OHIO SUPERCOMPUTER CENTER (OSC) WORKSHOP
Date held :6th August 2013
As computational biologists, we often require powerful, high performance computing, storage and software resources so as to handle effectively and efficiently the three phases in analysis of bioinformatics data (preprocessing, analysis, post-processing). At CCBL, in order to accelerate our research we are planning a collaboration with expert staff provided by the OSC in a one day workshop that will serve to:
- Inform CCBL members with an overview of the OSC mandate in academic research.
- Train members on batch processing jobs (example blast jobs will be used) that are frequently encountered in Bioinformatics analysis.
- Nurture a long-lasting collaborative environment between CCBL and OSC.
INTRODUCTION TO R PROGRAMMING AND STATISTICAL ANALYSIS
Instructor: Stephen O. Opiy Email:firstname.lastname@example.org
Date held : March 2014
The programming language R is becoming increasingly important because it is not only very flexible in reading, manipulating, and writing data, but all its outcomes are directly available as objects for further programming.R makes basic as well as advanced statistical programming easy and provides the possibility to combine the learning of statistical concepts by mathematics,programming, and visualization. Statistical tools therefore provide procedures to explore and visualize data as well as to test biological hypotheses.
- Introduction into basic functionalities of Rstudio (Day 1)
- Installation of Rstudio
- Rstudio session management
- Importing and exporting data in Rstudio
- Data analysis, storage of Basic data types(Logical, numeric, and character represented as Vectors, Matrices, Arrays)
- R graphics and Statistical analysis (Day 2)
- Graphics and data visualization in R (R generates publication-ready figures).
- How to locate and install necessary packages
- How to use High and Low level plotting commands/functions
- Basic Statistics using R
- How to obtain Mean, standard deviation, median and mode from expression data (most important descriptive statistics)
After studying this course the members were equiped with a sufficient background and an environment for Bioconductor Case Studies as well as tools to be used in their daily routine research work in Bioinformatics and Computational Biology by using R and Bioconductor.
Kindly contact the instructor for training notes