RJMCMC_result: Nucleosomes obtained by running RJMCMC function (for demo...

In ArnaudDroitLab/RJMCMC: Bayesian hierarchical model for genome-wide profiling of nucleosome positions based on high-throughput short-read data (MNase-Seq data)

Description

A list of class "rjmcmcNucleosomes" which contains the information about the detected nucleosomes.

Usage

data(RJMCMC_result)

Format

A list of class "rjmcmcNucleosomes" containing:

• call the matched call.

• K a vector of integer, the estimation of the number of the nucleosomes for each iteration.

• k a integer, the final estimation of the number of nucleosomes.

• mu a vector of numeric of length k, the positions of the nucleosomes.

• sigmaf a vector of numeric of length k, the variance of the forward reads for each nucleosome.

• sigmar a vector of numeric of length k, the variance of the reverse reads for each nucleosome.

• delta a vector of numeric of length k, the distance between the maxima of the forward and reverse reads position densities for each nucleosome.

• df a vector of numeric of length k, the degrees of freedom for each nucleosome.

• w a vector of positive numerical of length k, the weight for each nucleosome. The sum of all w values must be equal to 1.

• qmu a matrix of numerical with a number of rows of k, the 2.5% and 97.5% quantiles of each mu.

• qsigmaf a matrix of numerical with a number of rows of k, the 2.5% and 97.5% quantiles of the variance of the forward reads for each nucleosome.

• qsigmar a matrix of numerical with a number of rows of k, the 2.5% and 97.5% quantiles of the variance the reverse reads for each nucleosome.

• qdelta a matrix of numerical with a number of rows of k, the 2.5% and 97.5% quantiles of the distance between the maxima of the forward and reverse reads position densities for each nucleosome.

• qdf a matrix of numerical with a number of rows of k, the 2.5% and 97.5% quantiles of the degrees of freedom for each nucleosome.

• qw a matrix of numerical with a number of rows of k, the 2.5% and 97.5% quantiles of the weight for each nucleosome.

See Also

• rjmcmc for profiling of nucleosome positions

Examples

## Loading dataset
data(RJMCMC_result)
data(reads_demo)

## Results before post-treatment
RJMCMC_result$mu

## Post-treatment function which merged closely positioned nucleosomes
postResult <- postTreatment(startPosForwardReads = reads_demo$readsForward,
startPosReverseReads = reads_demo$readsReverse, RJMCMC_result, 74, 73500)

## Results after post-treatment
postResult

ArnaudDroitLab/RJMCMC documentation built on May 5, 2019, 7:06 a.m.