detectionP.RdCompute detection p-values. p-values are based on the distribution of the intensities of the negative control probes or the U (M) intensities observed for completely methylated (unmethylated) probes, respectively (Heiss and Just, 2019). detP_threshold generates a plot showing the number of undetected Y chromosome probes among male and female subjects for various p-value thresholds, in order to empirically choose a threshold. Finally, mask is masking all probes with detection p-values below the specified threshold. detectionP.minfi provides an implementation for RGChannelSet objects as used in the minfi package.
summits(beta)
detectionP(raw)
detectionP.neg(raw)
mask(raw, threshold)
eval_detP_cutoffs(raw, males = NULL, females = NULL)
detectionP.minfi(rgSet)Output of calling read_idats, must include component detP for mask and detP_threshold.
p-value threshold (arithmetic scale) above which oberservations are set to NA.
minfi rgSet object
Indices of male and female subjects
For detectionP and detectionP.neg a modified raw object with a detP component, a matrix of detection p-values, added. detectionP computes p-values on the linear scale, whereas detectionP.neg returns p-values on the log10 scale.
For detectionP.minfi a matrix of detection p-values.
For mask, a modified raw object, with undetected probes set to NA.
Vector of length two
Heiss JA, Just AC. Improved filtering of DNA methylation microarray data by detection p values and its impact on downstream analyses. Clinical Epigenetics (2019) 11:15 Return peaks of beta-value distribution
Return the locations of the two peaks (completly methylated and unmethylated CpG sites) of the beta-value distribution.