manhattanDMCs-method: manhattanDMCs method

In DMCHMM: Differentially Methylated CpG using Hidden Markov Model

Description

Creates a Manhattan plot based on the p-values obtained from findDMCs method

Usage

manhattanDMCs(
  object,
  col,
  chrlabs,
  suggestiveline,
  genomewideline,
  highlight,
  logp,
  annotatePval,
  annotateTop,
  ...
)

## S4 method for signature 'BSDMCs'
manhattanDMCs(
  object,
  col,
  chrlabs,
  suggestiveline,
  genomewideline,
  highlight,
  logp,
  annotatePval,
  annotateTop,
  ...
)

Arguments

object	A BSData-class or BSDMCs-class object
col	A character vector indicating which colors to alternate.
chrlabs	A character vector equal to the number of chromosomes specifying the chromosome labels (e.g., c(1:22, "X", "Y", "MT")).
suggestiveline	Where to draw a "suggestive" line. Default -log10(1e-5). Set to FALSE to disable.
genomewideline	Where to draw a "genome-wide sigificant" line. Default -log10(5e-8). Set to FALSE to disable.
highlight	A character vector of SNPs in your dataset to highlight. These SNPs should all be in your dataset.
logp	If TRUE, the -log10 of the p-value is plotted. It isn't very useful to plot raw p-values, but plotting the raw value could be useful for other genome-wide plots, for example, peak heights, bayes factors, test statistics, other "scores," etc.
annotatePval	If set, SNPs below this p-value will be annotated on the plot.
annotateTop	If TRUE, only annotates the top hit on each chromosome that is below the annotatePval threshold.
...	other possible parameters

Value

A Manhattan plot

Author(s)

Farhad Shokoohi <[e-mail]>

Examples

set.seed(1980)
nr <- 150; nc <- 8
metht <- matrix(as.integer(runif(nr * nc, 0, 100)), nr)
methc <- matrix(rbinom(n=nr*nc,c(metht),prob = runif(nr*nc)),nr,nc)
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 <- cBSData(rowRanges=r1,methReads=methc,totalReads=metht,colData=cd1)
OBJ2 <- methHMEM(OBJ1, MaxK=2, mc.cores=2)
OBJ3 <- methHMMCMC(OBJ2, mc.cores=2)
OBJ4 <- findDMCs(OBJ3, mc.cores=2)
manhattanDMCs(OBJ4)

DMCHMM documentation built on Nov. 8, 2020, 8:20 p.m.