download TCGA data from the Genomic Data Commons (GDC).  Other means of accessing, analyzing, and downloading TCGA data will also be discussed.  

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

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.

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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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
Password:
VRjdm9A5y$4

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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. 

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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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. 

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.

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.

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. 

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
Password:
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Host key:
520526

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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. 

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.

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.