Data Analysis

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.

Quality Control of Illumina Data at the Command Line

Want to take your analysis to the next level? 

This hands-on tutorial will introduce new bioinformaticitions to the skills needed to start to build more complex analysis pipelines. This tutorial will take you though the steps needed to run standard quality control analysis on Illumina data using scripting to automate the analysis. 

In this tutorial you will be introduced to:

Basics of RNA-Seq Data Analysis - Lecture

This lecture will cover the basics of RNA-Seq experimental design and data quality assessment, followed by an overview of data analysis for the detection of differentally expressed genes.  Specific subtopics include:

Analysis of PacBio Sequencing Data Using SMRT Portal

This hands-on tutorial will cover installation and use of the SMRT portal at MSI to analyze PacBio sequencing data. The basics of full genome assembly and transcript assembly will be covered.  At the end of this tutorial, participants should be able to:

PacBio Sequencing - Lecture

This lecture will cover the special capabilities and use cases of PacBio sequencing as well as the basics of data analysis. Specific subtopics include:

  • Technology overview (physical basis of sequencing, pros and cons compared with other sequencing technologies)
  • De novo assembly applications (N50 and other assembly concepts, HGAP algorithm, diploid assembly)
  • IsoSeq transcriptome assessment (motivation, experimental procedure, biological applications, analysis approaches)
  • Visualization of PacBio data with new IGV features

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.


Intended Audience

Undergraduate and graduate students with some familiarity with finite element method, plus faculty interested in finite element analysis, optimization, or fatigue.

The SIMULIA Central’s Minneapolis office invites you to two-part seminar held on campus to provide an introductory, hands-on workshop with Abaqus and to introduce you to additional simulation technology recently made available to the University of Minnesota.


Rna-Seq Analysis

The RNA-Seq analysis tutorials includes two lectures and two hands-on guided tutorials. The lecture materials cover the basics of differential expression analysis and touches on other RNA-seq topics such as transcriptome assembly. 

Topics Covered:

Quality Control of Illumina Data with Galaxy

If you are new to bioinformatics this is the best place to start.

This hands-on tutorial will help a new user understand how to use the the Galaxy platform to analyze NGS data by working though the quality control steps needed for Illumina sequencing data.

This tutorial will: