plot.MatrixEQTL {MatrixEQTL}

Plot histogram or QQ-plot of all p-values

Description

This method plots a histogram or QQ-plot of p-values for all tests performed by Matrix_eQTL_engine.

Usage

## S3 method for class 'MatrixEQTL'
plot(
    x,
    cex = 0.5,
    pch = 19,
    xlim = NULL,
    ylim = NULL,
    main = NULL,
    ...)

Arguments

x

An object returned by Matrix_eQTL_engine.

cex

A numerical value giving the amount by which plotting text and symbols should be magnified relative to the default.

pch

Plotting "character", i.e., symbol to use. See points.

xlim

Set the range of the horisontal axis.

ylim

Set the range of the vertical axis.

main

Plot title.

...

Further graphical parameters passed to lines and points.

Details

The plot type (histogram vs. QQ-plot) is determined by the pvalue.hist parameter in the call of Matrix_eQTL_engine function.

Value

The method does not return any value.

Note

The sample code below produces figures like these:

Histogram:

QQ-plot:

Author(s)

Andrey A Shabalin [e-mail]

References

The package website: http://www.bios.unc.edu/research/genomic_software/Matrix_eQTL/

See Also

See Matrix_eQTL_engine for reference and sample code.

Examples

library(MatrixEQTL)

# Number of samples
n = 100 

# Number of variables
ngs = 2000

# Common signal in all variables
pop = 0.2*rnorm(n)

# data matrices
snps.mat = matrix(rnorm(n*ngs), ncol = ngs) + pop
gene.mat = matrix(rnorm(n*ngs), ncol = ngs) + pop + snps.mat*((1:ngs)/ngs)^9/2

# data objects for Matrix eQTL engine
snps1 = SlicedData$new( t( snps.mat ) )
gene1 = SlicedData$new( t( gene.mat ) )
cvrt1 = SlicedData$new( )
rm(snps.mat, gene.mat)

# Slice data in blocks of 500 variables
snps1$ResliceCombined(500)
gene1$ResliceCombined(500)

# Produce no output files
filename = NULL # tempfile()

# Perform analysis recording information for a histogram
meh = Matrix_eQTL_engine(
    snps = snps1, 
    gene = gene1, 
    cvrt = cvrt1, 
    output_file_name = filename, 
    pvOutputThreshold = 1e-100, 
    useModel = modelLINEAR, 
    errorCovariance = numeric(), 
    verbose = TRUE,
    pvalue.hist = 100)
    
plot(meh, col="grey")

# Perform analysis recording information for a QQ-plot
meq = Matrix_eQTL_engine(
    snps = snps1, 
    gene = gene1, 
    cvrt = cvrt1, 
    output_file_name = filename,
    pvOutputThreshold = 1e-6, 
    useModel = modelLINEAR, 
    errorCovariance = numeric(), 
    verbose = TRUE,
    pvalue.hist = "qqplot")
    
plot(meq)