Package 'MAGAR'

Title: MAGAR: R-package to compute methylation Quantitative Trait Loci (methQTL) from DNA methylation and genotyping data
Description: "Methylation-Aware Genotype Association in R" (MAGAR) computes methQTL from DNA methylation and genotyping data from matched samples. MAGAR uses a linear modeling stragety to call CpGs/SNPs that are methQTLs. MAGAR accounts for the local correlation structure of CpGs.
Authors: Michael Scherer [cre, aut]
Maintainer: Michael Scherer <[email protected]>
License: GPL-3
Version: 1.15.1
Built: 2024-12-05 21:51:18 UTC
Source: https://github.com/bioc/MAGAR

Help Index

computeCorrelationBlocks

Description

This function computes CpG correlation blocks from correlations of CpGs across samples by Louvian clustering.

Usage

computeCorrelationBlocks(
  meth.data,
  annotation,
  cor.threshold = qtlGetOption("cluster.cor.threshold"),
  sd.gauss = qtlGetOption("standard.deviation.gauss"),
  absolute.cutoff = qtlGetOption("absolute.distance.cutoff"),
  max.cpgs = qtlGetOption("max.cpgs"),
  assembly = "hg19",
  chromosome = "chr1"
)

Arguments

meth.data

A data.frame containing the methylation data with CpGs in the rows and samples in the columns.
annotation

The genomic annotations of the CpG positions.
cor.threshold

The correlation threshold used to discard edges from the correlation-based network.
sd.gauss

Standard deviation of the Gauss distribution used to weight the distance
absolute.cutoff

Absolute distance cutoff after which no methQTL interaction is to be considered.
max.cpgs

Maximum number of CpGs used in the computation (used to save memory). 40,000 is a reasonable default for machines with ~128GB of main memory. Should be smaller for smaller machines and larger for larger ones.
assembly

The assembly used
chromosome

The chromosome for which correlation block calling is to be performed

Details

This method performs clustering of the correlation matrix obtaind from the DNA methylation matrix. Correlations are computed for each pair of CpGs across all the samples. We then compute a similarity matrix from this correlation matrix and set correlations lower than the given threshold to 0. In the next step, we weight the correlations by the distance between the CpGs: smaller distances get higher weights according to Gaussian distribution with mean 0 and standard deviation as specified above. Furthermore, similarities of CpGs that are further than absolute.distance.cutoff away from one another are discarded.

We then compute the associated weighted, undirected graph from the similarity matrix and execute Louvain clustering on the graph. The resulting clusters of CpGs are returned.

Value

A list representing the clustering of CpGs into correlation blocks. Each element is a cluster, which contains row indices of the DNA methylation matrix that correspond to this cluster.

Author(s)

Michael Scherer

Examples

meth.qtl <- loadMethQTLInput(system.file("extdata","reduced_methQTL",package="MAGAR"))
meth.data <- getMethData(meth.qtl)
anno.meth <- getAnno(meth.qtl,"meth")
cor.blocks <- computeCorrelationBlocks(meth.data[seq(1,10),],annotation=anno.meth[seq(1,10),])

doImport

Description

Performs input for the given DNA methylation and genotyping data.

Usage

doImport(
  data.location,
  s.anno = NULL,
  assembly.meth = "hg19",
  assembly.geno = "hg19",
  tab.sep = ",",
  s.id.col = "sample_id",
  out.folder = tempdir(),
  ...
)

Arguments

data.location

Named character vector specifying the data location. The names correspond to:

idat.dir

Path to the DNA methylation data. Can be in the form of IDAT files or in any other format accepted by RnBeads

geno.dir

Path to the genotyping data file directory, either containing PLINK files (i.e. with bed, bim and fam files), imputed, (dosage) files (i.e. with dos and txt files), or idat files
s.anno

Path to the sample annotation sheet. If NULL, the program searches for potential sample annotation sheets in the data location directories.
assembly.meth

Assembly used for the DNA methylation data. Typically is "hg19" for Illumina BeadArray data.
assembly.geno

Assembly used for the genotyping data. If it is not the same as assembly.geno, the positions will be matched using liftOver.
tab.sep

The table separator used for the sample annotation sheet.
s.id.col

The column name of the sample annotation sheet that specifies the sample identifier.
out.folder

The output directory to store diagnostic plots
...

Futher parameters passed to e.g. doGenoImport

Details

Import of DNA methylation and genotyping data is done separately:

DNA methylation data

DNA methylation data is imported using the RnBeads package. We use a default option setting commonly used for DNA methylation data obtained from the Illumina BeadArray series. If you want to specify further options, we refer to the rnb.options.

Genotyping data

Genotyping data is processed using PLINK. We focus on genotyping data generated with the Illumina BeadArray series and use default options. For further option settings, you should consult the qtlSetOption documentation.

You can specify the import type using qtlSetOption through the options meth.data.type and geno.data.type.

This function internally uses doMethImport and doGenoImport

Value

An object of type MethQTLInput-class with the methylation and genotyping information added.

Author(s)

Michael Scherer

Examples

meth.qtl.in <- loadMethQTLInput(system.file("extdata","reduced_methQTL",package="MAGAR"))
 meth.qtl.in

doMethQTL

Description

Function to compute methQTL given DNA methylation and genotyping data.

Usage

doMethQTL(
  meth.qtl,
  sel.covariates = NULL,
  p.val.cutoff = 1e-05,
  ncores = 1,
  cluster.submit = FALSE,
  out.dir = getwd(),
  default.options = TRUE
)

Arguments

meth.qtl

An object of type MethQTLInput-class on which methQTL computation is to be performed
sel.covariates

Covariates as column names of the sample annotation sheet stored in meth.qtl to be used for covariate adjustment.
p.val.cutoff

The p-value cutoff used for methQTL calling
ncores

The number of cores used.
cluster.submit

Flag indicating if jobs are to be distributed among a SGE compute cluster
out.dir

Output directory
default.options

Flag indicating if default options for cluster.cor.threshold, standard.deviation.gauss, and absolute.distance.cutoff should be loaded for the data set used. See the option settings in 'inst/extdata'.

Details

The process is split into 4 steps:

1

First the two matrices are split according to the chromosomes.

2

We then compute correlations among the CpGs and compute CpG correlation blocks.

3

In each of the CpG correlation blocks, linear models according to the linear.model.type qtlSetOption with the CpG methylation state of the reference CpG specified by representative.cpg.computation as output and the SNP genotype state and all possible covariates as input are computed.

4

For each of the CpG correlation blocks, we report the p-value of the representative CpG.

Currently, if qtlGetOption('cluster.architecture')=='sge' the function does not return a MethQTLResult object, but NULL, since monitoring finished jobs is hard through SLURM. After the jobs are finished (checked using squeue), the results can can be loaded from out.dir using loadMethQTLResult.

Value

An object of type MethQTLResult-class containing the called methQTL interactions.

Author(s)

Michael Scherer

See Also

doMethQTLChromosome

Examples

meth.qtl <- loadMethQTLInput(system.file("extdata","reduced_methQTL",package="MAGAR"))
meth.qtl.res <- doMethQTL(meth.qtl,p.val.cutoff=0.01)

doMethQTLChromosome

Description

This functions computes the methQTL interactions for a single chromosome

Usage

doMethQTLChromosome(
  meth.qtl,
  chrom,
  sel.covariates = NULL,
  p.val.cutoff = 1e-05,
  out.dir = NULL,
  ncores = 1
)

Arguments

meth.qtl

An Object of type MethQTLInput-class.
chrom

Character vector represeting the chromosome to be investigated.
sel.covariates

Covariates as column names of the sample annotation sheet stored in meth.qtl to be used for covariate adjustment.
p.val.cutoff

The p-value used for methQTL calling
out.dir

Optional argument specifying the output directory
ncores

The number of cores to be used

Value

A data frame with seven columns:

CpGs

The CpG ID chosen to be the representative CpG in the methQTL

SNP

The SNP ID (as rsNNNNNN) involved in the methQTL

Beta

The coefficient estimate of the linear model

P.value

The p-value associated with the coefficient estimate

Chromosome

The chromosome name

Position.CpG

The genomic position of the CpG

Position.SNP

The genomic position of the SNP

Distance

The distance between the CpG and the SNP

Author(s)

Michael Scherer

See Also

doMethQTL

Examples

meth.qtl <- loadMethQTLInput(system.file("extdata","reduced_methQTL",package="MAGAR"))
meth.qtl.res <- doMethQTLChromosome(meth.qtl,chrom="chr18",p.val.cutoff=0.01)

filterPval

Description

This functions filters the methQTL results according to a given p-value cutoff

Usage

## S4 method for signature 'MethQTLResult'
filterPval(object, p.val.cutoff = 0.01)

Arguments

object

The MethQTLResult-class object to be filtered
p.val.cutoff

The p-value cutoff to be employed

Value

The filtered MethQTLResult-class object

Author(s)

Michael Scherer

Examples

meth.qtl.res <- loadMethQTLResult(system.file("extdata","MethQTLResult_chr18",package="MAGAR"))
meth.qtl.res <- filterPval(meth.qtl.res)
meth.qtl.res

getAnno

Description

Returns genomic annotation information for the given dataset.

Usage

## S4 method for signature 'MethQTLInput'
getAnno(object, type = "meth")

## S4 method for signature 'MethQTLResult'
getAnno(object, type = "meth")

Arguments

object

An object of class MethQTLInput-class or MethQTLResult-class.
type

The type of annotation to be returned. Can either be 'meth' or 'geno' for methylation, and genotyping information, respectively.

Value

The genomic annotation as a data.frame.

Examples

meth.qtl <- loadMethQTLInput(system.file("extdata","reduced_methQTL",package="MAGAR"))
head(getAnno(meth.qtl,"meth"))
head(getAnno(meth.qtl,"geno"))
meth.qtl.res <- loadMethQTLResult(system.file("extdata","MethQTLResult_chr18",package="MAGAR"))
head(getAnno(meth.qtl.res,"meth"))
head(getAnno(meth.qtl.res,"geno"))

getCorrelationBlocks

Description

Returns the correlation blocks defined for the given dataset

Usage

## S4 method for signature 'MethQTLResult'
getCorrelationBlocks(object)

Arguments

object

An object of class MethQTLResult-class.

Value

A list object containing the correlation blocks.

Examples

meth.qtl.res <- loadMethQTLResult(system.file("extdata","MethQTLResult_chr18",package="MAGAR"))
head(getCorrelationBlocks(meth.qtl.res))

getGeno

Description

Returns genotyping information for the given dataset.

Usage

## S4 method for signature 'MethQTLInput'
getGeno(object, site = NULL, sample = NULL)

Arguments

object

An object of class MethQTLInput-class.
site

The sites to be selected either as a numeric or logical vector. If NULL all sites are returned.
sample

The samples to be selected either as a numeric or logical vector. If NULL all samples are returned.

Value

The genotyping matrix either as a matrix of HDF5Matrix.

Examples

meth.qtl <- loadMethQTLInput(system.file("extdata","reduced_methQTL",package="MAGAR"))
head(getGeno(meth.qtl))

getMethData

Description

Returns methylation information for the given dataset.

Usage

## S4 method for signature 'MethQTLInput'
getMethData(object, site = NULL, sample = NULL)

Arguments

object

An object of class MethQTLInput-class.
site

The sites to be selected either as a numeric or logical vector. If NULL all sites are returned.
sample

The samples to be selected either as a numeric or logical vector. If NULL all samples are returned.

Value

The methylation matrix either as a matrix of HDF5Matrix.

Examples

meth.qtl <- loadMethQTLInput(system.file("extdata","reduced_methQTL",package="MAGAR"))
head(getMethData(meth.qtl))

getOverlappingQTL

Description

This function merges the QTLs given and returns the methQTL table in a merged format.

Usage

getOverlappingQTL(meth.qtl.list, type = "SNP")

Arguments

meth.qtl.list

A list of MethQTLResult-class objects to be merged
type

The type of annotation to be overlapped. Needs to be 'SNP', 'CpG' or 'cor.block'

Value

A data.frame with the methQTL interactions and an additional column specifying where the interaction displayed has been found. This value is generated from the names() argument of meth.qtl.list.

Author(s)

Michael Scherer

Examples

meth.qtl.res.1 <- loadMethQTLResult(system.file("extdata","MethQTLResult_chr18",package="MAGAR"))
meth.qtl.res.2 <- meth.qtl.res.1
res <- getOverlappingQTL(list(A=meth.qtl.res.1,B=meth.qtl.res.2),type="SNP")

getOverlapUniverse

Description

This function overlaps results from a list of MethQTLResults and returns the union of all the input data points used.

Usage

getOverlapUniverse(meth.qtl.res, type)

Arguments

meth.qtl.res

An object of type MethQTLResult-class or a list of such objects
type

The type of annotation to be overlapped. Needs to be 'SNP', 'CpG' or 'cor.block'

Value

A list with two GRanges objects, one containing the overlapped set and the other the union of input data points as elements 'all.qtl' and 'all.input'

Author(s)

Michael Scherer

Examples

meth.qtl.res.1 <- loadMethQTLResult(system.file("extdata","MethQTLResult_chr18",package="MAGAR"))
meth.qtl.res.2 <- meth.qtl.res.1
res <- getOverlapUniverse(list(A=meth.qtl.res.1,B=meth.qtl.res.2),type="SNP")

getPheno

Description

Returns phenotypic information for the given dataset.

Usage

## S4 method for signature 'MethQTLInput'
getPheno(object)

Arguments

object

An object of class MethQTLInput-class.

Value

The phenotypic data either as a data.frame.

Examples

meth.qtl <- loadMethQTLInput(system.file("extdata","reduced_methQTL",package="MAGAR"))
head(getPheno(meth.qtl))

getResult

Description

Returns the methQTL results stores in the object.

Usage

## S4 method for signature 'MethQTLResult'
getResult(object, cor.blocks = NULL, na.rm = FALSE)

Arguments

object

An of type MethQTLResult-class.
cor.blocks

Correlation blocks as obtained using getCorrelationBlocks. Please note that the correlation blocks need to contain the CpG identifiers, so the MethQTLInput-class object needs to be provided to getCorrelationBlocks.
na.rm

Flag indicating if rows containing NA values are to be removed from the result.

Value

The methQTL results as a data.frame with each row being a methQTL.

Examples

meth.qtl.res <- loadMethQTLResult(system.file("extdata","MethQTLResult_chr18",package="MAGAR"))
head(getResult(meth.qtl.res))

getResultGWASMap

Description

Returns the methQTL results in the format used as input to GWAS-map and stores in the object.

Usage

## S4 method for signature 'MethQTLResult'
getResultGWASMap(object, meth.qtl)

Arguments

object

An of type MethQTLResult-class.
meth.qtl

An object of type MethQTLInput-class containing further information about the QTLs

Value

The methQTL results as a data.frame with each row being a methQTL.

Examples

meth.qtl.res <- loadMethQTLResult(system.file("extdata","MethQTLResult_chr18",package="MAGAR"))
meth.qtl <- loadMethQTLInput(system.file("extdata","reduced_methQTL",package="MAGAR"))
head(getResultGWASMap(meth.qtl.res,meth.qtl))

getSamples

Description

Returns the samples of the given dataset.

Usage

## S4 method for signature 'MethQTLInput'
getSamples(object)

Arguments

object

An object of class MethQTLInput-class.

Value

The samples of the dataset as a character vector.

Examples

meth.qtl <- loadMethQTLInput(system.file("extdata","reduced_methQTL",package="MAGAR"))
getSamples(meth.qtl)

getSpecificQTL

Description

This function returns the methQTL interactions specific for a result

Usage

getSpecificQTL(meth.qtl.res, meth.qtl.background, type = "SNP")

Arguments

meth.qtl.res

An object of type MethQTLResult-class for which specific QTLs are to be obtained.
meth.qtl.background

The background set as a list of MethQTLResult-class objects.
type

The type of annotation to be overlapped. Needs to be 'SNP', 'CpG' or 'cor.block'

Value

A data.frame of methQTL interactions sorted by the effect size.

Author(s)

Michael Scherer

Examples

meth.qtl.res.1 <- loadMethQTLResult(system.file("extdata","MethQTLResult_chr18",package="MAGAR"))
meth.qtl.res.2 <- meth.qtl.res.1
res <- getSpecificQTL(meth.qtl.res.1,list(A=meth.qtl.res.1,B=meth.qtl.res.2),type="SNP")

imputeMeth

Description

Replaces missing values in the DNA methylation data matrix by imputed values

Usage

## S4 method for signature 'MethQTLInput'
imputeMeth(object)

Arguments

object

An object of class MethQTLInput-class.

Value

The object with imputed values.

Examples

meth.qtl <- loadMethQTLInput(system.file("extdata","reduced_methQTL",package="MAGAR"))
meth.qtl.imp <- imputeMeth(meth.qtl)

joinMethQTLResult

Description

This function combines a list of MethQTLResult-class objects.

Usage

joinMethQTLResult(obj.list)

Arguments

obj.list

A list of MethQTLResult-class objects to be joined

Value

An object of type MethQTLResult-class containing the combined information

Author(s)

Michael Scherer

Examples

meth.qtl.res.1 <- loadMethQTLResult(system.file("extdata","MethQTLResult_chr18",package="MAGAR"))
meth.qtl.res.2 <- meth.qtl.res.1
meth.qtl.res <- joinMethQTLResult(list(meth.qtl.res.1,meth.qtl.res.2))

loadMethQTLInput

Description

This functions load a MethQTLInput-class object from disk.

Usage

loadMethQTLInput(path)

Arguments

path

Path to the directory that has been created by saveMethQTLInput,MethQTLInput-method.

Value

The object of type MethQTLInput-class that has been stored on disk.

Author(s)

Michael Scherer

Examples

meth.qtl <- loadMethQTLInput(system.file("extdata","reduced_methQTL",package="MAGAR"))
meth.qtl

loadMethQTLResult

Description

This functions load a MethQTLResult-class object from disk.

Usage

loadMethQTLResult(path)

Arguments

path

Path to the directory that has been created by saveMethQTLResult,MethQTLResult-method.

Value

The object of type MethQTLResult-class that has been stored on disk.

Author(s)

Michael Scherer

Examples

meth.qtl.res <- loadMethQTLResult(system.file("extdata","MethQTLResult_chr18",package="MAGAR"))
meth.qtl.res

MethQTLInput-class

Description

Class storing methQTL input data, such as DNA methylation and genotyping data, as well as sample metadata

Details

This class is the basis for computing methQTLs in the methQTL-package. It stores all the relevant information including methylation data and genotype data as a matrix or HDF5Matrix, the phenotypic data as a data frame and the genomic annotation of both the methylation sites and the SNP data.

Slots

meth.data

The methylation data as a numeric matrix of beta values or as an object of type HDF5Matrix

geno.data

The genotyping data as a numeric matrix of SNP genotypes (0=homozygote reference, 1=heterozygote, 2=homozygote alternative allele) or as an object of type HDF5Matrix

pheno.data

Phenotypic data describing the samples used in the study. Matches the dimensions of both meth.data and geno.data

anno.meth

Genomic annotation of the methylation sites as a data.frame. Has the same number of rows as meth.data.

anno.geno

Genomic annotation of the SNPs as a data.frame. Has the same number of rows as geno.data.

samples

The sample identifiers used both for meth.data and geno.data, and as the rownames of pheno.data.

assembly

The genome assembly used.

platform

The platform used to compute the methylation data.

disk.dump

Flag indicating if the matrices are stored on disk rather than in memory.

imputed

Flag indicating if genotype dataset has been imputed.

Methods

getMeth

Returns the methylation matrix.

getGeno

Returns the genotyping matrix.

getPheno

Returns the phenotypic information.

getAnno

Returns the genomic annotation.

saveMethQTLInput

Stores the object on disk.

imputeMeth

Imputes the DNA methylation data matrix

Author(s)

Michael Scherer

MethQTLResult-class

Description

Class storing methQTL analysis results and the associated genomic annotations

Details

This class stores the results of the methQTL analysis. It stores a data.frame with the methQTL results, and associated genomic annotations for both the methylation sites and SNPs.

Slots

result.frame

The methQTL results as a data.frame

anno.meth

Genomic annotation of the methylation sites as a data.frame.

anno.geno

Genomic annotation of the SNPs as a data.frame.

correlation.blocks

Correlation blocks determined from the methylation matrix.

method

The method used to call methQTL.

rep.type

Method used to determine representative CpGs from correlation blocks.

chr

Optional argument specifying if methQTL were called on a single chromosome.

Methods

getResult

Returns the methQTL results.

getAnno

Returns the genomic annotation.

Author(s)

Michael Scherer

overlapInputs

Description

Overlaps the input annotations

Usage

overlapInputs(meth.qtl.list, type)

Arguments

meth.qtl.list

A list of MethQTLInput-class or MethQTLResult-class objects to be overlapped
type

The type of annotation to be overlapped. Needs to be 'SNP', 'CpG' or 'cor.block'

Value

A data frame containing the annotations of the unique input values.

Author(s)

Michael Scherer

Examples

meth.qtl.1 <- loadMethQTLInput(system.file("extdata","reduced_methQTL",package="MAGAR"))
meth.qtl.2 <- meth.qtl.1
res <- overlapInputs(list(A=meth.qtl.1,B=meth.qtl.2),type="SNP")

overlapQTLs

Description

This function overlaps a list of methQTLs to determine which interactions are common.

Usage

overlapQTLs(meth.qtl.result.list, type)

Arguments

meth.qtl.result.list

A named list with each entry being an object of type MethQTLResult-class. The names are used in the visualization.
type

Determines if either the SNP (default), the CpG, or the correlation block 'cor.block' is to be visualized

Value

A list with length(meth.qtl.result.list) elements, containing IDs of methQTL interactions according to the option type.

Author(s)

Michael Scherer

Examples

meth.qtl.res.1 <- loadMethQTLResult(system.file("extdata","MethQTLResult_chr18",package="MAGAR"))
meth.qtl.res.2 <- meth.qtl.res.1
res <- overlapQTLs(list(A=meth.qtl.res.1,B=meth.qtl.res.2),type="SNP")

options.R

Description

This files contains code to generate the options of the methQTL package.

Usage

QTL.OPTIONS

Format

An object of class environment of length 36.

qtlAnnotationEnrichment

Description

This functions performs enrichment analysis using the Fisher's test for the methQTLs detected with respect to different genomic annotations.

Usage

qtlAnnotationEnrichment(
  meth.qtl.res,
  type = "SNP",
  annotation = "cpgislands",
  assembly = "hg19"
)

Arguments

meth.qtl.res

An object of type MethQTLResult-class or a list of such objects.
type

The type of methQTL to be visualized. Can be either 'SNP', 'CpG', or 'cor.block'
annotation

The genomic annotation to be used. Can be the ones available in rnb.region.types or "ctcf", "distal", "dnase", "proximal", "tfbs", "tss"
assembly

The assembly used. Only "hg19" (default) and "hg38" supported.

Details

We use all data points that have been used to calculate methQTLs as the background and compare the overlaps with the annotation of interest in comparison to the methQTLs that have been computed in case a MethQTLResult-class is provided. If a list of MethQTLResult-class objects is provided, the intersection between the methQTLs from all objects in the list is compared with the union of all interactions that have been tested.

Value

A list of two p-values named 'enrichment' for overrepresentation and 'depletion' for underrepresentation

Author(s)

Michael Scherer

Examples

meth.qtl.res <- loadMethQTLResult(system.file("extdata","MethQTLResult_chr18",package="MAGAR"))
res <- qtlAnnotationEnrichment(meth.qtl.res)

qtlBaseSubstitutionEnrichment

Description

This function tests for enrichment of a specific base substitution in the methQTL interactions.

Usage

qtlBaseSubstitutionEnrichment(meth.qtl.res, merge = FALSE)

Arguments

meth.qtl.res

An object of type MethQTLResult-class or a list of such objects.
merge

Flag indicating if 5' and 3' substitutions are to be merged or to be analyzed separately.

Details

The names of the list are e.g. A_G, which refers to a replacement of the reference base A with an A. Enrichment is computed using Fisher's exact test, using all SNP that have been used as input as the background.

Value

A list with one element for each potential base substitution containing the enrichment p-value.

Author(s)

Michael Scherer

Examples

meth.qtl.res <- loadMethQTLResult(system.file("extdata","MethQTLResult_chr18",package="MAGAR"))
res <- qtlBaseSubstitutionEnrichment(meth.qtl.res)

qtlDistanceScatterplot

Description

Computes a scatterplot between CpG-SNP distance with both effect size and p-value

Usage

qtlDistanceScatterplot(meth.qtl.result, out.dir = NULL, out.name = NULL)

Arguments

meth.qtl.result

An object of type MethQTLResult-class containing called methQTL
out.dir

If specified, the plot is stored as a pdf in this directory
out.name

Optional name for the resulting plot

Value

An object of type ggplot comparing the distance between CpG and SNP. Negative values indicate that the SNP is downstream of the CpG.

Author(s)

Michael Scherer

Examples

meth.qtl.res <- loadMethQTLResult(system.file("extdata","MethQTLResult_chr18",package="MAGAR"))
qtlDistanceScatterplot(meth.qtl.res)

qtlGetOption Print the value of the global option

Description

qtlGetOption Print the value of the global option

Usage

qtlGetOption(names)

Arguments

names

string or character vector containing the names of the options to be printed. All options are listed in qtlSetOption

Value

the option for the specified option

Author(s)

Michael Scherer

Examples

qtlGetOption("cluster.cor.threshold")

qtlJSON2options

Description

This function reads an option setting from a JSON file and applies them to the current session

Usage

qtlJSON2options(path)

Arguments

path

Path to a JSON file containing the options to be specified

Value

None

Author(s)

Michael Scherer

Examples

qtlJSON2options(system.file("extdata","qtl_options_probesEPIC.json",package="MAGAR"))

qtlManhattanPlot

Description

This function creates a manhattan plot for the given methQTL result

Usage

qtlManhattanPlot(meth.qtl.result, type = "CpG", stat = "p.val.adj.fdr")

Arguments

meth.qtl.result

An object of type MethQTLResult-class containing the methQTL
type

Determines if either the CpG (default) or the SNP is to be visualized
stat

Determines the statistic that is to be visualized. Can be either P.value, Beta or p.val.adj.fdr

Details

A plot is shown that contains chromosome-wise interactions.

Value

None

Author(s)

Michael Scherer

Examples

meth.qtl.res <- loadMethQTLResult(system.file("extdata","MethQTLResult_chr18",package="MAGAR"))
qtlManhattanPlot(meth.qtl.res)

qtlOptions2JSON

Description

This function stores the current options setting as a JSON file at the specified path

Usage

qtlOptions2JSON(path = file.path(getwd(), "methQTL_options.json"))

Arguments

path

A filename, to which the option setting is to be saved

Value

None

Author(s)

Michael Scherer

Examples

qtlSetOption('cluster.cor.threshold'=0.5)
qtlOptions2JSON("my_opts.json")
qtlJSON2options("my_opts.json")

qtlPlotBaseSubstitution

Description

This function returns an enrichment plot for the different base substitutions.

Usage

qtlPlotBaseSubstitution(meth.qtl.res, ...)

Arguments

meth.qtl.res

An object of type MethQTLResult-class or a list of such objects.
...

Further parameters passed to qtlBaseSubstitutionEnrichment

Value

None

Author(s)

Michael Scherer

See Also

qtlBaseSubstitutionEnrichment

Examples

meth.qtl.res <- loadMethQTLResult(system.file("extdata","MethQTLResult_chr18",package="MAGAR"))
qtlPlotBaseSubstitution(meth.qtl.res)

qtlPlotClusterSize

Description

This functions returns a histogram comprising the (genomic) sizes of the correlation blocks in the given objet.

Usage

qtlPlotClusterSize(meth.qtl.res, type = "count")

Arguments

meth.qtl.res

An object of type MethQTLResult-class
type

Either "genomic" or "count", for genomic size of the correlation block in base pairs or as the number of CpGs

Value

An object of type ggplot containing the histogram as a plot

Author(s)

Michael Scherer

Examples

meth.qtl.res <- loadMethQTLResult(system.file("extdata","MethQTLResult_chr18",package="MAGAR"))
qtlPlotClusterSize(meth.qtl.res)

qtlPlotSNPCpGInteraction

Description

Compares the methylation states of a given CpG for the genotype states availabe at the given SNP

Usage

qtlPlotSNPCpGInteraction(
  meth.qtl,
  cpg = NULL,
  snp = NULL,
  out.dir = NULL,
  meth.qtl.res = NULL,
  out.name = NULL
)

Arguments

meth.qtl

An object of type MethQTLInput-class containing the methylation and genotype information for the given CpG and the given SNP
cpg

The CpG identifier as a character (e.g. cg12345678)
snp

The SNP identifier as a character (e.g. rs12345678)
out.dir

If specified, the plot is stored as a pdf in this directory
meth.qtl.res

An optional argument of type MethQTLResult-class containing information on the results. If either cpg or snp are NULL, this function sorts the results by increasing p-value and the uses the best results for plotting.
out.name

Optional name for the resulting plot

Value

An object of type ggplot comparing the CpG methylation states as boxplots across the different genotype states

Author(s)

Michael Scherer

Examples

meth.qtl <- loadMethQTLInput(system.file("extdata","reduced_methQTL",package="MAGAR"))
qtlPlotSNPCpGInteraction(meth.qtl,cpg="cg19565884",snp="rs149871695")

qtlSetOption

Description

Change global options for methQTL calculation

Usage

qtlSetOption(
  rnbeads.options = NULL,
  meth.data.type = "idat.dir",
  geno.data.type = "plink",
  rnbeads.report = "temp",
  rnbeads.qc = FALSE,
  hdf5dump = FALSE,
  hardy.weinberg.p = 0.001,
  db.snp.ref = NULL,
  minor.allele.frequency = 0.05,
  missing.values.samples = 0.05,
  plink.geno = 0.1,
  impute.geno.data = FALSE,
  n.prin.comp = NULL,
  plink.path = NULL,
  fast.qtl.path = NULL,
  bgzip.path = NULL,
  tabix.path = NULL,
  correlation.type = "pearson",
  cluster.cor.threshold = 0.25,
  standard.deviation.gauss = 250,
  absolute.distance.cutoff = 5e+05,
  linear.model.type = "classial.linear",
  representative.cpg.computation = "row.medians",
  meth.qtl.type = "oneVSall",
  max.cpgs = 40000,
  cluster.architecture = "sge",
  cluster.config = c(h_vmem = "5G", mem_free = "5G"),
  n.permutations = 1000,
  compute.cor.blocks = TRUE,
  recode.allele.frequencies = FALSE,
  vcftools.path = NULL,
  imputation.user.token = NULL,
  imputation.reference.panel = "[email protected]",
  imputation.phasing.method = "shapeit",
  imputation.population = "eur"
)

Arguments

rnbeads.options

Path to an XML file specifying the RnBeads options used for data import. The default options are suitable for Illumina Beads Array data sets.
meth.data.type

Type of DNA methylation data used. Choices are listed in rnb.execute.import.
geno.data.type

The type of data to be imported. Can be either 'plink' for '.bed', '.bim', and '.fam' or '.dos' and 'txt' files or 'idat' for raw IDAT files.
rnbeads.report

Path to an existing directory, in which the preprocessing report of RnBeads is to be stored. Defaults to the temporary file.
rnbeads.qc

Flag indicating if the quality control module of RnBeads is to be executed.
hdf5dump

Flag indicating, if large matrices are to be stored on disk rather than in main memory using the HDF5Array package.
hardy.weinberg.p

P-value used for the markers to be excluded if they do not follow the Hardy-Weinberg equilibrium as implemented in PLINK.
db.snp.ref

Path to a locally stored version of dbSNP[3]. If this option is specified, the reference allele is determined from this file instead of from the allele frequencies of the dataset. This circumvents problems with some imputation methods. If NULL(default), recoding will not be performed.
minor.allele.frequency

Threshold for the minor allele frequency of the SNPs to be used in the analysis.
missing.values.samples

Threshold specifying how much missing values per SNP are allowed across the samples to be included in the analyis.
plink.geno

Threshold for missing values per SNP
impute.geno.data

Flag indicating if imputation of genotyping data is to be perfomed using the Michigan imputation server (https://imputationserver.sph.umich.edu/index.html)[2].
n.prin.comp

Number of principal components of the genetic data to be used as covariates in the methQTL calling. NULL means that no adjustment is conducted.
plink.path

Path to an installation of PLINK (also comes with the package)
fast.qtl.path

Path to an installation of fastQTL (comes with the package for Linux)
bgzip.path

Path to an installation of BGZIP (comes with the package for Linux)
tabix.path

Path to an installation of TABIX (comes with the package for Linux)
correlation.type

The type of correlation to be used. Please note that for type='pearson' (default) the more efficient implementation of correlation in the bigstatsr is used. Further available options are 'spearman' and 'kendall'.
cluster.cor.threshold

Threshold for CpG methylatin state correlation to be considered as connected in the distance graph used to compute the correlation clustering.
standard.deviation.gauss

Standard deviation of the Gauss distribution used to weight the correlation according to its distance.
absolute.distance.cutoff

Distance cutoff after which a CpG correlation is not considered anymore.
linear.model.type

Linear model type to be used. Can be either "categorical.anova" or "classical.linear". If 'meth.qtl.type'='fastQTL', this option is automatically set to 'fastQTL' see callMethQTLBlock for more informations.
representative.cpg.computation

Option specifying how reference CpGs per correlation block are to be computed. Available options are "row.medians" for the site that is the row median across the samples within the correlation block (for ties a random selection is performed), "mean.center" for an artifical site in the geometric center of the block with the average methylation level or "best.all" for the CpG with the best p-value across all of the CpGs in the correlation block.
meth.qtl.type

Option specifying how a methQTL interaction is computed. Since the package is based on correlation blocks, a single correlation block can be associated with either one SNP (meth.qtl.type='oneVSall'), with multiple SNPs (meth.qtl.type='allVSall'), or each correlation block can once be positively and once negatively correlated with a SNP genotype (meth.qtl.type='twoVSall'). Additionally, we provide the option to use (FastQTL)[1] as a methQTL mapping tool (option 'fastQTL').
max.cpgs

Maximum number of CpGs used in the computation (used to save memory). 40,000 is a reasonable default for machines with ~128GB of main memory. Should be smaller for smaller machines and larger for larger ones.
cluster.architecture

The type of HPC cluster architecture present. Currently supported are 'sge' and 'slurm'
cluster.config

Resource parameters needed to setup an SGE or SLURM cluster job. Includes h_vmem and mem_free for SGE and clock.limit and mem.size for SLURM. An example configuration for SLURM would be c("clock.limit"="1-0","mem.size"="10G") for 1 day of running time (format days:hours) and 10 GB of maximum memory usage. Additionally, 'n.cpus' can be specified as the SLURM option cpus-per-task
n.permutations

The number of permutations used to correct the p-values for multiple testing. See (http://fastqtl.sourceforge.net/) for further information.
compute.cor.blocks

Flag indicating if correlation blocks are to be called. If FALSE, each CpG is considered separately.
recode.allele.frequencies

Flag indicating if the reference allele is to be redefined according to the frequenciess found in the cohort investigated.
vcftools.path

Path to the installation of VCFtools. Necessary is the vcf-sort function in this folder.
imputation.user.token

The user token that is required for authorization with the Michigan imputation server. Please have a look at https://imputationserver.sph.umich.edu, create a user account and request a user token for access in your user profile.
imputation.reference.panel

The reference panel used for imputation. Please see https://imputationserver.readthedocs.io/en/latest/reference-panels/ for further information which panels are supported by the Michigan imputation server.
imputation.phasing.method

The phasing method employed by the Michigan imputation server. See https://imputationserver.readthedocs.io/en/latest/api/ for further information.
imputation.population

The population for the phasing method required by the Michigan imputation server. See https://imputationserver.readthedocs.io/en/latest/api/ for further information.

Value

None

Author(s)

Michael Scherer

References

1. Ongen, H., Buil, A., Brown, A. A., Dermitzakis, E. T., & Delaneau, O. (2016). Fast and efficient QTL mapper for thousands of molecular phenotypes. Bioinformatics, 32(10), 1479–1485. https://doi.org/10.1093/bioinformatics/btv722 2. Das S, Forer L, Schönherr S, Sidore C, Locke AE, et al. (2016). Next-generation genotype imputation service and methods. Nature Genetics 48, 1284–1287, https://doi.org/10.1038/ng.3656 3. Sherry, S. T. et al. (2001). dbSNP: the NCBI database of genetic variation. Nucleic Acids Res. 29, 308–311, https://doi.org/10.1093/nar/29.1.308.

Examples

qtlGetOption("rnbeads.report")
qtlSetOption(rnbeads.report=getwd())
qtlGetOption("rnbeads.report")

qtlTFBSMotifEnrichment

Description

This function performs TFBS enrichment analysis for the methQTL SNPs/CpGs detected and returns overrepresented binding motifs.

Usage

qtlTFBSMotifEnrichment(
  meth.qtl.res,
  type = "SNP",
  size = 500,
  assembly = "hg19",
  subsample = 1e+05,
  out.dir = getwd(),
  ...
)

Arguments

meth.qtl.res

An object of type MethQTLResult-class or a list of such objects
type

The type of methQTL to be visualized. Can be either 'SNP', 'CpG', or 'cor.block'
size

Motif enrichment is only supported for genomic regions. Therefore, we resize the invididual methQTL to genomic regions using a width of this size around the site of interest.
assembly

The assembly used. Only "hg19" and "hg38" supported
subsample

Integer specifying how many of the regions are to be subsamples from the universe.
out.dir

The output directory in which resulting plots will be stored.
...

Further parameters passed to findMotifFgBg

Details

This function is in part based on the tutorial for Motif discovery in https://compgenomr.github.io/book/motif-discovery.html. We use all data points that have been used to calculate methQTLs as the background and compare the overlaps with the annotation of interest in comparison to the methQTLs that have been computed in case a MethQTLResult-class is provided. If a list of MethQTLResult-class objects is provided, the intersection between the methQTLs from all objects in the list is compared with the union of all interactions that have been tested.

Value

A plot describing the TFB motif enrichment

Author(s)

Michael Scherer

Examples

meth.qtl.res <- loadMethQTLResult(system.file("extdata","MethQTLResult_chr18",package="MAGAR"))
res <- qtlTFBSMotifEnrichment(meth.qtl.res)

qtlUpsetPlot

Description

This function creates an UpSet plot from the given methQTL results

Usage

qtlUpsetPlot(meth.qtl.result.list, type = "SNP", ...)

Arguments

meth.qtl.result.list

A named list with each entry being an object of type MethQTLResult-class. The names are used in the visualization.
type

Determines if either the SNP (default), the CpG, or the correlation block 'cor.block' is to be visualized
...

Further argument passed to upset

Details

The plot is directly drawn and can be stored on disk using the known R graphic devices

Value

None

Author(s)

Michael Scherer

Examples

meth.qtl.res.1 <- loadMethQTLResult(system.file("extdata","MethQTLResult_chr18",package="MAGAR"))
meth.qtl.res.2 <- meth.qtl.res.1
qtlUpsetPlot(list(A=meth.qtl.res.1,B=meth.qtl.res.2))

qtlUpSetPlotCorBlocks

Description

This function overlaps correlation blocks for a list of methQTL results

Usage

qtlUpSetPlotCorBlocks(meth.qtl.res.list, ...)

Arguments

meth.qtl.res.list

A list of MethQTLResult-class objects, for which correlation blocks are to be overlapped
...

Further argument passed to upset

Details

This function draws an UpSetPlot for the overlaps directly from to the open graphics device

Value

None

Author(s)

Michael Scherer

Examples

meth.qtl.res.1 <- loadMethQTLResult(system.file("extdata","MethQTLResult_chr18",package="MAGAR"))
meth.qtl.res.2 <- meth.qtl.res.1
qtlUpSetPlotCorBlocks(list(A=meth.qtl.res.1,B=meth.qtl.res.2))

qtlUpSetPlotTagCpGs

Description

This function overlaps the tagCpGs for a list of methQTL results

Usage

qtlUpSetPlotTagCpGs(meth.qtl.res.list, ...)

Arguments

meth.qtl.res.list

A list of MethQTLResult-class objects, for which correlation blocks are to be overlapped
...

Further argument passed to upset

Details

This function draws an UpSetPlot for the overlaps directly from to the open graphics device

Value

None

Author(s)

Michael Scherer

Examples

meth.qtl.res.1 <- loadMethQTLResult(system.file("extdata","MethQTLResult_chr18",package="MAGAR"))
meth.qtl.res.2 <- meth.qtl.res.1
qtlUpSetPlotTagCpGs(list(A=meth.qtl.res.1,B=meth.qtl.res.2))

qtlVennPlot

Description

This function creates a venn plot from a list of methQTL results, showing the overlap between the interactions

Usage

qtlVennPlot(
  meth.qtl.result.list,
  out.folder,
  type = "SNP",
  out.name = NULL,
  ...
)

Arguments

meth.qtl.result.list

A named list with each entry being an object of type MethQTLResult-class. The names are used in the visualization.
out.folder

Required argument specifying the location to store the resulting plot
type

Determines if either the SNP (default), the CpG, or the correlation block 'cor.block' is to be visualized
out.name

Optional argument for the name of the plot on disk (ending needs to be .png)
...

Further argument passed to venn.diagram

Details

The plot can be stored on disk using out.folder and out.name

Value

None

Author(s)

Michael Scherer

Examples

meth.qtl.res.1 <- loadMethQTLResult(system.file("extdata","MethQTLResult_chr18",package="MAGAR"))
meth.qtl.res.2 <- meth.qtl.res.1
qtlVennPlot(list(A=meth.qtl.res.1,B=meth.qtl.res.2),out.folder=getwd())

saveMethQTLInput

Description

This functions stores a MethQTLInput object in disk.

Usage

## S4 method for signature 'MethQTLInput'
saveMethQTLInput(object, path)

Arguments

object

The MethQTLInput-class object to be stored on disk.
path

A path to a non-existing directory for files to be stored.

Value

None

Author(s)

Michael Scherer

Examples

meth.qtl <- loadMethQTLInput(system.file("extdata","reduced_methQTL",package="MAGAR"))
saveMethQTLInput(meth.qtl,"MethQTLInput")

saveMethQTLResult

Description

This functions stores a MethQTLInput object in disk.

Usage

## S4 method for signature 'MethQTLResult'
saveMethQTLResult(object, path)

Arguments

object

The MethQTLResult-class object to be stored on disk.
path

A path to a non-existing directory for files to be stored.

Value

None

Author(s)

Michael Scherer

Examples

meth.qtl.res <- loadMethQTLResult(system.file("extdata","MethQTLResult_chr18",package="MAGAR"))
saveMethQTLResult(meth.qtl.res,"MethQTLResult")