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R/Bioconductor Workshop Session II - Bioconductor-ing

Join the growing community of R/Bioconductor users in learning how to analyze ChIP-seq data. Explore packages like Biostrings and ShortRead, and discover the power and versatility of R for bioinformatics analysis. Get support from experts and access hundreds of software packages for customized analysis.

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R/Bioconductor Workshop Session II - Bioconductor-ing

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  1. R/Bioconductor WorkshopSession II - Bioconductor-ing

  2. What is Bioconductor Fall 2001 Remember this guy?? Gordon Symth Herve Pages Robert Gentleman, Program Head Computational Biology FHCR James W Macdonald Rafael Irizarry Martin Morgan VJ Carey Wolfgang Huber

  3. A growing community

  4. Citations • Google Scholar(May 2008) reports 970 scientific documents

  5. Screenshots

  6. Mailing Lists (Bioc-help,Bioc-dev) Subject: Re: [BioC] analysis ChIP-seq dataSent By:  bioconductor-bounces@stat.math.ethz.ch  On:June 10, 2008 11:40 AM On Behalf Of:"Martin Morgan" <mtmorgan@fhcrc.org>To:"Bogdan Tanasa" <tanasa@gmail.com>Cc:bioc-sig-sequencing@r-project.org; bioconductor Hi Bodan -- "Bogdan Tanasa" <tanasa@gmail.com> writes: > Hi everyone, > > I am in the process of analyzing a lot of ChIP-seq data and I am writing to ask > if an analysis module becomes available for R/Bioconductor anytime soon. Visit the bioc-sig-sequencing news group (Cc'd in the reply) https://stat.ethz.ch/mailman/listinfo/bioc-sig-sequencingCurrent packages include Biostrings (for lots of string matching / manipulation facilities) and ShortRead (for IO from ELAND or MAQ, for instance, plus additional sorting, counting, and qa-related functionality. There are posts in the bioc-sig-sequencing news group about package use. Maybe others will reply (to bioc-sig-sequencing) with additional developments; I know people are working with and developing packages for this data in R. Martin

  7. clusterData clusterAnnotation goCluster clusterAlgorithm clusterSignif clusterStatistic clusterVisual goCluster goCluster Structure: 6 abstract classes define the general structure of the analysis task. Each abstract class can be filled with a specific module fullfilling the requested function in a special way. • goCluster is a tool for the analysis of expression data in conjunction with annotation data • The package provides an object-oriented “framework” that allows to flexibly combine plugins to a specialized analysis method. • goCluster provides modules for annotation data as well as clustering, statistical, and visualization methods. Example analysis: The plot shows a section of a hierarchical clustering that has been combined with gene ontology data using goCluster. The package has been able to automatically detect regions in the clustering that are enriched for specific GO-terms. Biological process

  8. affylmGUI

  9. GLAD: Gain and Loss Analysis of DNA GLAD is devoted to the analysis of array CGH data (Comparative Genomic Hybridization) It allows the identification of breakpoints It detects outliers Each chromosomal regions are given a status (Gain, Normal or Loss) Plot functions are available to draw genomic profiles package required: AWS Reference: Hupé et al., Bioinformatics (2004) contact: glad@curie.fr web site: http://bioinfo.curie.fr

  10. Why I am falling in love with bioconductor • Versatile and powerful– Room for development, customized analysis, hundreds of software packages • Runs only Everything – Laptops, Servers, Windows, Linux, Unix, Ultrasparc • Support – Hundreds of bioinformaticians, biologists, Statisticians, IT dudes, mailing list, etc • Free!!!!

  11. What are we waiting for?

  12. Before we begin…

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