peakreg {iSeq} | R Documentation

## Call and merge enriched genomic windows/bins.

### Description

A function used to call and merge enriched bins using the posterior probability calculated by iSeq1 or iSeq2 functions at certain posterior probability and false discovery rate (FDR) cutoffs.

### Usage

    peakreg(chrpos,count,pp,cutoff,method=c("ppcut","fdrcut"),maxgap=300)

### Arguments

`chrpos` | A n by 3 matrix or data frame. The rows correspond to genomic bins. The first column contains chromosome IDs; the second and third columns contain the start and end positions of the bin, respectively.
`count` | A n by 2 matrix containing the number of sequence tags in the bins specified by chrpos. The first column contains the tag counts for chain 1 (usually the forward chain), and the second column contains the tag counts for chain 2 (usually the reverse chain). See the document of the function 'mergetag' for the definition of chain 1 and 2. The function uses the information in 'count' to find the center of the enriched regions, where the true binding sites are usually located.
`pp` | A vector containing the posterior probabilities of bins in the enriched state returned by functions iSeq1 or iSeq2.
`cutoff` | The cutoff value (a scalar) used to call enriched bins. If use posterior probability as a criterion (method="ppcut"), a bin is said to be enriched if its pp is greater than the cutoff. If use FDR as a criterion (method="fdrcut"), bins are said to be enriched if the bin-based FDR is less than the cutoff. The FDR is calculated using a direct posterior probability approach (Newton et al., 2004).
`method` | 'ppcut' or 'fdrcut'.
`maxgap` | The criterion used to merge enriched bins. If the genomic distance of adjacent bins is less than maxgap, the bins will be merged into the same enriched region.

### Value

A data frame with rows corresponding to enriched regions and columns corresponding to the following:

`chr` | Chromosome IDs.
`gstart` | The start genomic position of the enriched region.
`gend` | The end genomic position of the enriched region.
`rstart` | The row number for gstart in chrpos.
`rend` | The row number for gend in chrpos.
`peakpos` | The inferred center (peak) of the enriched region.
`meanpp` | The mean posterior probability of the merged regions/bins.
`ct1` | total tag counts for the region from gstart to gend for the chain corresponding to count[,1]; ct1=sum(count[rstart:rend,1])
`ct2` | total tag counts for the region from gstart to gend for the chain corresponding to count[,2]; ct2=sum(count[rstart:rend,2])
`ct12` | ct12 = ct1 + ct2
`sym` | A parameter used to measure if the forward and reverse tag counts are symmetrical (or balanced) in enriched regions. The values range from 0.5 (perfect symmetry) to 0 (complete asymmetry).

### Author(s)

Qianxing Mo qianxing.mo@moffitt.org

### References

Qianxing Mo. (2012). A fully Bayesian hidden Ising model for ChIP-seq data analysis. Biostatistics 13(1), 113-28.

Newton, M., Noueiry, A., Sarkar, D., Ahlquist, P. (2004). Detecting differential gene expression with a semiparametric hierarchical mixture method. Biostatistics 5 , 155-176.

### See Also

`iSeq1`, `iSeq2`, `mergetag`,`plotreg`

### Examples

    data(nrsf)
    chip = rbind(nrsf$chipFC1592,nrsf$chipFC1862,nrsf$chipFC2002)
    mock = rbind(nrsf$mockFC1592,nrsf$mockFC1862,nrsf$mockFC2002)
    tagct = mergetag(chip=chip,control=mock,maxlen=80,minlen=10,ntagcut=20)
    tagct22 = tagct[tagct[,1]=="chr22",]
    res1 = iSeq1(Y=tagct22[,1:4],gap=200,burnin=200,sampling=500,ctcut=0.95,a0=1,b0=1,
     a1=5,b1=1, k0=3,mink=0,maxk=10,normsd=0.1,verbose=FALSE)

    reg1 = peakreg(tagct22[,1:3],tagct22[,5:6]-tagct22[,7:8],res1$pp,0.5,
            method="ppcut",maxgap=200)

    reg2 = peakreg(tagct22[,1:3],tagct22[,5:6]-tagct22[,7:8],res1$pp,0.05,
             method="fdrcut",maxgap=200)

[Package iSeq version 1.40.0 Index]