Description Usage Arguments Value Author(s) References See Also Examples

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.

1 |

`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. |

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). |

Qianxing Mo qianxing.mo@moffitt.org

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.

`iSeq1`

, `iSeq2`

, `mergetag`

,`plotreg`

1 2 3 4 5 6 7 8 9 10 11 12 13 | ```
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)
``` |

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