| getPrecursors | R Documentation | 
Get a data-frame of analytes' transition_group_id, transition_ids, peptide_id and amino-acid sequences.
getPrecursors(
  fileInfo,
  oswMerged = TRUE,
  runType = "DIA_Proteomics",
  context = "global",
  maxPeptideFdr = 0.05,
  level = "Peptide",
  useIdentifying = FALSE
)
fileInfo | 
 (data-frame) Output of   | 
oswMerged | 
 (logical) TRUE for experiment-wide FDR and FALSE for run-specific FDR by pyprophet.  | 
runType | 
 (char) This must be one of the strings "DIA_Proteomics", "DIA_IPF", "DIA_Metabolomics".  | 
context | 
 (string) Context used in pyprophet peptide. Must be either "run-specific", "experiment-wide", or "global".  | 
maxPeptideFdr | 
 (numeric) A numeric value between 0 and 1. It is used to filter peptides from osw file which have SCORE_PEPTIDE.QVALUE less than itself.  | 
level | 
 (string) Apply maxPeptideFDR on Protein as well if specified as "Protein". Default: "Peptide".  | 
useIdentifying | 
 (logical) Set TRUE to use identifying transitions in alignment. (DEFAULT: FALSE)  | 
(data-frames) A data-frame having following columns:
transition_group_id | 
 (integer) a unique id for each precursor.  | 
peptide_id | 
 (integer) a unique id for each peptide. A peptide can have multiple precursors.  | 
sequence | 
 (string) amino-acid sequence of the precursor with possible modifications.  | 
charge | 
 (integer) charge on the precursor.  | 
group_label | 
 (string) TODO Figure it out.  | 
transition_ids | 
 (list) fragment-ion ID associated with transition_group_id. This is matched with chromatogram ID in mzML file.  | 
Shubham Gupta, shubh.gupta@mail.utoronto.ca
ORCID: 0000-0003-3500-8152
License: (c) Author (2019) + GPL-3 Date: 2019-04-06
getRunNames, fetchPrecursorsInfo
dataPath <- system.file("extdata", package = "DIAlignR")
fileInfo <- getRunNames(dataPath = dataPath)
precursorsInfo <- getPrecursors(fileInfo, oswMerged = TRUE, runType = "DIA_Proteomics",
context = "experiment-wide", maxPeptideFdr = 0.05)
dim(precursorsInfo) # 234  6
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