Summer 2017 | Bioinformatics Workshops at MSU |

Summer 2017 | Bioinformatics Workshops at MSU |

The CMSE Department is offering three week-long bionformatics workshops. Each week, we will meet from 8:30am - 12:30pm, Monday through Friday, in Room 1502/1503 Engineering Building. Cost is $50 per person per workshop and must be paid via an MSU grant. A limited number of fee waivers are available. Lunch and snacks will be provided.

Week 1: July 31 -- August 4
Week 2: August 7 -- 11
Week 3: August 14 -- 18

If you click the registration link below and get a permissions error, please go to http://googleapps.msu.edu.  Click on Google Drive and log in using your MSU NetID and password.  Then try clicking the link again.
 
Register Here: http://bit.ly/msubioinfo2017
 
Send questions about the workshops and issues with registration to the Bioinformatics Coordinator at ablackpz@msu.edu.

In Week 1, we will introduce you to UNIX commands and R programming, and show how to integrate them to create automated, reproducible workflows.

  • LEARNING OUTCOMES
    • Download, organize, modify data files using Linux utilities
    • Use RStudio and R Notebooks to write & execute R programs
    • Implement file input/output, loops, control statement, and functions in R
    • Import and use external R packages
    • Manipulate data and make multiple types of plots

In Week 2, we will introduce you to a range of fundamental concepts in statistics and demonstrate how to apply them for routine data analyses.

  • LEARNING OUTCOMES
    • Summarize data using descriptive statistics and plots
    • Learn common continuous & discrete distributions and use them in R
    • Perform parametric and nonparametric hypothesis testing
    • Learn and perform multivariable data analysis (regression, clustering, & PCA)

In Week 3, we demonstrate all the steps involved in turning RNA-Seq raw reads into gene-expression levels, differentially-expressed genes, enriched pathways, and gene/sample clusters.

  • LEARNING OUTCOMES
    • Execute quality control and mapping of RNA-seq reads
    • Quantify gene, transcript, and exon expression levels
    • Perform differential expression and pathway enrichment analyses
    • Perform advanced analyses including clustering, PCA, and network analysis