RGM

This course is designed to introduce the most popular statistical software (R/Bioconductor) for biology students with a strong interest in analyzing high-throughput data. R/Bioconductor is a powerful, open source, and flexible statistical language to analyze large data types such as expression, genomics and genetics (http://www.bioconductor.org/). Because this will be an introduction, no prerequiste is required, except familiarity with a computer. The aim is to cover the basics of using R for statistical programming, computation, graphics, and modeling, especially for analyzing high-throughput genomic data. I will start with a basic introduction to the R language, reading and writing data, and plotting data. As an example, we will go through an analysis of my recent work (Noushmehr et al. Cancer Cell. 2010 May 18;17(5):510-22). This case study will be based on real gene expression and epigenomics data types and will introduce you to some of the popular R/Bioconductor packages currently available. The ultimate objective is to provide students an opportunity to explore the ins-and-outs of R/Bioconductor such that they can quickly apply it in their own research. In addition, the main objective is to also introduce advanced bioinformatic tools used in the field of genomics research to assist in analyzing and interpreting large-scale next generation sequencing data such as RNAseq, DNAseq, ChIPseq, BSseq.