postPING {PING} | R Documentation

## Post process Estimation of binding site positions obtained from PING

### Description

Post process Estimation of binding site positions obtained from PING. Refit mixture models with stronger prior in candidate regions contain potential problems, and then convert final result into dataframe.

### Usage

    postPING(ping, seg, rho2=NULL, sigmaB2=NULL, alpha2=NULL, beta2=NULL, min.dist= 100, paraEM=NULL, paraPrior=NULL, score=0.05, dataType="MNase", nCores=1, makePlot=FALSE, FragmentLength=100, mart=NULL, seg.boundary=NULL, DupBound=NULL, IP=NULL, datname="")

### Arguments

`ping` | A 'pingList' object containing estimation of nuclesome positions, result of 'PING' function.
`seg` | An object of class 'segmentReadsList' containing the results for all regions pre-processed, 'segmentReads' function.
`paraEM` | A list of parameters for the EM algorithm. The default parameters should be good enough for most usages.

`minK`:

  An `integer`, default=0. The minimum number of binding events per region. If the value is 0, the minimum number is automatically calculated.

`maxK`:

  An `integer`, default=0. The maximum number of binding events per region. If the value is 0, the maximum number is automatically calculated.

`tol`:

  A `numeric`, default=1e-4. The tolerance for the EM algorithm.

`B`:

  An `integer`, default=100. The maximum number of iterations to be used.

`mSelect`:

  A character string specifying the information criteria to be used when selecting the number of binding events. Default="AIC3"

`mergePeaks`:

  A `logical` stating whether overlapping binding events should be picked. Default=TRUE

`mapCorrect`:

  A `logical` stating whether mappability profiles should be incorporated in the estimation, i.e: missing reads estimated. Default=TRUE

`paraPrior` | A list of parameters for the prior distribution. The default parameters should be good enough for most usages.

`xi`:

  An `integer`. The average DNA fragment size.

`rho`:

  An `integer`. A variance parameter for the average DNA fragment size distribution.

`alpha`:

  An `integer`. First hyperparameter of the inverse Gamma distribution for sigma^2 in the PICS model

`beta`:

  An `integer`. Second hyperparameter of the inverse Gamma distribution for sigma^2 in the PING model

`lambda`:

  An `integer`. The lambda control Gaussian Markov Random Field prior on the distance of adjacent nucleosomes, we do not recommend user change the default value.

`dMu`:

  An `integer`. Our best guess for the distance between two neighboring nucleosomes.

`rho2, sigmaB2, alpha2, beta2` | Integer values, the parameters in the prior of mixture models to be re-fitted.
`min.dist` | The minimum distance of two adjacent nucleosomes predicted from different candidate regions, smaller than that will be treated as duplicated predictions for the same nucleosomes.
`score` | A `numeric`. The score threshold used when calling `FilterPING`.

`dataType` | A character string that can be set to use selected default parameters for the algorithm.
`nCores` | An `integer`. The number of cores that should be used in parallel by the function.
`makePlot` | A `logical`. Plot a summary of the output.
`FragmentLength, mart, seg.boundary, DupBound, IP, datname` | Plotting parameters and options.

`IP`:

  A `GRanges` object. The reads used in segmentation process.

`FragmentLength`:

  An `integer`. The length of XSET profile extension

### Value

A `data.frame` containing the estimation of binding site positions.

### Note

Based on our experiemt on a few real data sets, we suggestion to use following values of parameters. For sonication data we use rho1=1.2; sigmaB2=6400;rho=15;alpha1=10; alpha2=98; beta2=200000. For MNase data we use rho1=3; sigmaB2=4900; rho=8; alpha1=20; alpha2=100; beta2=100000. The value of xi depends on specy of sample, since that affect the length of linker-DNA. For example, we use xi=160 for yeast and xi=200 for mouse.

### Author(s)

Xuekui Zhang <xzhang@stat.ubc.ca>, Sangsoon Woo, swoo@fhcrc.org and Raphael Gottardo <raphael.gottardo@ircm.qc.ca>

### References

Xuekui Zhang, Gordon Robertson, Sangsoon Woo, Brad G. Hoffman, and Raphael Gottardo, "Probabilistic Inference for Nucleosome Positioning with MNase-based or Sonicated Short-read Data" PlosONE, under review.

### See Also

`PING` `plotSummary`

[Package PING version 2.24.0 Index]