Containers for chromatographic and peak detection data
Source:R/functions-XChromatograms.R
, R/functions-XChromatogram.R
, R/methods-XChromatogram.R
, and 1 more
XChromatogram.Rd
The XChromatogram
object allows to store chromatographic data (e.g.
an extracted ion chromatogram) along with identified chromatographic peaks
within that data. The object inherits all functions from the Chromatogram()
object in the MSnbase
package.
Multiple XChromatogram
objects can be stored in a XChromatograms
object.
This class extends MChromatograms()
from the MSnbase
package and allows
thus to arrange chromatograms in a matrix-like structure, columns
representing samples and rows m/z-retention time ranges.
All functions are described (grouped into topic-related sections) after the Arguments section.
Usage
XChromatograms(data, phenoData, featureData, chromPeaks, chromPeakData, ...)
XChromatogram(
rtime = numeric(),
intensity = numeric(),
mz = c(NA_real_, NA_real_),
filterMz = c(NA_real_, NA_real_),
precursorMz = c(NA_real_, NA_real_),
productMz = c(NA_real_, NA_real_),
fromFile = integer(),
aggregationFun = character(),
msLevel = 1L,
chromPeaks,
chromPeakData
)
# S4 method for class 'XChromatogram'
show(object)
# S4 method for class 'XChromatogram'
chromPeaks(
object,
rt = numeric(),
mz = numeric(),
ppm = 0,
type = c("any", "within", "apex_within"),
msLevel
)
# S4 method for class 'XChromatogram'
chromPeaks(object) <- value
# S4 method for class 'XChromatogram,ANY'
plot(
x,
col = "#00000060",
lty = 1,
type = "l",
xlab = "retention time",
ylab = "intensity",
main = NULL,
peakType = c("polygon", "point", "rectangle", "none"),
peakCol = "#00000060",
peakBg = "#00000020",
peakPch = 1,
...
)
# S4 method for class 'XChromatogram'
filterMz(object, mz, ...)
# S4 method for class 'XChromatogram'
filterRt(object, rt, ...)
# S4 method for class 'XChromatogram'
hasChromPeaks(object)
# S4 method for class 'XChromatogram'
dropFilledChromPeaks(object)
# S4 method for class 'XChromatogram'
chromPeakData(object)
# S4 method for class 'XChromatogram'
chromPeakData(object) <- value
# S4 method for class 'XChromatogram,MergeNeighboringPeaksParam'
refineChromPeaks(object, param = MergeNeighboringPeaksParam())
# S4 method for class 'XChromatogram'
filterChromPeaks(object, method = c("keepTop"), ...)
# S4 method for class 'XChromatogram'
transformIntensity(object, FUN = identity)
# S4 method for class 'XChromatograms'
show(object)
# S4 method for class 'XChromatograms'
hasChromPeaks(object)
# S4 method for class 'XChromatograms'
hasFilledChromPeaks(object)
# S4 method for class 'XChromatograms'
chromPeaks(
object,
rt = numeric(),
mz = numeric(),
ppm = 0,
type = c("any", "within", "apex_within"),
msLevel
)
# S4 method for class 'XChromatograms'
chromPeakData(object)
# S4 method for class 'XChromatograms'
filterMz(object, mz, ...)
# S4 method for class 'XChromatograms'
filterRt(object, rt, ...)
# S4 method for class 'XChromatograms,ANY'
plot(
x,
col = "#00000060",
lty = 1,
type = "l",
xlab = "retention time",
ylab = "intensity",
main = NULL,
peakType = c("polygon", "point", "rectangle", "none"),
peakCol = "#00000060",
peakBg = "#00000020",
peakPch = 1,
...
)
# S4 method for class 'XChromatograms'
processHistory(object, fileIndex, type)
# S4 method for class 'XChromatograms'
hasFeatures(object, ...)
# S4 method for class 'XChromatograms'
dropFeatureDefinitions(object, ...)
# S4 method for class 'XChromatograms,PeakDensityParam'
groupChromPeaks(object, param)
# S4 method for class 'XChromatograms'
featureDefinitions(
object,
mz = numeric(),
rt = numeric(),
ppm = 0,
type = c("any", "within", "apex_within")
)
# S4 method for class 'XChromatograms,ANY,ANY,ANY'
x[i, j, drop = TRUE]
# S4 method for class 'XChromatograms'
featureValues(
object,
method = c("medret", "maxint", "sum"),
value = "into",
intensity = "into",
missing = NA,
...
)
# S4 method for class 'XChromatograms'
plotChromPeakDensity(
object,
param,
col = "#00000060",
xlab = "retention time",
main = NULL,
peakType = c("polygon", "point", "rectangle", "none"),
peakCol = "#00000060",
peakBg = "#00000020",
peakPch = 1,
simulate = TRUE,
...
)
# S4 method for class 'XChromatograms'
dropFilledChromPeaks(object)
# S4 method for class 'XChromatograms,MergeNeighboringPeaksParam'
refineChromPeaks(object, param = MergeNeighboringPeaksParam())
# S4 method for class 'XChromatograms'
filterChromPeaks(object, method = c("keepTop"), ...)
# S4 method for class 'XChromatograms'
transformIntensity(object, FUN = identity)
Arguments
- data
For
XChromatograms
:list
ofChromatogram
orXChromatogram
objects.- phenoData
For
XChromatograms
: either adata.frame
,AnnotatedDataFrame
orNAnnotatedDataFrame
describing the phenotypical information of the samples.- featureData
For
XChromatograms
: either adata.frame
orAnnotatedDataFrame
with additional information for each row of chromatograms.- chromPeaks
For
XChromatogram
:matrix
with required columns"rt"
,"rtmin"
,"rtmax"
,"into"
,"maxo"
and"sn"
. ForXChromatograms
:list
, same length thandata
, with the chromatographic peaks for each chromatogram. Each element has to be amatrix
, the ordering has to match the order of the chromatograms indata
.- chromPeakData
For
XChromatogram
:DataFrame
with optional additional annotations for each chromatographic peak. The number of rows has to match the number of chromatographic peaks.- ...
For
filterChromPeaks
: additional parameters defining how to filter chromatographic peaks. See function description below for details.- rtime
For
XChromatogram
:numeric
with the retention times (length has to be equal to the length ofintensity
).- intensity
For
XChromatogram
:numeric
with the intensity values (length has to be equal to the length ofrtime
).- mz
For
XChromatogram
:numeric(2)
representing the m/z value range (min, max) on which the chromatogram was created. This is supposed to contain the real range of m/z values in contrast to thefilterMz
below. ForchromPeaks
andfeatureDefinitions
:numeric(2)
defining the m/z range for which chromatographic peaks or features should be returned. ForfilterMz
:numeric(2)
defining the m/z range for which chromatographic peaks should be retained.#'- filterMz
For
XChromatogram
:numeric(2)
representing the m/z value range (min, max) that was used to filter the original object on m/z dimension. If not applicable usefilterMz = c(0, 0)
.- precursorMz
For
XChromatogram
:numeric(2)
for SRM/MRM transitions. Represents the mz of the precursor ion. See details for more information.- productMz
For
XChromatogram
:numeric(2)
for SRM/MRM transitions. Represents the mz of the product. See details for more information.- fromFile
For
XChromatogram
:integer(1)
the index of the file within theOnDiskMSnExp
orMSnExp
object from which the chromatogram was extracted.- aggregationFun
For
XChromatogram
:character(1)
specifying the function that was used to aggregate intensity values for the same retention time across the m/z range.- msLevel
For
XChromatogram
:integer
with the MS level from which the chromatogram was extracted. ForchromPeaks
andchromPeakData
: extract chromatographic peaks of a certain MS level.- object
An
XChromatogram
orXChromatograms
object.- rt
For
chromPeaks
andfeatureDefinitions
:numeric(2)
defining the retention time range for which chromatographic peaks or features should be returned. ForfilterRt
:numeric(2)
defining the retention time range to reduceobject
to.- ppm
For
chromPeaks
andfeatureDefinitions
:numeric(1)
defining a ppm to expand the provided m/z range.- type
For
chromPeaks
andfeatureDefinitions
:character(1)
defining which peaks or features to return ifrt
ormz
is provided:"any"
(default) return all peaks that are even partially overlapping withrt
,"within"
return peaks that are completely withinrt
and"apex_within"
return peaks which apex is withinrt
.For `plot`: what type of plot should be used for the chromatogram (such as `"l"` for lines, `"p"` for points etc), see help of [plot()] in the `graphics` package for more details. For `processHistory`: restrict returned processing steps to specific types. Use [processHistoryTypes()] to list all supported values.
- value
For
chromPeaks<-
: a numericmatrix
with required columns"rt"
,"rtmin"
,"rtmax"
,"into"
and"maxo"
.- x
For
plot
: anXChromatogram
orXChromatograms
object.- col
For
plot
: the color to be used to draw the chromatogram.- lty
For
plot
andplotChromPeakDensity
: the line type.- xlab
For
plot
andplotChromPeakDensity
: the x axis label.- ylab
For
plot
: the y axis label.- main
For
plot
andplotChromPeakDensity
: an optional title for the plot.- peakType
For
plot
andplotChromPeakDensity
:character(1)
defining how (and if) identified chromatographic peak within the chromatogram should be plotted. Options are"polygon"
(default): draw the peak borders with thepeakCol
color and fill the peak area with thepeakBg
color,"point"
: indicate the peak's apex with a point,"rectangle"
: draw a rectangle around the identified peak and"none"
: don't draw peaks.- peakCol
For
plot
andplotChromPeakDensity
: the foreground color for the peaks. ForpeakType = "polygon"
andpeakType = "rectangle"
this is the color for the border. UseNA
to not use a foreground color. This should either be a single color or a vector of colors with the same length thanchromPeaks(x)
has rows.- peakBg
For
plot
andplotChromPeakDensity
: the background color for the peaks. ForpeakType = "polygon"
andpeakType = "rectangle"
the peak are or rectangle will be filled with this color. UseNA
to skip. This should be either a single color or a vector of colors with the same length thanchromPeaks(x)
has rows.- peakPch
For
plot
andplotChromPeakDensity
: the point character to be used forpeakType = "point"
. Seeplot()
in thegraphics
package for more details.- param
For
groupChromPeaks
andplotChromPeakDensity
: aPeakDensityParam()
object with the settings for the peak density correspondence analysis algorithm.- method
For
featureValues
:character(1)
specifying the method to resolve multi-peak mappings within the sample sample, i.e. to select the representative peak for a feature for which more than one peak was assigned in one sample. Options are"medret"
(default): select the peak closest to the median retention time of the feature,"maxint"
: select the peak with the largest signal and"sum"
: sum the values of all peaks (only ifvalue
is"into"
or"maxo"
). ForfilterChromPeaks
:character(1)
defining the method that should be used to filter chromatographic peaks. See help onfilterChromPeaks
below for details.- FUN
For
transformIntensity
: a function to transform the intensity values ofobject
.- fileIndex
For
processHistory
: optionalinteger
specifying the index of the files/samples for which the ProcessHistory objects should be returned.- i
For
[
:integer
with the row indices to subset theXChromatograms
object.- j
For
[
:integer
with the column indices to subset theXChromatograms
object.- drop
For
[
:logical(1)
whether the dimensionality should be dropped (if possible). Defaults todrop = TRUE
, thus, if length ofi
andj
is 1 aXChromatogram
is returned. Note thatdrop
is ignored if length ofi
orj
is larger than 1, thus aXChromatograms
is returned.- missing
For
featureValues
: how missing values should be reported. Allowed values areNA
(default), anumeric(1)
to replaceNA
s with that value ormissing = "rowmin_half"
to replaceNA
s with half of the row's minimal (non-missing) value.- simulate
For
plotChromPeakDensity
:logical(1)
whether a correspondence analysis should be simulated based on the available data and the providedPeakDensityParam()
param
argument. See section Correspondence analysis for details.
Note
Highlighting the peak area(s) in an XChromatogram
or XChromatograms
object (plot
with peakType = "polygon"
) draws a polygon representing
the displayed chromatogram from the peak's minimal retention time to the
maximal retention time. If the XChromatograms
was extracted from an
XCMSnExp()
object with the chromatogram()
function this might not
represent the actual identified peak area if the m/z range that was
used to extract the chromatogram was larger than the peak's m/z.
Creation of objects
Objects can be created with the contructor function XChromatogram
and
XChromatograms
, respectively. Also, they can be coerced from
Chromatogram or MChromatograms()
objects using
as(object, "XChromatogram")
or as(object, "XChromatograms")
.
Filtering and subsetting
Besides classical subsetting with [
specific filter operations on
MChromatograms()
and XChromatograms
objects are available. See
filterColumnsIntensityAbove()
for more details.
[
allows to subset aXChromatograms
object by row (i
) and column (j
), withi
andj
being of typeinteger
. ThefeatureDefinitions
will also be subsetted accordingly and thepeakidx
column updated.filterMz
filters the chromatographic peaks within anXChromatogram
orXChromatograms
, if a column"mz"
is present in thechromPeaks
matrix. This would be the case if theXChromatogram
was extracted from anXCMSnExp()
object with thechromatogram()
function. All chromatographic peaks with their m/z within the m/z range defined bymz
will be retained. Also feature definitions (if present) will be subset accordingly. The function returns a filteredXChromatogram
orXChromatograms
object.filterRt
filters chromatogram(s) by the provided retention time range. All eventually present chromatographic peaks with their apex within the retention time range specified withrt
will be retained. Also feature definitions, if present, will be filtered accordingly. The function returns a filteredXChromatogram
orXChromatograms
object.
Accessing data
See also help of Chromatogram in the MSnbase
package for general
information and data access. The methods listed here are specific for
XChromatogram
and XChromatograms
objects.
chromPeaks
,chromPeaks<-
: extract or set the matrix with the chromatographic peak definitions. Parameterrt
allows to specify a retention time range for which peaks should be returned along with parametertype
that defines how overlapping is defined (parameter description for details). ForXChromatogram
objects the function returns amatrix
with columns"rt"
(retention time of the peak apex),"rtmin"
(the lower peak boundary),"rtmax"
(the upper peak boundary),"into"
(the ingegrated peak signal/area of the peak),"maxo"
(the maximum instensity of the peak and"sn"
(the signal to noise ratio). Note that, depending on the peak detection algorithm, the matrix may contain additional columns. ForXChromatograms
objects thematrix
contains also columns"row"
and"column"
specifying in which chromatogram ofobject
the peak was identified. Chromatographic peaks are ordered by row.chromPeakData
,chromPeakData<-
: extract or set theDataFrame()
with optional chromatographic peak annotations.hasChromPeaks
: infer whether aXChromatogram
(orXChromatograms
) has chromatographic peaks. ForXChromatogram
: returns alogical(1)
, forXChromatograms
: returns amatrix
, same dimensions thanobject
with eitherTRUE
orFALSE
if chromatographic peaks are available in the chromatogram at the respective position.hasFilledChromPeaks
: whether aXChromatogram
(or aXChromatogram
in aXChromatograms
) has filled-in chromatographic peaks. ForXChromatogram
: returns alogical(1)
, forXChromatograms
: returns amatrix
, same dimensions thanobject
with eitherTRUE
orFALSE
if chromatographic peaks are available in the chromatogram at the respective position.dropFilledChromPeaks
: removes filled-in chromatographic peaks. SeedropFilledChromPeaks()
help forXCMSnExp()
objects for more information.hasFeatures
: forXChromatograms
objects only: if correspondence analysis has been performed and m/z-rt feature definitions are present. Returns alogical(1)
.dropFeatureDefinitions
: forXChrmomatograms
objects only: delete any correspondence analysis results (and related process history).featureDefinitions
: forXChromatograms
objects only. Extract the results from the correspondence analysis (performed withgroupChromPeaks
). Returns aDataFrame
with the properties of the defined m/z-rt features: their m/z and retention time range. Columnspeakidx
androw
contain the index of the chromatographic peaks in thechromPeaks
matrix associated with the feature and the row in theXChromatograms
object in which the feature was defined. Similar to thechromPeaks
method it is possible to filter the returned feature matrix with themz
,rt
andppm
parameters.featureValues
: forXChromatograms
objects only. Extract the abundance estimates for the individuals features. Note that by default (with parametervalue = "index"
amatrix
of indices of the peaks in thechromPeaks
matrix associated to the feature is returned. To extract the integrated peak area usevalue = "into"
. The function returns amatrix
with one row per feature (infeatureDefinitions
) and each column being a sample (i.e. column ofobject
). For features without a peak associated in a certain sampleNA
is returned. This can be changed with themissing
argument of the function.filterChromPeaks
: filters chromatographic peaks inobject
depending on parametermethod
and method-specific parameters passed as additional arguments with...
. Available methods are:method = "keepTop"
: keep topn
(defaultn = 1L
) peaks in each chromatogram ordered by columnorder
(defaults toorder = "maxo"
). Parameterdecreasing
(defaultdecreasing = TRUE
) can be used to order peaks in descending (decreasing = TRUE
) or ascending (decreasing = FALSE
) order to keep the topn
peaks with largest or smallest values, respectively.
processHistory
: returns alist
of ProcessHistory objects representing the individual performed processing steps. Optional parameterstype
andfileIndex
allow to further specify which processing steps to return.
Manipulating data
transformIntensity
: transforms the intensity values of the chromatograms with provided functionFUN
. SeetransformIntensity()
in theMSnbase
package for details. ForXChromatogram
andXChromatograms
in addition to the intensity values also columns"into"
and"maxo"
in the object'schromPeaks
matrix are transformed by the same function.
Plotting and visualizing
plot
draws the chromatogram and highlights in addition any chromatographic peaks present in theXChromatogram
orXChromatograms
(unlesspeakType = "none"
was specified). To draw peaks in different colors a vector of color definitions with length equal tonrow(chromPeaks(x))
has to be submitted withpeakCol
and/orpeakBg
defining one color for each peak (in the order as peaks are inchromPeaks(x))
. For base peak chromatograms or total ion chromatograms it might be better to setpeakType = "none"
to avoid generating busy plots.plotChromPeakDensity
: visualize peak density-based correspondence analysis results. See section Correspondence analysis for more details.
Chromatographic peak detection
See findChromPeaks-Chromatogram-CentWaveParam for information.
After chromatographic peak detection it is also possible to refine
identified chromatographic peaks with the refineChromPeaks
method (e.g. to
reduce peak detection artifacts). Currently, only peak refinement using the
merge neighboring peaks method is available (see
MergeNeighboringPeaksParam()
for a detailed description of the approach.
Correspondence analysis
Identified chromatographic peaks in an XChromatograms
object can be grouped
into features with the groupChromPeaks
function. Currently, such a
correspondence analysis can be performed with the peak density method
(see groupChromPeaks for more details) specifying the algorithm settings
with a PeakDensityParam()
object. A correspondence analysis is performed
separately for each row in the XChromatograms
object grouping
chromatographic peaks across samples (columns).
The analysis results are stored in the returned XChromatograms
object
and can be accessed with the featureDefinitions
method which returns a
DataFrame
with one row for each feature. Column "row"
specifies in
which row of the XChromatograms
object the feature was identified.
The plotChromPeakDensity
method can be used to visualize peak density
correspondence results, or to simulate a peak density correspondence
analysis on chromatographic data. The resulting plot consists of two panels,
the upper panel showing the chromatographic data as well as the identified
chromatographic peaks, the lower panel the distribution of peaks (the peak
density) along the retention time axis. This plot shows each peak as a point
with it's peak's retention time on the x-axis, and the sample in which it
was found on the y-axis. The distribution of peaks along the retention time
axis is visualized with a density estimate. Grouped chromatographic peaks
are indicated with grey shaded rectangles. Parameter simulate
allows to
define whether the correspondence analysis should be simulated (
simulate=TRUE
, based on the available data and the provided
PeakDensityParam()
parameter class) or not (simulate=FALSE
). For the
latter it is assumed that a correspondence analysis has been performed with
the peak density method on the object
.
See examples below.
Abundance estimates for each feature can be extracted with the
featureValues
function using parameter value = "into"
to extract the
integrated peak area for each feature. The result is a matrix
, columns
being samples and rows features.
See also
findChromPeaks-centWave for peak
detection on MChromatograms()
objects.
Examples
## ---- Creation of XChromatograms ----
##
## Create a XChromatograms from Chromatogram objects
library(MSnbase)
dta <- list(Chromatogram(rtime = 1:7, c(3, 4, 6, 12, 8, 3, 2)),
Chromatogram(1:10, c(4, 6, 3, 4, 7, 13, 43, 34, 23, 9)))
## Create an XChromatograms without peak data
xchrs <- XChromatograms(dta)
## Create an XChromatograms with peaks data
pks <- list(matrix(c(4, 2, 5, 30, 12, NA), nrow = 1,
dimnames = list(NULL, c("rt", "rtmin", "rtmax", "into", "maxo", "sn"))),
NULL)
xchrs <- XChromatograms(dta, chromPeaks = pks)
## Create an XChromatograms from XChromatogram objects
dta <- lapply(dta, as, "XChromatogram")
chromPeaks(dta[[1]]) <- pks[[1]]
xchrs <- XChromatograms(dta, nrow = 1)
hasChromPeaks(xchrs)
#> 1 2
#> 1 TRUE FALSE
## Loading a test data set with identified chromatographic peaks
faahko_sub <- loadXcmsData("faahko_sub2")
## Subset the dataset to the first and third file.
xod_sub <- filterFile(faahko_sub, file = c(1, 3))
od <- as(xod_sub, "MsExperiment")
## Extract chromatograms for a m/z - retention time slice
chrs <- chromatogram(od, mz = 344, rt = c(2500, 3500))
chrs
#> MChromatograms with 1 row and 2 columns
#> 1 2
#> <Chromatogram> <Chromatogram>
#> [1,] length: 639 length: 639
#> phenoData with 2 variables
#> featureData with 4 variables
## --------------------------------------------------- ##
## Chromatographic peak detection ##
## --------------------------------------------------- ##
## Perform peak detection using CentWave
xchrs <- findChromPeaks(chrs, param = CentWaveParam())
xchrs
#> XChromatograms with 1 row and 2 columns
#> 1 2
#> <XChromatogram> <XChromatogram>
#> [1,] peaks: 2 peaks: 1
#> phenoData with 2 variables
#> featureData with 4 variables
#> - - - xcms preprocessing - - -
#> Chromatographic peak detection:
#> method: centWave
## Do we have chromatographic peaks?
hasChromPeaks(xchrs)
#> 1 2
#> 1 TRUE TRUE
## Process history
processHistory(xchrs)
#> [[1]]
#> Object of class "XProcessHistory"
#> type: Peak detection
#> date: Wed Oct 30 14:02:49 2024
#> info:
#> fileIndex: 1,2
#> Parameter class: CentWaveParam
#>
## The chromatographic peaks, columns "row" and "column" provide information
## in which sample the peak was identified.
chromPeaks(xchrs)
#> rt rtmin rtmax into intb maxo sn row column
#> [1,] 2589.015 2571.801 2612.490 592297.3 554533.9 27600 14 1 1
#> [2,] 2679.783 2646.919 2709.517 5210015.9 5071346.6 152320 30 1 1
#> [3,] 2682.914 2643.790 2731.427 5255689.5 4983388.9 125632 28 1 2
## Spectifically extract chromatographic peaks for one sample/chromatogram
chromPeaks(xchrs[1, 2])
#> rt rtmin rtmax into intb maxo sn
#> [1,] 2682.914 2643.79 2731.427 5255689 4983389 125632 28
## Plot the results
plot(xchrs)
## Plot the results using a different color for each sample
sample_colors <- c("#ff000040", "#00ff0040", "#0000ff40")
cols <- sample_colors[chromPeaks(xchrs)[, "column"]]
plot(xchrs, col = sample_colors, peakBg = cols)
## Indicate the peaks with a rectangle
plot(xchrs, col = sample_colors, peakCol = cols, peakType = "rectangle",
peakBg = NA)
## --------------------------------------------------- ##
## Correspondence analysis ##
## --------------------------------------------------- ##
## Group chromatographic peaks across samples
prm <- PeakDensityParam(sampleGroup = rep(1, 2))
res <- groupChromPeaks(xchrs, param = prm)
hasFeatures(res)
#> [1] TRUE
featureDefinitions(res)
#> DataFrame with 2 rows and 10 columns
#> mzmed mzmin mzmax rtmed rtmin rtmax npeaks
#> <numeric> <numeric> <numeric> <numeric> <numeric> <numeric> <numeric>
#> FT1 NA NA NA 2681.35 2679.78 2682.91 2
#> FT2 NA NA NA 2589.01 2589.01 2589.01 1
#> X1 peakidx row
#> <numeric> <list> <integer>
#> FT1 2 2,3 1
#> FT2 1 1 1
## Plot the correspondence results. Use simulate = FALSE to show the
## actual results. Grouped chromatographic peaks are indicated with
## grey shaded rectangles.
plotChromPeakDensity(res, simulate = FALSE)
## Simulate a correspondence analysis based on different settings. Larger
## bw will increase the smoothing of the density estimate hence grouping
## chromatographic peaks that are more apart on the retention time axis.
prm <- PeakDensityParam(sampleGroup = rep(1, 3), bw = 60)
plotChromPeakDensity(res, param = prm)
## Delete the identified feature definitions
res <- dropFeatureDefinitions(res)
hasFeatures(res)
#> [1] FALSE
library(MSnbase)
## Create a XChromatogram object
pks <- matrix(nrow = 1, ncol = 6)
colnames(pks) <- c("rt", "rtmin", "rtmax", "into", "maxo", "sn")
pks[, "rtmin"] <- 2
pks[, "rtmax"] <- 9
pks[, "rt"] <- 4
pks[, "maxo"] <- 19
pks[, "into"] <- 93
xchr <- XChromatogram(rtime = 1:10,
intensity = c(4, 8, 14, 19, 18, 12, 9, 8, 5, 2),
chromPeaks = pks)
xchr
#> Object of class: XChromatogram
#> length of object: 10
#> from file:
#> mz range: [NA, NA]
#> rt range: [1, 10]
#> MS level: 1
#> Identified chromatographic peaks (1):
#> rt rtmin rtmax into maxo sn
#> 4 2 9 93 19 NA
## Add arbitrary peak annotations
df <- DataFrame(peak_id = c("a"))
xchr <- XChromatogram(rtime = 1:10,
intensity = c(4, 8, 14, 19, 18, 12, 9, 8, 5, 2),
chromPeaks = pks, chromPeakData = df)
xchr
#> Object of class: XChromatogram
#> length of object: 10
#> from file:
#> mz range: [NA, NA]
#> rt range: [1, 10]
#> MS level: 1
#> Identified chromatographic peaks (1):
#> rt rtmin rtmax into maxo sn
#> 4 2 9 93 19 NA
chromPeakData(xchr)
#> DataFrame with 1 row and 3 columns
#> peak_id ms_level is_filled
#> <character> <integer> <logical>
#> 1 a 1 FALSE
## Extract the chromatographic peaks
chromPeaks(xchr)
#> rt rtmin rtmax into maxo sn
#> [1,] 4 2 9 93 19 NA
## Plotting of a single XChromatogram object
## o Don't highlight chromatographic peaks
plot(xchr, peakType = "none")
## o Indicate peaks with a polygon
plot(xchr)
## Add a second peak to the data.
pks <- rbind(chromPeaks(xchr), c(7, 7, 10, NA, 15, NA))
chromPeaks(xchr) <- pks
## Plot the peaks in different colors
plot(xchr, peakCol = c("#ff000080", "#0000ff80"),
peakBg = c("#ff000020", "#0000ff20"))
## Indicate the peaks as rectangles
plot(xchr, peakCol = c("#ff000060", "#0000ff60"), peakBg = NA,
peakType = "rectangle")
## Filter the XChromatogram by retention time
xchr_sub <- filterRt(xchr, rt = c(4, 6))
xchr_sub
#> Object of class: XChromatogram
#> length of object: 3
#> from file:
#> mz range: [NA, NA]
#> rt range: [4, 6]
#> MS level: 1
#> Identified chromatographic peaks (1):
#> rt rtmin rtmax into maxo sn
#> 4 2 9 93 19 NA
plot(xchr_sub)