BAC {BAC} | R Documentation

## Bayesian Analysis of ChIP-chip tiling arrays

### Description

Bayesian Analysis of ChIP-chip tiling arrays

### Usage

    BAC(C, I, B=15000,verbose=FALSE,w=5)

### Arguments

`C` | The matrix of control measurements. Rows correspond to probes and columns to samples.
`I` | The matrix of IP measurements. Rows correspond to probes and columns to samples.
`B` | Number of iterations used the MCMC. Default to 15000.
`verbose` | Logical parameter. If TRUE, some progression
`w` | The window size. Default to 5. See details below for more about this parameter.

### Details

The window size should be calculated in function of the resolution and the shearing resolution. For example, for Affymetrix human tiling arrays, the shearing resolution is 500-1000bps, the tiling resolution is 35bps and the probe length is 25bps. Then one would expect a bound region to contain 500-1000/(35+25)~8-16 probes. Thus we decided to set w to 5. Note that the exact value of w is not crucial.

### Value

The marginal posterior probabilities and the joint posterior probabilities computed from the Bayesian hierarchical model. We recommend using the joint posterior probabilities to call enriched regions.

### Author(s)

Raphael Gottardo, raph@stat.ubc.ca

### See Also

CallRegions

### Examples

    # Load the data
    data(ER)
    # Only select the first 5000 probes for speed-up
    ER<-ER[1:5000,]
    # Calculate the joint posterior probabilities
    #Only use 100 iterations for speed up (You should use more! See default value)
    BAConER<-BAC(ER[,5:7], ER[,2:4], B=100,verbose=FALSE,w=5)
    # For Regions using 0.5 cut-off for the joint posterior probabilities
    ERregions<-CallRegions(ER[,1],BAConER$jointPP,cutoff=0.5,maxGap=500)
    # Create the BED file
    nRegions<-max(ERregions)
    BED<-matrix(0,nRegions,4)
    for(i in 1:nRegions)
    {
    BED[i,2:3]<-range(ER[ERregions==i,1])
    #The score should be between 0 and 1000
    BED[i,4]<-max(BAConER$jointPP[ERregions==i])*1000
    }
    BED<-data.frame(BED)
    # The ER data is a subset of chr 21
    BED[,1]<-"chr21"
    names(BED)<-c("chrom","chromStart","chromEnd","Score")
    # print it
    print(BED)

[Package BAC version 1.0.0 Index]