MoskalevCalibrationPlot: Moskalev calibration plots

In lb664/MethylCal: MethylCal: Bayesian Calibration of Methylation Levels

Description

Visualisation of Moskalev calibration of the standard control experiment.

Usage

MoskalevCalibrationPlot(data, Target = NULL, ModA = FALSE,
  ModB = TRUE, level = 0.95, dir = NULL, cex_par = 1.25)

Arguments

data	Formatted input data frame obtained from the function Formatting.
Target	Name of the target DMR/CpG island/gene to be visualised.
ModA	Extension of Warnecke's calibration curve (Warnecke et al., 1997) by Moskalev et al. (2011). Since default value is codeModA = FALSE, results of this extension do not appear. To show results, select ModA = TRUE.
ModB	Moskalev's cubic polynomial calibration curve (Moskalev et al., 2011). Default value is ModB = TRUE.
level	Level of significance of Moskalev's cubic polynomial prediction interval.
dir	In Unix-specific OS, user-specified directory where the plots in pdf format are saved. If the directory is not specified, figures are saved in the current working directory.
cex_par	Number indicating the amount by which plotting text and symbols should be scaled relative to the default (cex_par = 1).

Value

This function returns four plots. The first scatterplot depicts the values of the recorded apparent methylation levels at each Actual Methylation Percentage (AMP) with superimposed Moskalev's cubic polynomial calibration curve (Moskalev et al., 2011) for each CpG (red dashed line). The second plot presents the apparent methylation levels at consecutive CpGs stratified by AMPs with superimposed the predicted values (red dashed line) as well as the (1-level)% prediction interval (dashed-dotted red lines). The third plot is the scatterplot of the corrected methylation levels at each AMP for all CpGs within a DRM/CpG island/gene. Finally, the fourth plot is the hyperbolic coefficient (Moskalev et al., 2011) of the corrected methylation levels regressed on the AMPs for each CpG.

In Unix-specific OS, figures are saved in the current directory, unless otherwise specified by the user, in pdf format. In Windows OS, figures are printed on the screen.

References

Ochoa E, Zuber V, Fernandez-Jimenez N, Bilbao JR, Clark GR, Maher ER and Bottolo L. MethylCal: Bayesian calibration of methylation levels. Submitted. 2019.

Moskalev EA, Zavgorodnij MG, Majorova SP, Vorobjev IA, Jandaghi P, Bure IV, Hoheisel JD. Correction of PCR-bias in quantitative DNA methylation studies by means of cubic polynomial regression. Nucleic Acids Res. 2011; 39(11):e77. (PubMed)

Examples

data(BWS_data)
AMP = c(0, 25, 50, 75, 100)
data = Formatting(BWS_data, AMP = AMP)
MoskalevCalibrationPlot(data, Target = "KCNQ1OT1")

data(Celiac_data)
AMP = c(0, 12.5, 25, 37.5, 50, 62.5, 87.5, 100)
data = Formatting(Celiac_data, AMP = AMP)
MoskalevCalibrationPlot(data, Target = "NFKBIA", level = 0.99)

lb664/MethylCal documentation built on May 23, 2019, 4:02 a.m.