[BioC] [Course] CSAMA 2011: Computational Statistics for Genome Biology (Ninth Edition)

[stefano iacus]

CSAMA 2011: Computational Statistics for Genome Biology (Ninth Edition)

This one week intensive course is intended to give insights into recent advances in statistical and computational aspects of the design and interpretation of microarray experiments. The topics will include all aspects of the data analysis of microarray experiments for transcript profiling and ChIP-chip. The course is intended mainly for researchers with a basic understanding of microarray technology and its statistical and computational challenges. The four practical sessions of the course will be most beneficial for participants that are able to converse in a programming language such as R.


What will it cover? (tentative program)

* Introduction to R and Bioconductor
* RNA-Seq and ChiP-Seq data analysis
* Microarray analysis
* Statistics for differential expression
* Sequence manipulation
* Annotation of genes, genomic features and variants
* Gene set enrichment analysis
* Machine Learning
* High-throughput image analysis

Where? 
Brixen-Bressanone (Alps!), Italy

When? 
26th June -- 1st July, 2011

Please see
http://marray.economia.unimi.it/

List of speakers

Vincent J. Carey, Channing Laboratory, Harvard Medical School (USA)
Robert Gentleman, Genentech (USA)
Kasper Daniel Hansen,  Johns Hopkins Bloomberg School of Public Health (USA)
Wolfgang Huber, European Molecular Biology Laboratory (DE)
Martin Morgan, Fred Hutchinson Cancer Research Center (USA)

Few places left, registration closes soon!

Best regards
   Stefano


Tentative day by day program follows
*Mon*
  Introduction to R and Bioconductor
  Bioconductor packages for short read I/O, data management and analysis
  Reproducible workflows with R
  Basics of HT sequencing technologies

*Tue*
  Short read alignment using externals tools like bowtie, bwa, SOAP
  Biostrings, ShortRead, Rsamtools, gapped alignments
  IRanges, GenomicRanges
  What you still need to know about microarrays: normalisation, quality assessment, strengths and weaknesses, differential expression, use of existing datasets for integrative analyses

*Wed*
  t-test and linear model - the general statistical concepts
  RNA-Seq transcript quantification and differential expression: what to do once you have read counts per gene, transcript, exon or region. GLMs with the negative binomial distribution; DESeq, edgeR
  Multiple testing and independent filtering
  Emerging topic

*Thu*
  Gene and genome annotation - AnnotationDbi, GenomicFeatures
  Methods for visualising your data along genomic coordinates - Rtracklayer, IGB, GenomeGraphs
  ChIP-Seq related topics
  eQTL-type analyses
 
*Fri*
 Clustering and Classification
 Aggregation - gene set enrichment analysis
 Image Analysis and pattern recognition in cellular assays, perhaps something about genetic interactions
 Emerging topic


-----------------------------------
Stefano M. Iacus
Department of Economics,
Business and Statistics
University of Milan
Via Conservatorio, 7
I-20123 Milan - Italy
Ph.: +39 02 50321 461
Fax: +39 02 50321 505
http://www.economia.unimi.it/iacus
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