getMultipeptide {DIAlignR} | R Documentation |
Each element of the multipeptide is a collection of features associated with a peptide.
getMultipeptide( precursors, features, runType = "DIA_Proteomics", applyFun = lapply, masters = NULL )
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. |
(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. |
Shubham Gupta, shubh.gupta@mail.utoronto.ca
ORCID: 0000-0003-3500-8152
License: (c) Author (2020) + GPL-3 Date: 2020-04-08
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"]]