isobar-preprocessing {isobar} | R Documentation

## IBSpectra preprocessing

### Description

Preprocessing is a necessary step prior to analysis of data. In a sequential order, it is often neccassary to correct isotope impurities, to normalize, and subtract additive noise.

### Isotope impurity correction

`correctIsotopeImpurities(x)`:

  Returns impurity corrected IBSpectra object by solving a linear system of equations. See also isotopeImpurities.

### Normalization

`normalize(x,f=median,target="intensity",exclude.protein=NULL, use.protein=NULL,f.doapply=TRUE,log=TRUE,channels=NULL,na.rm=FALSE)`:

  Normalizes the intensities for multiplicative errors. Those changes are most likely produced by pipetting errors, and different hybridization efficencies, but can also be due to biological reasons. By default, tag intensities are multiplied by a factor so that the median intensity is equal across tags.

  `f`:

    `f` is applied to each column, unless f.doapply is FALSE. Then `f` is supposed to compute column-wise statistics of the matrix of intensities. E.g. `colSums` and `colMeans`.

  `target`:

    One of "intensity" and "ratio".

  `exclude.proteins`

    Spectra of peptides which might come from these proteins are excluded. Use for example for contaminants and proteins depleted in the experiment.

  `use.protein`:

    If specified, only spectra coming from this protein are used. Use when a protein is spiked-in as normalization control.

  `f.isglobal`:

    If true, `f` is applied on each column. If false, `f` is supposed to compute column-wise statistics of the matrix of intensities. E.g. `colSums` and `colMeans`.

  `log`:

    Used when target=ratio.

### Substract additive noise

`subtractAdditiveNoise(x,method="quantile",shared=TRUE,prob=0.01)`:
  `method`

    'quantile' method is supported for now. It take's the prob (0.01) quantile to estimate the noise level. This value is subtracted from all intensities, and all remaining intensities have to be at least that value.

  `prob`

    See 'method'.

  `shared`

    If channels are assumed similar in intensity and hence a shared noise level is reasonable. If not, then one level per channel is necessary.

### Exclusion of proteins

`exclude(x,proteins.to.exclude)`:

  Removes spectra which are assigned to proteins in protein.to.exclude from the object. This can be useful to remove contaminants. It create a new grouping based on the data which is left.

  `proteins.to.exclude`

    Proteins to exclude.

### Author(s)

Florian P. Breitwieser, Jacques Colinge

### See Also

ProteinGroup, IBSpectra, isobar-analysis, isobar-plots

### Examples

    data(ibspiked_set1)
    maplot(ibspiked_set1,main="IBSpiked, not normalized")
    maplot(normalize(ibspiked_set1),main="IBSpiked, normalized")

[Package isobar version 1.32.0 Index]