MS Data Analysis

Description Usage Arguments Author(s) See Also Examples

Plot the difference between the adjusted and the raw retention time (y-axis) for each file along the (adjusted or raw) retention time (x-axis). If alignment was performed using the adjustRtime-peakGroups method, also the features (peak groups) used for the alignment are shown.

plotAdjustedRtime(object, col = "#00000080", lty = 1, type = "l",
  adjustedRtime = TRUE, xlab = ifelse(adjustedRtime, yes =
  expression(rt[adj]), no = expression(rt[raw])),
  ylab = expression(rt[adj] - rt[raw]), peakGroupsCol = "#00000060",
  peakGroupsPch = 16, peakGroupsLty = 3, ylim, ...)

`object`	A `XCMSnExp` object with the alignment results.
`col`	colors to be used for the lines corresponding to the individual samples.
`lty`	line type to be used for the lines of the individual samples.
`type`	plot type to be used. See help on the `par` function for supported values.
`adjustedRtime`	logical(1) whether adjusted or raw retention times should be shown on the x-axis.
`xlab`	the label for the x-axis.
`ylab`	the label for the y-axis.
`peakGroupsCol`	color to be used for the peak groups (only used if alignment was performed using the `adjustRtime-peakGroups` method.
`peakGroupsPch`	point character (`pch`) to be used for the peak groups (only used if alignment was performed using the `adjustRtime-peakGroups` method.
`peakGroupsLty`	line type (`lty`) to be used to connect points for each peak groups (only used if alignment was performed using the `adjustRtime-peakGroups` method.
`ylim`	optional `numeric(2)` with the upper and lower limits on the y-axis.
`...`	Additional arguments to be passed down to the `plot` function.

Johannes Rainer

adjustRtime for all retention time correction/ alignment methods.

## Below we perform first a peak detection (using the matchedFilter
## method) on some of the test files from the faahKO package followed by
## a peak grouping and retention time adjustment using the "peak groups"
## method
library(faahKO)
library(xcms)
fls <- dir(system.file("cdf/KO", package = "faahKO"), recursive = TRUE,
           full.names = TRUE)

## Reading 2 of the KO samples
raw_data <- readMSData(fls[1:2], mode = "onDisk")

## Perform the peak detection using the matchedFilter method.
mfp <- MatchedFilterParam(snthresh = 20, binSize = 1)
res <- findChromPeaks(raw_data, param = mfp)

## Performing the peak grouping using the "peak density" method.
p <- PeakDensityParam(sampleGroups = c(1, 1))
res <- groupChromPeaks(res, param = p)

## Perform the retention time adjustment using peak groups found in both
## files.
fgp <- PeakGroupsParam(minFraction = 1)
res <- adjustRtime(res, param = fgp)

## Visualize the impact of the alignment. We show both versions of the plot,
## with the raw retention times on the x-axis (top) and with the adjusted
## retention times (bottom).
par(mfrow = c(2, 1))
plotAdjustedRtime(res, adjusted = FALSE)
grid()
plotAdjustedRtime(res)
grid()