MS Data Analysis

Description Usage Arguments Details Value Author(s) Examples

Use "democracy" to determine the average m/z and RT deviations for a grouped xcmsSet, and dependency on sample or absolute m/z

1	plotQC(object, sampNames, sampColors, sampOrder, what)

`object`	A grouped `xcmsSet`
`sampNames`	Override sample names (e.g. with simplified names)
`sampColors`	Provide a set of colors (default: monochrome ?)
`sampOrder`	Override the order of samples, e.g. to bring them in order of measurement to detect time drift
`what`	A vector of which QC plots to generate. "mzdevhist": histogram of mz deviations. Should be gaussian shaped. If it is multimodal, then some peaks seem to have a systematically higher m/z deviation "rtdevhist": histogram of RT deviations. Should be gaussian shaped. If it is multimodal, then some peaks seem to have a systematically higher RT deviation "mzdevmass": Shows whether m/z deviations are absolute m/z dependent, could indicate miscalibration "mzdevtime": Shows whether m/z deviations are RT dependent, could indicate instrument drift "mzdevsample": median mz deviation for each sample, indicates outliers "rtdevsample": median RT deviation for each sample, indicates outliers

plotQC() is a warpper to create a set of diagnostic plots. For the m/z deviations, the median of all m/z withon one group are assumed.

List with four matrices, each of dimension features * samples: "mz": median mz deviation for each sample "mzdev": median mz deviation for each sample "rt": median RT deviation for each sample "rtdev": median RT deviation for each sample

Michael Wenk, Michael Wenk <michael.wenk@student.uni-halle.de>

library(faahKO)
xsg <- group(faahko)

plotQC(xsg, what="mzdevhist")
plotQC(xsg, what="rtdevhist")
plotQC(xsg, what="mzdevmass")
plotQC(xsg, what="mzdevtime")
plotQC(xsg, what="mzdevsample")
plotQC(xsg, what="rtdevsample")