evidenceToMatrix: Creates intensity matrix from tabular data in evidence table...

In DavisLaboratory/msImpute: Imputation of label-free mass spectrometry peptides

Creates intensity matrix from tabular data in evidence table of MaxQuant

Description

Every Modified sequence - Charge is considered as a precursor feature. Only the feature with maximum intensity is retained. The columns are run names, the rows are peptide ids (in the Modified.sequence_Charge format)

Usage

evidenceToMatrix(
  evidence,
  run_id = "Raw.file",
  peptide_id = "PeptideID",
  return_EList = FALSE,
  weights = NULL
)

Arguments

evidence	data.frame. The evidence table read from evidence.txt, or data.frame created by mspip.
run_id	character. The name of the column of evidence containing the run/raw file name. These form the columns of the intensity data matrix.
peptide_id	character. The name of the column of evidence containing the peptide ids. These form the rows of the intensity data matrix.
return_EList	logical. If TRUE, returns a EListRaw object storing both the intensity data matrix and observation-level weights from mspip (propagation confidence score), otherwise returns a matrix.
weights	character. The name of the column of evidence containing weights from mspip. default to NULL. Set this to "weight" if you want the weights from PIP stored in the weights slot of the EListRaw object.

Details

The EListRaw object created by the function is intended to bridge msImpute and statistical methods of limma. The object can be passed to normalizeBetweenArrays for normalisation, which can then be passed to lmFit and eBayes for fitting linear models per peptide and Empirical Bayes moderation of t-statistics respectively. The weights slot is recognized by lmFit, which incorporates the uncertainty in intensity values inferred by PIP into the test statistic. The function is also a generic tool to create a matrix or limma-compatible objects from the evidence table of MaxQuant.

Value

a numeric matrix of intensity data, or a EListRaw object containing such data and observation-level weights from mspip.

Author(s)

Soroor Hediyeh-zadeh

See Also

mspip

DavisLaboratory/msImpute documentation built on Jan. 5, 2024, 3:50 a.m.