Biostatistics in Practice

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Data Sciences for the Life Sciences in a High Performance Computing Environment
A One-Day Short Course on February 7, 2014

ICB3 is pleased to launch the Biostatistics in Practice series. The first one-day short course is data sciences for the life sciences in a high performance computing environment. This course offers participants a foundational curriculum on statistical computing using R, an open-source and freely-available statistical programming language, in a high performance computing environment. Emphasis is placed on “big data” applications in biomedical and public health research settings.
The short course is jointly sponsored by the Massachusetts Green High Performance Computing Center (MGHPCC), a new state- of-the-art facility dedicated to research-oriented computing. This course offers the first opportunity for life sciences researchers to learn how to effectively utilize the MGHPCC facility for their research and become early-adopters of this world-class resource.

What? The workshop will take place at the Massachusetts Green High Performance Computing Center (MGHPCC), a new state-of-the-art facility dedicated to research-oriented computing. Biostatistiucs in Practice offers the first opportunity for life sciences researchers to learn how to effectively utilize the MGHPCC facility for their research and become early-adopters of this world-class resource.

Participants will learn how to leverage powerful tools for high-performance computational research using R, such as:

  • ggplot2
  • GitHub
  • knitr
  • multicore
  • RStudio
  • Shiny

When? Friday, Februrary 7, 2014– 8am to 6pm (all meals for the day included)

Where? The Massachusetts Green High Performance Computing Center (MGHPCC) – 100 Bigelow Street, Holyoke, MA

Who should attend? The short course is designed for researchers from academic and industry environments. Basic familiarity with the R statistical computing environment is recommended.

 

Tentative Program

 

8:00 Registration and networking
9:00 Session 1: Principles of reproducible research with R
10:15 Break and networking
10:45 Session 2: Introduction to cluster computing with R
12:00 Lunch and networking
1:15 Tour of the MGHPCC
1:45 Session 3: Simulation and parallel computing with R
3:00 Break and networking
3:30 Session 4: Topics in big data sciences
4:45-6 Closing Reception