MChromatograms {MSnbase} | R Documentation

## Container for multiple Chromatogram objects

### Description

The `MChromatograms` class allows to store `Chromatogram()` objects in a `matrix`-like two-dimensional structure.

### Usage

    MChromatograms(data, phenoData, featureData, ...)

    ## S4 method for signature 'MChromatograms'
    show(object)

    ## S4 method for signature 'MChromatograms,ANY,ANY,ANY'
    x[i, j, drop = FALSE]

    ## S4 replacement method for signature 'MChromatograms'
    x[i, j] <- value

    ## S4 method for signature 'MChromatograms,ANY'
    plot(
      x,
      col = "#00000060",
      lty = 1,
      type = "l",
      xlab = "retention time",
      ylab = "intensity",
      main = NULL,
      ...
    )

    ## S4 method for signature 'MChromatograms'
    phenoData(object)

    ## S4 method for signature 'MChromatograms'
    pData(object)

    ## S4 replacement method for signature 'MChromatograms,data.frame'
    pData(object) <- value

    ## S4 method for signature 'MChromatograms'
    x$name

    ## S4 replacement method for signature 'MChromatograms'
    x$name <- value

    ## S4 replacement method for signature 'MChromatograms'
    colnames(x) <- value

    ## S4 method for signature 'MChromatograms'
    sampleNames(object)

    ## S4 replacement method for signature 'MChromatograms,ANY'
    sampleNames(object) <- value

    ## S4 method for signature 'MChromatograms'
    isEmpty(x)

    ## S4 method for signature 'MChromatograms'
    featureNames(object)

    ## S4 replacement method for signature 'MChromatograms'
    featureNames(object) <- value

    ## S4 method for signature 'MChromatograms'
    featureData(object)

    ## S4 replacement method for signature 'MChromatograms,ANY'
    featureData(object) <- value

    ## S4 method for signature 'MChromatograms'
    fData(object)

    ## S4 replacement method for signature 'MChromatograms,ANY'
    fData(object) <- value

    ## S4 method for signature 'MChromatograms'
    fvarLabels(object)

    ## S4 replacement method for signature 'MChromatograms'
    rownames(x) <- value

    ## S4 method for signature 'MChromatograms'
    precursorMz(object)

    ## S4 method for signature 'MChromatograms'
    productMz(object)

    ## S4 method for signature 'MChromatograms'
    mz(object)

    ## S4 method for signature 'MChromatograms'
    polarity(object)

    ## S4 method for signature 'MChromatograms'
    bin(object, binSize = 0.5, breaks = numeric(), fun = max)

    ## S4 method for signature 'MChromatograms'
    clean(object, all = FALSE, na.rm = FALSE)

    ## S4 method for signature 'MChromatograms'
    normalize(object, method = c("max", "sum"))

    ## S4 method for signature 'MChromatograms'
    filterIntensity(object, intensity = 0, ...)

    ## S4 method for signature 'MChromatograms,Chromatogram'
    alignRt(x, y, method = c("closest", "approx"), ...)

    ## S4 method for signature 'MChromatograms'
    c(x, ...)

### Arguments

`data` | for `MChromatograms`: a `list` of `Chromatogram()` objects.
`phenoData` | for `MChromatograms`: either a `data.frame`, `AnnotatedDataFrame` describing the phenotypical information of the samples.
`featureData` | for `MChromatograms`: either a `data.frame` or `AnnotatedDataFrame` with additional information for each row of chromatograms.
`...` | for `MChromatograms`: additional parameters to be passed to the `matrix` constructor, such as `nrow`, `ncol` and `byrow`.
`object` | a `MChromatograms` object.
`x` | for all methods: a `MChromatograms` object.
`i` | for `[`: `numeric`, `logical` or `character` defining which row(s) to extract.
`j` | for `[`: `numeric`, `logical` or `character` defining which columns(s) to extract.
`drop` | for `[`: `logical(1)` whether to drop the dimensionality of the returned object (if possible). The default is `drop = FALSE`, i.e. each subsetting returns a `MChromatograms` object (or a `Chromatogram` object if a single element is extracted).
`value` | for `[<-`: the replacement object(s). Can be a `list` of [Chromatogram()`objects or, if length of`i`and`j`are 1, a single`Chromatogram' object.
    For `pData<-`: a `data.frame` with the number of rows matching
    the number of columns of `object`.

    For `colnames`: a `character` with the new column names.
`col` | for `plot`: the color to be used for plotting. Either a vector of length 1 or equal to `ncol(x)`.
`lty` | for `plot`: the line type (see `plot` in the `graphics` package for more details). Can be either a vector of length 1 or of length equal to `ncol(x)`.
`type` | for `plot`: the type of plot (see `plot` from the `graphics` package for more details). Can be either a vector of length 1 or of length equal to `ncol(x)`.
`xlab` | for `plot`: the x-axis label.
`ylab` | for `plot`: the y-axis label.
`main` | for `plot`: the plot title. If not provided the mz range will be used as plot title.
`name` | for `$`, the name of the pheno data column.
`binSize` | for `bin`: `numeric(1)` with the size of the bins (in seconds).
`breaks` | For `bin`: `numeric` defining the bins. Usually not required as the function calculates the bins automatically based on `binSize` and the retention time range of chromatograms in the same row.
`fun` | for `bin`: function to be used to aggregate the intensity values falling within each bin.
`all` | for `clean`: `logical(1)` whether all 0-intensities should be removed (`all = TRUE`), or whether 0-intensities adjacent to peaks should be kept (`all = FALSE`; default).
`na.rm` | for `clean`: `logical(1)` whether all `NA` intensities should be removed prior to clean 0-intensity data points.
`method` | `character(1)`. For `normalise`: defining whether each chromatogram should be normalized to its maximum signal (`method = "max"`) or total signal (`method = "sum"`). For `alignRt`: alignment methods (see documentation for `alignRt` in the `Chromatogram()` help page. Defaults to `method = "closest"`.
`intensity` | for `filterIntensity`: `numeric(1)` or `function` to use to filter intensities. See description for details.
`y` | for `alignRt`: a `Chromatogram()` object against which `x` should be aligned against.

### Details

The `MChromatograms` class extends the base `matrix` class and hence allows to store `Chromatogram()` objects in a two-dimensional array. Each row is supposed to contain `Chromatogram` objects for one MS data slice with a common m/z and rt range. Columns contain `Chromatogram` objects from the same sample.

### Value

For `[`: the subset of the `MChromatograms` object. If a single element is extracted (e.g. if `i` and `j` are of length 1) a `Chromatogram()` object is returned. Otherwise (if `drop = FALSE`, the default, is specified) a `MChromatograms` object is returned. If `drop = TRUE` is specified, the method returns a `list` of `Chromatogram` objects.

    For `phenoData`: an `AnnotatedDataFrame` representing the
    pheno data of the object.

    For `pData`: a `data.frame` representing the pheno data of
    the object.

    For `$`: the value of the corresponding column in the pheno data
    table of the object.

    For all other methods see function description.

### Object creation

`MChromatograms` are returned by a `chromatogram()` function from an `MSnExp` or `OnDiskMSnExp`. Alternatively, the `MChromatograms` constructor function can be used.

### Data access

- `$` and `$<-`: get or replace individual columns of the object's phenodata.

- `colnames` and `colnames<-`: replace or set the column names of the `MChromatograms` object. Does also set the `rownames` of the `phenoData`.

- `fData`: return the feature data as a `data.frame`.

- `fData<-`: replace the object's feature data by passing a `data.frame`.

- `featureData`: return the feature data.

- `featureData<-`: replace the object's feature data.

- `featureNames`: returns the feature names of the `MChromatograms` object.

- `featureNames<-`: set the feature names.

- `fvarLabels`: return the feature data variable names (i.e. column names).

- `isEmpty`: returns `TRUE` if the `MChromatograms` object or all of its `Chromatogram` objects is/are empty or contain only `NA` intensities.

- `mz`: returns the m/z for each row of the `MChromatograms` object as a two-column `matrix` (with columns `"mzmin"` and `"mzmax"`).

- `pData`: accesses the phenotypical description of the samples. Returns a `data.frame`.

- `pData<-`: replace the phenotype data.

- `phenoData`: accesses the phenotypical description of the samples. Returns an `AnnotatedDataFrame` object.

- `polarity`: returns the polarity of the scans/chromatograms: `1`, `0` or `-1` for positive, negative or unknown polarity.

- `precursorMz`: return the precursor m/z from the chromatograms. The method returns a `matrix` with 2 columns (`"mzmin"` and `"mzmax"`) and as many rows as there are rows in the `MChromatograms` object. Each row contains the precursor m/z of the chromatograms in that row. An error is thrown if the chromatograms within one row have different precursor m/z values.

- `productMz`: return the product m/z from the chromatograms. The method returns a `matrix` with 2 columns (`"mzmin"` and `"mzmax"`) and as many rows as there are rows in the `MChromatograms` object. Each row contains the product m/z of the chromatograms in that row. An error is thrown if the chromatograms within one row have different product m/z values.

- `rownames<-`: replace the rownames (and featureNames) of the object.

### Data subsetting, combining and filtering

- `[` subset (similar to a `matrix`) by row and column (with parameters `i` and `j`).

- `[<-` replace individual or multiple elements. `value` has to be either a single `Chromatogram` obhect or a `list` of `Chromatogram` objects.

- `c` concatenate (row-wise) `MChromatogram` objects with the same number of samples (columns).

- `filterIntensity`: filter each `Chromatogram()` object within the `MChromatograms` removing data points with intensities below the user provided threshold. If `intensity` is a `numeric` value, the returned chromatogram will only contain data points with intensities > `intensity`. In addition it is possible to provide a function to perform the filtering. This function is expected to take the input `Chromatogram` (`object`) and to return a logical vector with the same length then there are data points in `object` with `TRUE` for data points that should be kept and `FALSE` for data points that should be removed. See the `filterIntensity` documentation in the `Chromatogram()` help page for details and examples.

### Data processing and manipulation

- `alignRt`: align all chromatograms in an `MChromatograms` object against the chromatogram specified with `y`. See documentation on `alignRt` in the `Chromatogram()` help page.

- `bin`: aggregates intensity values of chromatograms in discrete bins along the retention time axis. By default, individual `Chromatogram` objects of one row are binned into the same bins. The function returns a `MChromatograms` object with binned chromatograms.

- `clean`: removes 0-intensity data points. Either all of them (with `all = TRUE`) or all except those adjacent to non-zero intensities (`all = FALSE`; default). See `clean()` documentation for more details and examples.

- `normalize`, `normalise`: normalises the intensities of a chromatogram by dividing them either by the maximum intensity (`method = "max"`) or total intensity (`method = "sum"`) of the chromatogram.

### Data visualization

- `plot`: plots a `MChromatograms` object. For each row in the object one plot is created, i.e. all `Chromatogram()` objects in the same row are added to the same plot. If `nrow(x) > 1` the plot area is split into `nrow(x)` sub-plots and the chromatograms of one row are plotted in each.

### Author(s)

Johannes Rainer

### See Also

`Chromatogram()] for the class representing chromatogram data. [chromatogram()] for the method to extract a` MChromatograms`object from a`MSnExp`or`OnDiskMSnExp`object. [readSRMData()` for the function to read chromatographic data of an SRM/MRM experiment.

### Examples

    ## Creating some chromatogram objects to put them into a MChromatograms object
    ints <- abs(rnorm(25, sd = 200))
    ch1 <- Chromatogram(rtime = 1:length(ints), ints)
    ints <- abs(rnorm(32, sd = 90))
    ch2 <- Chromatogram(rtime = 1:length(ints), ints)
    ints <- abs(rnorm(19, sd = 120))
    ch3 <- Chromatogram(rtime = 1:length(ints), ints)
    ints <- abs(rnorm(21, sd = 40))
    ch4 <- Chromatogram(rtime = 1:length(ints), ints)

    ## Create a MChromatograms object with 2 rows and 2 columns
    chrs <- MChromatograms(list(ch1, ch2, ch3, ch4), nrow = 2)
    chrs

    ## Extract the first element from the second column. Extracting a single
    ## element always returns a Chromatogram object.
    chrs[1, 2]

    ## Extract the second row. Extracting a row or column (i.e. multiple elements
    ## returns by default a list of Chromatogram objects.
    chrs[2, ]

    ## Extract the second row with drop = FALSE, i.e. return a MChromatograms
    ## object.
    chrs[2, , drop = FALSE]

    ## Replace the first element.
    chrs[1, 1] <- ch3
    chrs

    ## Add a pheno data.
    pd <- data.frame(name = c("first sample", "second sample"),
        idx = 1:2)
    pData(chrs) <- pd

    ## Column names correspond to the row names of the pheno data
    chrs

    ## Access a column within the pheno data
    chrs$name

    ## Access the m/z ratio for each row; this will be NA for the present
    ## object
    mz(chrs)

    ## Data visualization

    ## Create some random Chromatogram objects
    ints <- abs(rnorm(123, mean = 200, sd = 32))
    ch1 <- Chromatogram(rtime = seq_along(ints), intensity = ints, mz = 231)
    ints <- abs(rnorm(122, mean = 250, sd = 43))
    ch2 <- Chromatogram(rtime = seq_along(ints), intensity = ints, mz = 231)
    ints <- abs(rnorm(125, mean = 590, sd = 120))
    ch3 <- Chromatogram(rtime = seq_along(ints), intensity = ints, mz = 542)
    ints <- abs(rnorm(124, mean = 1200, sd = 509))
    ch4 <- Chromatogram(rtime = seq_along(ints), intensity = ints, mz = 542)

    ## Combine into a 2x2 MChromatograms object
    chrs <- MChromatograms(list(ch1, ch2, ch3, ch4), byrow = TRUE, ncol = 2)

    ## Plot the second row
    plot(chrs[2, , drop = FALSE])

    ## Plot all chromatograms
    plot(chrs, col = c("#ff000080", "#00ff0080"))

[Package MSnbase version 2.18.0 Index]