evidenceToMatrix {msImpute} | R Documentation

## 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

[Package msImpute version 1.4.0 Index]