BSDMC-class {DMCFB} | R Documentation

## BSDMC object

### Description

The `BSDMC` object is an S4 class that represents differentially methylated CpG sites (DMCs) in BS-Seq Data.

### Arguments

`methReads` | The matrix `methReads` contains the number of methylated reads spanning a CpG-site. The rows represent the CpG sites in `rowRanges` and the columns represent the samples in `colData`.
`totalReads` | The matrix `totalReads` contains the number of reads spanning a CpG-site. The rows represent the CpG sites in `rowRanges` and the columns represent the samples in `colData`.
`methLevels` | The matrix `methLevels` contains the predicted methylation level spanning a CpG-site using Bayesian functional regression models. The rows represent the CpG sites in `rowRanges` and the columns represent the samples in `colData`.

### Value

A `BSDMC-class` object

### Slots

`methReads`

  An integer matrix

`totalReads`

  An integer matrix

`methLevels`

  A numeric matrix

### Author(s)

Farhad Shokoohi <shokoohi@icloud.com>

### See Also

`RangedSummarizedExperiment-class` `GRanges-class`

### Examples

    nr <- 500
    nc <- 16
    metht <- matrix(as.integer(runif(nr * nc, 0, nr)), nr)
    methc <- matrix(rbinom(n = nr * nc, c(metht), prob = runif(nr * nc)), nr, nc)
    meths <- matrix(as.integer(runif(nr * nc, 0, 10)), nr)
    methl <- methc / metht
    methv <- matrix((runif(nr * nc, 0.1, 0.5)), nr)
    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])
    OBJ2 <- cBSDMC(
      rowRanges = r1, methReads = methc, totalReads = metht,
      methLevels = methl, methStates = meths, methVars = methv, colData = cd1
    )
    OBJ2

[Package DMCFB version 1.4.0 Index]