Course Details

  • Date: May 22nd, 2017 - May 23rd, 2017
  • Time: 9:30 am - 4:00 pm
  • Location: Bldg 10 FAES room 4 (B1C205)
  • Presenter(s): Matthew Wampole (Clarivate Analytics), Michael Ryan (Johns Hopkins/InSilico Solutions/MDACC)
Driven by the decreasing costs and increasing performance of next-generation sequencing (NGS) technologies, the amount of available genomic data has grown exponentially in recent years.  While most of the analyses of these data is done computationally, there are many instances where visual inspection of the original and/or processed data is invaluable. Such direct visualization can provide: “sanity checks” on computational results; novel biological insights; aid in communicating results; and a better understanding of the interplay between spatially related biological elements. These visualization, pathways and enrichment analysis tools are relevant whether one is interested in expression analysis (RNA-Seq), variant detection (Exome-Seq), protein binding (ChIP-Seq), or any other genome scale data.

NOTE: This is a BYOC (Bring your own laptop Computer) class. Government issued or personal computers are permitted. We will be able to supply a very limited set of computers, so if you want to take the class but cannot bring your own computer please indicate such in the Comment section on the registration form. Please also review the software requirements and instructions provided below.

  • Registration is required. Important: Registration will close on Thursday, May 18th at 5:00 pm.
  • Note: On the registration page, you have the option to (a) attend all four sessions, or (b) select the session/s that you would like to attend. Please choose carefully and only if you are committed to attending the session/s.
Software requirements and instructions for hands-on training on the respective applications:
  • Preferred browsers are Chrome, Firefox, or Safari for all sessions. Internet Explorer (IE) will not be compatible with most of these analysis tools.
  • Please bring your PIV cards (and card readers) in order to set up VPN or access to NIH Wireless in the Building 10 FAES classroom.
  • For the Ingenuity Pathway Analysis (IPA) session, please make sure you have an active account and the application opens up succesfully on your computer prior to the workshop. Kindy submit a request to NCI IT ( for accessing this software through the NIH institutional license. Review the instructions provided in the PDF file under Course Material1 below. Additionally, please make sure your computer meets our specifications for running IPA, as described here:
  • For the MetaCore session, please make sure that you have an active account and that the web-based application opens up correcetly on your computer browser. Kindy submit a request to NCI IT ( for setting up an account to access this software through the NIH institutional license. If any issues arise, please send an email to Maria Ryan – Additionally, please download the training files under Course Materials2 below.
  • Training accounts for the open-source tools (CRAVAT, MuPIT, and NG-CHM) will be provided at the workshop
  • For QluCore Omics Explorer (QOE) – please click this link: After registering on their website, please download the appropriate (Windows or Mac) QOE Trial Software onto your computer. You will need administrative privileges on the computer, so please submit a request to IT to complete the installation if necessary. Once installed, access can be activated by using the trial license file (.lic) that is contained within the file provided under Course Materials3 below. That unzipped folder also contains training files required for the workshop.


Day 1 – Monday, May 22, 2017

9:30 – 10:00 am                      Introduction to Workshop Concepts and Sessions
                                               Presenter: Anand S. Merchant, MD, PhD
10:00 am – 12:30 pm             MetaCore
                                              Presenter: Matthew Wampole, PhD
MetaCore™ is an integrated curated knowledge database and software suite for pathway analysis of experimental data and gene lists. The scope of data types includes microarray and sequence-based gene expression, SNPs and CGH arrays, RNAi screens, gene variants, proteomics, metabolomics, Co-IP pull-out and other custom interactions which can all by analyzed in tandem. In this session, we’ll be analyzing data published recently in PNAS about NOTCH1 signaling in chronic lymphocytic leukemia ( From this publication, we’ll explore what pathways are enriched by up regulated genes by ICN1-HA from RNA-seq and bound to NOTCH1 in CHiP-seq experiments. Use overconnectivity analysis to associate transcription factors with the regulation of these upregulated genes.  Compare RNA-seq expression data chronic lymphocytic leukemia cells derived from patients with and without NOTCH1 mutations and expression. Finally, we’ll use the ICN1-HA induced up-regulated gene signature to compare against publically available GEO microarray data to find similar signatures in other diseases.
12:30 – 1:00 pm                    LUNCH BREAK
1:00 –  4:00 pm                     QluCore Omics Explorer
                                              Presenter: Carl-Johan Ivarsson, PhD
This session will include introduction to and exercises on basic features and functionality in Qlucore Omics Explorer. It is intended for new users and does not require that you have previous experience with Qlucore Omics Explorer. After the training you should be able to do the following using Qlucore Omics Explorer:
  • Import data and annotations
  • Present data with different plot types (PCA, heatmap, bar, box…)
  • Identify discriminating variables using basic statistical test
  • Use visualization to enhance analysis and interpret results
  • Explore large data sets – find structure, patterns and subclusters in data
  • Export variable lists and images

Day 2 – Tuesday, May 23, 2017

9:30 am – 12:30 pm             Open-Source Tools for Analysis and Visualization of NGS Data (CRAVAT, MuPIT, and NG-CHM)
                                             Presenter: Michael Ryan, PhD, Johns Hopkins/MD Anderson/ In Silico Solutions
Cancer-Related Analysis of VAriants Toolkit, or CRAVAT (, is a free tool for high-throughput analysis of human sequencing variants developed by the Karchin lab at Johns Hopkins and In Silico Solutions.  CRAVAT accepts very large variant data files containing single nucleotide substitutions as well as indels and returns a wide variety of annotations and scores that help with identification and exploration of important variants.  The workshop will provide some background on CRAVAT and lots of hands-on exercises to learn how to use the tool and interpret the results.
Mutation Position Imaging Toolbox, or MuPIT (www.mupit.icm.jhu/MuPIT_Interactive/), is a sister tool to CRAVAT that shows human mutations on 3D protein structures.  MuPIT analysis enables identification of mutational clusters and proximity to functional domains in 3D space that are not obvious from the linear protein sequence. The focus of the workshop will be a series of exercises to learn how to visualize your mutations in MuPIT, how CRAVAT and MuPIT are integrated, and how to manipulate, investigate, and understand the results.
Next Generation Clustered Heat Maps, or NG-CHM(, is a tool developed by MD Anderson and In Silico Solutions to build clustered heat maps for genomic data. It provides interactive heat maps that enable the user to zoom and pan across the heat map, alter its color scheme, generate production quality PDFs, and link out from rows, columns, and individual heat map entries to related statistics, databases and other information.

12:30 – 1:00 pm                    LUNCH BREAK
1:00 –  4:00 pm                     Ingenuity Pathway Analysis (IPA)
                                              Presenter: Jennifer Poitras, PhD
In this session, you will get an opportunity to use IPA for maximizing the biological interpretation of gene, transcript & protein expression data using different modules of the tool. There will hands-on exercises from file uploading to interpreting results, visualizing and integrating multi-omics data, understanding and mining the Ingenuity Knowledge Base (IKB), core analysis, causal networks, and many more new functionalities.