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- Computational Statistics for Genome Biology (CSAMA)
Computational Statistics for Genome Biology (CSAMA)
Bressanone/Brixen, Italy
2012-07-02 ~ 2012-07-06
Instructors
- Martin Morgan
- Robert Gentleman
- Vincent J. Carey
- Wolfgang Huber
- Simon Anders
- Mark Robinson
Description
This one week intensive course will give insights into recent advances in statistical and computational aspects of the design and interpretation of genome-scale experiments. The topics will include all aspects of the data analysis of high-throughput sequencing for transcriptomics (RNA-Seq) and chromatin dynamics (ChIP-Seq). The course is intended for researchers with a basic understanding of these technologies and their associated statistical and computational challenges. The four practical sessions of the course will require basic programming in the language R.
Materials
Slides
- 2012-07-02-Carey-reproducible-workflows.pdf
- 2012-07-02-Gatto-Quick-Package.pdf
- 2012-07-02-Gatto-R-Basics.pdf
- 2012-07-02-Gentleman-Bioconductor.pdf
- 2012-07-02-Huber-Microarrays.pdf
- 2012-07-02-Morgan-bioc-for-seq-analysis.pdf
- 2012-07-03-Anders-Sequencing-alignment.pdf
- 2012-07-03-Carey-ranges.pdf
- 2012-07-03-Morgan-reads-sequences-alignments.pdf
- 2012-07-04-Anders-DESeq-DEXSeq.pdf
- 2012-07-04-Gentleman-Statistics-intro.pdf
- 2012-07-04-Huber-Multiple-testing-independent-filtering.pdf
- 2012-07-05-Morgan-annotation.pdf
- 2012-07-06-Gentleman-GSEA.pdf
- 2012-07-06-Gentleman-Variant-calling.pdf
- 2012-07-06-Huber-Machine-learning.pdf
- 2012-07-06-Morgan-motifs.pdf
- 2012-07-06-Morgan-splice-graphs.pdf
- BioCOverview2012.ppt
- Statistics101.ppt
- EpigenomicsBrixen_Computational.pptx.pdf
- EpigenomicsBrixen_Intro.pptx.pdf
Install the package for Friday’s lab, using R-2.15, as follows:
source("http://bioconductor.org/scratch-repos/pkgInstall.R")
pkgInstall("ReadsAlignmentsVariantsLab")