Analyzing ChIP-Seq Data using Galaxy

This practical, hands-on tutorial is designed to give participants experience with ChIP-Seq data analysis using the Galaxy platform. The analysis in this tutorial is typical of experiments using ChIP-Seq data to identify transcription factor binding sites in eukaryotic, high quality genomes.

Digital Gene Expression (DGE) Analysis Using Galaxy, Human Data

This is a practical, hands-on tutorial designed to give participants experience with RNA-Seq data analysis using Tophat, Cufflinks, and CummRbund in Galaxy. The analysis in this tutorial is typical of experiments in eukaryotic species with high-quality genomes and genome annotation available. Participants are expected to be familiar with next-generation sequence data, basic theory of RNA-Seq, and Galaxy. Participants do not need previous experience with Tophat, Cufflinks, or CummRbund.

Python for Scientific Computing

Python is a modern general purpose programming language that is popular in scientific computing for its readable syntax and extremely rich ecosystem of scientific and mathematical modules. The morning section will provide an introduction to some widely used packages, including common idioms for manipulating and visualizing data. The afternoon section will cover advanced modules and techniques relevant to high performance computing.

Analyze ChIP-Seq Data at the Command Line

This tutorial is paired with Analyzing ChIP-Seq Data using Galaxy and will take the user though the same steps but, using the command line versions of the tools used in the Galaxy environment. This tutorial will:

1. Provide a brief introduction to MSI systems.

2. Provide a very brief introduction to UNIX.

3. Take users step-by-step though the process needed to analyze ChIP-Seq data

4. Provide users with a basic PBS script to automate the mapping and peak calling.

5. Teach users how to edit and run the script to be used in the future.


This tutorial provides an introduction on how to write a parallel program using OpenMP, and will help researchers write better and more portable parallel codes for shared memory Linux nodes. The course will cover the Compiler Directives (44), Runtime Library Routines (35), and Environment Variables (13) relevant to OpenMP. OpenMP supports C/C++ and Fortran implementations. Examples of how to enable OpenMP on the Intel, GNU, and PGI compilers will be given. The fork-join model of thread parallel execution will be described.

Parallel Computing Overview

This tutorial will help users learn the basics of parallel computation methods, including strategies for collecting calculations together for parallel execution. A brief description of parallel programming using MPI message passing will be given. A brief description of parallel programming using OpenMP will also be given. The hybrid MPI/OpenMP model will be briefly described. This will be a fast crash course on the most basic parallel computation and programming methods. Examples of how to compile and execute simple parallel programs will be given. -- Think Supercomputing In Plain English.

Job Submission and Scheduling

This tutorial will introduce users to MSI supercomputers, and provide an overview of how to submit calculations to the job schedulers. Topics covered include creating job scripts, types of jobs, job queues, differences in available hardware, checking job status, and choosing an appropriate place to submit a calculation.