findDMCFB-method {DMCFB} | R Documentation

## findDMCFB method

### Description

DMC identification via Bayesian functional regression models

### Usage

    findDMCFB(
      object,
      bwa,
      bwb,
      nBurn,
      nMC,
      nThin,
      alpha,
      sdv,
      nCores,
      pSize,
      sfiles
    )

    ## S4 method for signature 'BSDMC'
    findDMCFB(
      object,
      bwa,
      bwb,
      nBurn,
      nMC,
      nThin,
      alpha,
      sdv,
      nCores,
      pSize,
      sfiles
    )

### Arguments

`object` | A `BSDMC-class` object
`bwa` | An integer value specifying the band-width size of B-spline basis matrix for a natural cubic spline for the group-specific effects of the Bayesian functional regression model
`bwb` | An integer value specifying the band-width size of B-spline basis matrix for a natural cubic spline for the individual-specific effects of the Bayesian functional regression model
`nBurn` | An integer value specifying the number of burn-in samples
`nMC` | An integer value specifying the number of MCMC samples after burn-in
`nThin` | An integer value specifying the thining number in MCMC
`alpha` | A numeric value specifying the level of α in credible interval (1-α)\%
`sdv` | An double value specifying the standard deviation of priors
`nCores` | An integer value specifying the number of machine cores for parallel computing
`pSize` | An integer value specifying the number of cytosines in a regrion to be used in a Bayesian functiona regression model for DMC detection
`sfiles` | A logical value indicating whether files to be saved or not.

### Value

`BSDMC-class` object

### Author(s)

Farhad Shokoohi <shokoohi@icloud.com>

### Examples

    set.seed(1980)
    nr <- 1000
    nc <- 4
    metht <- matrix(as.integer(runif(nr * nc, 0, 100)), nr)
    methc <- matrix(rbinom(n = nr * nc, c(metht), prob = runif(nr * nc)), nr, nc)
    methl <- methc / metht
    r1 <- GRanges(rep("chr1", nr), IRanges(1:nr, width = 1), strand = "*")
    names(r1) <- 1:nr
    cd1 <- DataFrame(
      Group = rep(c("G1", "G2"), each = nc / 2),
      row.names = LETTERS[1:nc]
    )
    OBJ1 <- cBSDMC(
      rowRanges = r1, methReads = methc, totalReads = metht,
      methLevels = methl, colData = cd1
    )
    OBJ2 <- findDMCFB(OBJ1,
      bwa = 10, bwb = 10, nBurn = 50, nMC = 50, nThin = 1,
      alpha = 0.05, nCores = 2, pSize = 500, sfiles = FALSE
    )
    OBJ2

[Package DMCFB version 1.4.0 Index]