proteinDataPrep: Formats a data set of spectral profiles for use with...

In mooredf22/protlocassign: Estimation of protein distribution from quantitative subcellular fractionation experiments using a constrained proportional assignment model

Formats a data set of spectral profiles for use with protlocassign

Description

The function sorts a data set of peptide-spectrum matches with associated profiles and descriptive information, ensuring that spectra are nested within peptides and peptides are nested within proteins so that all peptide and protein data are contiguous. Peptide names (typically sequences) are prepended with the associated protein name. The function assigns unique numerical identifiers to each protein (protId) and each peptide (pepId). The input data frame must be formatted so that the first column contains protein names and the second peptide names. This is followed by a series of columns containing descriptive information and profile data.

Usage

proteinDataPrep(protClass, numRefCols, numDataCols)

Arguments

protClass	data frame containing protein and peptide names, annotation data and profiles
numRefCols	number of reference columns (includes protein and peptide names)
numDataCols	number of fractions in each profile

Value

Data frame properly formatted for protlocassign

Examples

data(QuantPSM_test)
specNSA_out <- proteinDataPrep(QuantPSM_test, numRefCols=5,numDataCols=9)
head(specNSA_out)

mooredf22/protlocassign documentation built on Sept. 13, 2023, 3:57 p.m.