getMultipeptide {DIAlignR} | R Documentation

## Get multipeptides

### Description

Each element of the multipeptide is a collection of features associated with a peptide.

### Usage

    getMultipeptide(
      precursors,
      features,
      runType = "DIA_Proteomics",
      applyFun = lapply,
      masters = NULL
    )

### Arguments

`precursors` | (data-frames) Contains precursors and associated transition IDs.
`features` | (list of data-frames) Contains features and their properties identified in each run.
`runType` | (char) This must be one of the strings "DIA_Proteomics", "DIA_IPF", "DIA_Metabolomics".
`applyFun` | (function) value must be either lapply or BiocParallel::bplapply.
`masters` | (characters) names of extra runs.

### Value

(list) of dataframes having following columns:

`transition_group_id` | (integer) a unique id for each precursor.
`run` | (string) run identifier.
`RT` | (numeric) retention time as in FEATURE.EXP_RT of osw files.
`Intensity` | (numeric) peak intensity as in FEATURE_MS2.AREA_INTENSITY of osw files.
`leftWidth` | (numeric) as in FEATURE.LEFT_WIDTH of osw files.
`rightWidth` | (numeric) as in FEATURE.RIGHT_WIDTH of osw files.
`peak_group_rank` | (integer) rank of each feature associated with transition_group_id.
`m_score` | (numeric) q-value of each feature associated with transition_group_id.
`alignment_rank` | (integer) rank of each feature post-alignment.

### Author(s)

Shubham Gupta, shubh.gupta@mail.utoronto.ca

ORCID: 0000-0003-3500-8152

License: (c) Author (2020) + GPL-3 Date: 2020-04-08

### See Also

`getPrecursors, getFeatures`

### Examples

    dataPath <- system.file("extdata", package = "DIAlignR")
    fileInfo <- getRunNames(dataPath, oswMerged = TRUE)
    precursors <- getPrecursors(fileInfo, oswMerged = TRUE, context = "experiment-wide")
    features <- getFeatures(fileInfo, maxFdrQuery = 0.05)
    multipeptide <- getMultipeptide(precursors, features)
    multipeptide[["9861"]]

[Package DIAlignR version 2.2.0 Index]