R: Label Free Quantification using the top N peptide approach

pgLFQtNpq {protViz} | R Documentation

## Label Free Quantification using the top N peptide approach

### Description

This Function implements the recently emerged TopN strategy which uses only the top N intense features for calculating the proteinVolume. This approach should reveal a quantitative protein value, which should make the protein itself comparable within one condition. This allows to estimate protein stochiometries and simplifies modelling and calculations with copy numbers per cell.

### Usage

        pgLFQtNpq(QuantitativeValue,
        peptide, protein, N=3, plot=TRUE, FUN=asinh)

### Arguments

`QuantitativeValue` | a data set like `pgLFQfeature$"Normalized abundance"`.
`peptide` | a vector of peptide sequences.
`protein` | a vector of protein information.
`N` | top `N` peptide flyers.
`plot` | logical. If 'TRUE' (non default), a boxplot is drawn.
`FUN` | function for doing the data transformation for the correlation matrix for the image plot, default transformation is `asinh`.

### Details

The approach has first been described by Silva et al. in 2005 for Waters Q-tof instruments running in the MSe mode. Grossmann et al, showed in 2010 that this approach also works for more widely spread instruments such as Orbitrap-Velos or FTICR instruments from Thermo.

todo: additional columns (or additonal object) for 'protein names' and the total number of features assigned to protein in the master map. The length should be the same as for how many Ns chosen in the assembly method. Double check, if 'empty' protein names.. - basically - not assigned features.. are also in the list! - get rid of it.

### Author(s)

Christian Panse, Jonas Grossmann 2012

### References

http://www.ncbi.nlm.nih.gov/pubmed/16219938 http://www.ncbi.nlm.nih.gov/pubmed/20576481

### Examples

        data(pgLFQfeature)
        par(mfrow=c(2,4), mar=c(4,4,4,1))
        for (i in c(1, 2, 3, 4)){
            tNpq<-pgLFQtNpq(QuantitativeValue=pgLFQfeature$"Normalized abundance",
                peptide=pgLFQfeature$peptideInfo$Sequence,
                protein=pgLFQfeature$peptideInfo$Protein,
                N=i)
        }

        for (i in c(1, 2, 3, 4)){
            tNpq<-pgLFQtNpq(QuantitativeValue=pgLFQfeature$"Normalized abundance",
                peptide=pgLFQfeature$peptideInfo$Sequence,
                protein=pgLFQfeature$peptideInfo$Protein,
                plot=FALSE,
                N=i)

            boxplot(t(tNpq), xlab='proteins', ylab='protein value')
        }

[Package protViz version 0.2.45 Index]