R/Bioconductor WorkshopSession II - Bioconductor-ing

What is Bioconductor

Remember this guy??Fall 2001

Robert Gentleman, Program Head Computational

Biology FHCR

VJ Carey Wolfgang Huber

Rafael Irizarry

James W Macdonald

Herve Pages

Martin Morgan

Gordon Symth

A growing community

Citations Google Scholar(May 2008) reports 970 scientific documents

Screenshots

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-sequencing

Current 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

goCluster

• 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.

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.

goC

lust

er

clusterData

clusterAnnotation

clusterAlgorithm

clusterSignif

clusterStatistic

clusterVisual

Biological process

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.

affylmGUI

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

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