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Last data update: 2014.03.03

R: Determine false discovery rate

calculateFDRs

R Documentation

Determine false discovery rate

Description

This function calculates the false discovery rate (FDR) based on randomized Bis-seq data.

Usage

calculateFDRs(m, CGIs, PMDs = NA, pdfFilename=NULL, num.cores = 1,
nCpG.smoothing = 3, meth.cutoffs = seq(0.3, 0.7, by=0.1), nCpG.cutoffs =
seq(1, 6, by=1), minCover = 5)

Arguments

`m`	GRanges object containing the methylation data.
`CGIs`	A GRanges object of CpG island coordinates. All CpGs overlapping CpG islands will be removed for the randomization.
`PMDs`	The GRanges object of the PMDs. Set to either the return value of the function segmentPMDs (see example) or to NA (default) if there are no PMDs.
`pdfFilename`	Name of the pdf file in which the figure is saved. If no name is provided (default), the figure is printed to the screen.
`num.cores`	Number of cores used for the calculations.
`nCpG.smoothing`	The number of consecutive CpGs that the methylation levels are averaged over.
`meth.cutoffs`	A vector containing the cut-offs in methylation for which the FDR should be calculated. Numbers must be between 0 and 1.
`nCpG.cutoffs`	A vector containing the cut-offs on the minimal number of CpGs per region for which the FDR should be calculated.
`minCover`	Only CpGs with a coverage of at least minCover reads will be used.

Value

A list containing a matrix with FDR values and a matrix with the number of inferred segments for each methylation cut-off (rows) and each cut-off on the minimal number of CpGs per region (columns). The function creates a figure showing the relationship between the methylation cut-off, the cut-off on the minimal number of CpGs per region, the number of inferred segments and the FDR. The figure is either printed to the screen (default) or saved as a pdf if a filename is provided.

Author(s)

Lukas Burger lukas.burger@fmi.ch

Examples


library(MethylSeekR)

# get chromosome lengths
library("BSgenome.Hsapiens.UCSC.hg18")
sLengths=seqlengths(Hsapiens)

# read methylation data
methFname <- system.file("extdata", "Lister2009_imr90_hg18_chr22.tab",
package="MethylSeekR")
meth.gr <- readMethylome(FileName=methFname, seqLengths=sLengths)

#load CpG islands
library(rtracklayer)
session <- browserSession()
genome(session) <- "hg18"
query <- ucscTableQuery(session, "cpgIslandExt")
CpGislands.gr <- track(query)
genome(CpGislands.gr) <- NA
CpGislands.gr <- resize(CpGislands.gr, 5000, fix="center")

#calculate FDRs, assuming no PMDs
stats <- calculateFDRs(m=meth.gr, CGIs=CpGislands.gr)

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(MethylSeekR)
Loading required package: rtracklayer
Loading required package: GenomicRanges
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, cbind, colnames, do.call, duplicated, eval, evalq,
    get, grep, grepl, intersect, is.unsorted, lapply, lengths, mapply,
    match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, rank,
    rbind, rownames, sapply, setdiff, sort, table, tapply, union,
    unique, unsplit

Loading required package: S4Vectors
Loading required package: stats4

Attaching package: 'S4Vectors'

The following objects are masked from 'package:base':

    colMeans, colSums, expand.grid, rowMeans, rowSums

Loading required package: IRanges
Loading required package: GenomeInfoDb
Loading required package: mhsmm
Loading required package: mvtnorm
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/MethylSeekR/calculateFDRs.Rd_%03d_medium.png", width=480, height=480)
> ### Name: calculateFDRs
> ### Title: Determine false discovery rate
> ### Aliases: calculateFDRs
> 
> ### ** Examples
> 
> 
> library(MethylSeekR)
> 
> # get chromosome lengths
> library("BSgenome.Hsapiens.UCSC.hg18")
Loading required package: BSgenome
Loading required package: Biostrings
Loading required package: XVector
> sLengths=seqlengths(Hsapiens)
> 
> # read methylation data
> methFname <- system.file("extdata", "Lister2009_imr90_hg18_chr22.tab",
+ package="MethylSeekR")
> meth.gr <- readMethylome(FileName=methFname, seqLengths=sLengths)
reading methylome data
Read 200000 records
> 
> #load CpG islands
> library(rtracklayer)
> session <- browserSession()
> genome(session) <- "hg18"
Error in `genome<-`(`*tmp*`, value = "hg18") : 
  Failed to set session genome to 'hg18'
Calls: genome<- -> genome<-
Execution halted