peaklist-class {IPPD} | R Documentation

## "Peaklist"

### Description

Object returned from a call to getPeaklist.

### Slots

peaklist

  A `matrix` with rows equal to the number of peak patterns used in fitting and five columns. For each row (pattern), the first column contains the initial position of the peak pattern (`loc_init`, in Thomson), the second one contains the position of the most intense peak within a peak pattern (`loc_most_intense`, in Thomson), the third one contains the charge state (`charge`), the fourth one the quantification of the overall intensity of the pattern (`quant`) and the last one contains the amplitude at the most intense peak (`amplitude`).

peaklistprocessed

  The result after applying the postprocessing procedure to the raw list `peaklist`. It is a matrix of the same structure as `peaklist`, with two up to four additional columns: the fifth column contains the local noise level at the position, and the last one contains the ratio of the amplitude to local noise level (signal-to-noise ratio), hence quantitatively describing the significance of the peak pattern. If `goodnessoffit` has been set to `TRUE`, there are two additional columns labelled `goodness_of_fit` and `ratio_adj`. The column `goodness_of_fit` contains a local assessment of the goodness-of-fit at the respective positions in the spectrum, while the column `ratio_adj` contains a goodness-of-fit adjusted signal-to-noise ratio. If `postprocessed` has been set to `FALSE` when calling getPeaklist, this slot is an empty matrix.

model

  One of "Gaussian" or "EMG".

averagine.table

  Averagine table used, cf.getPeaklist.

loss

  One of "L2" or "L1".

alpha

  Function for the parameter "alpha" (`model = "EMG"`).

sigma

  Function for the parameter "sigma" (both models).

mu

  Function for the parameter "mu" (`model = "EMG"`).

charges

  A `numeric` vector containing the set of charge states used.

basis

  The matrix of basis functions if `returnbasis` has been set to `TRUE` when calling getPeaklist. Otherwise, this slot is an empty matrix.

book

  A `matrix` annotating each column of `basis`. Each row corresponds to a template/peak pattern characterized by the initial position of the peak pattern (column `initial`), the position of the most intense peak (column `most_intense`) and the charge state (column `charge`).

beta

  A `numeric` vector storing the amplitudes for each peak pattern in `book`/each column of `basis`, obtained by non-negative least squares estimation (if `loss = "L2"`) or by non-negative least absolute deviation estimation (if `loss = "L1"`). Hence, together with `book`, `cbind(book, beta)` constitutes a predecessor of `peaklist`.

locnoise

  A `matrix` of local quantiles of the intensities computed along the spectrum. Each row corresponds to a m/z value of the spectrum (ordered increasingly), and each column to a quantile as indicated by the column names. For instance, `slot(object, "locnoise")[,"0.5"]` would give the vector of local medians.

noiselevel

  A `numeric` vector storing the noise level used for computation of the signal-to-noise ratios appearing in `peaklistprocessed`.

goodnessoffit

  A `numeric` vector storing the local goodness-of-fit criterion. An empty vector unless `control.postprocessing$goodnessfittrue` was `TRUE` when `getPeaklist` was called.

data

  A `list` storing the spectrum used to generate the object.

### Methods

show

  Use `show(object)` for brief information about the object.

threshold

  Only applicable if `postprocessed` has been set to `TRUE` when calling `getPeaklist`. A function to threshold `peaklistprocessed`, yielding a peaklist maintaining only those peaks exceeding a specified threshold. Optionally, re-fitting of the spectrum using only those templates that have passed the thresholding step can be performed. The argument list is given by

  `object`

    An object of class `peaklist`.

  `threshold`

    The value to be used as threshold.

  `ratio`

    Whether to use the signal-to-noise ratio `"ratio"` or the goodness-of-fit adjusted signal-to-noise ratio `"ratio_adj"`

  `refit`

    Whether re-fitting of the spectrum should be done, using only the templates above the threshold.

  `trace`

    A `logical` indicating whether information tracing the different steps of the fitting process should be displayed. Only used if `refit = TRUE`.

  `eps`

    Function values below `eps` are set equal to precisely zero in order to make the basis function matrix sparse. Only used if `refit = TRUE`.

  .

visualize

  A function to displaying the results of the fitting procedure, in particular significant peak patterns, in selected m/z ranges. The description of the arguments is as follows:

  `object`

    An object of class `peaklist`.

  `mz`

    The vector of m/z values used to obtain `object`.

  `intensities`

    The vector of intensities used to obtain `object`.

  `lower, upper`

    The m/z range for which the result of the fitting procedure should be visualized (`lower < upper`). Hint: the difference `upper - lower` should be between 0-30. If it is significantly larger, computation times increase considerably. Moreover, this will lead to a reduced quality of the plot.

  `truth`

    May be set to `TRUE` if one has a precise knowledge of the true underlying signal (normally only occuring for simulated data) and one wants to compare the results with the gold standard. If `truth = TRUE`, `booktrue` (s. below) has to be specified. In this case, the true signal is displayed as upper panel in the plot.

  `signal`

    A `logical` indicating whether the raw spectrum in the range `[lower,upper]` should be plotted. If `TRUE`, it is displayed as upper panel or as one of the middle panels.

  `fitted`

    A `logical` indicating whether basically all (with restrictions, s. `cutoff.functions` and `cutoff.eps` below) fitted templates should be plotted. If `TRUE`, the result is displayed as a middle panel or as lower panel.

  `postprocessed`

    A `logical` indicating whether fitted templates after postprocessing should be plotted. If `TRUE`, the result is displayed as lower panel.

  `fittedfunction`

    A `logical` indicating whether the fitted function should be drawn as lines in the panel displaying the raw spectrum (requires `signal = TRUE`). Note that the fitted function is the result of summing up all fitted templates multiplied by their amplitude. Setting `fittedfunction = TRUE` requires that `object` contains the matrix of basis functions.

  `fittedfunction.cut`

    A `logical` indicating whether the fitted function after cutting peak patterns falling below a prespecified cutoff should be drawn as lines in the panel displaying the raw spectrum (requires `signal = TRUE`). Setting `fittedfunction.cut = TRUE` requires that `object` contains the matrix of basis functions.

  `quantile`

    Optional argument. If `quantile` is specified, it has to be one of the values `0.1,...,0.9`, and the corresponding local quantile as contained in the slot `locnoise` (s. above) will be added to the plot as dotted line.

  `booktrue`

    Required if and only if `truth = TRUE`. In this case, `booktrue` has to be a matrix having the same structure as `cbind(slot(object, "book"), slot(object, "beta"))`, i.e. the first two columns of `booktrue` contain initial- and most intense peak locations within a peak pattern, the third column contains the charge state and the fourth one the amplitude of the most intense peak. Note: the 'truth' is computed according to `slot(object, model)`. This excludes the following scenario: assuming that the true peak shapes is `"EMG"`, but the chosen model is `"Gaussian"`. Then the true model in this function is computed according to the latter model.

  `cutoff.eps, cutoff.functions`

    Control arguments reducing the number of templates to be plotted if `fitted = TRUE`. Specifying `cutoff.eps` removes all templates with intensity smaller than `cutoff.eps`. Specifying `cutoff.functions` as a positive integer only plots the `cutoff` 'most intense' templates.

  `...`

    Additional options passed to `plot`.

  Note that the colours in the plot have no meaning. They are only used to distinguish between different patterns within a panel. Further note that the colour of a pattern appearing in several panels may vary from panel to panel.

[Package IPPD version 1.34.0 Index]