FragPipetoMSstatsPTMFormat: Convert output of TMT labeled Fragpipe data into MSstatsPTM...

In Vitek-Lab/MSstatsPTM: Statistical Characterization of Post-translational Modifications

Convert output of TMT labeled Fragpipe data into MSstatsPTM format.

Description

Takes as input TMT experiments which are the output of Fragpipe and converts into MSstatsPTM format. Requires msstats.csv file and an annotation file. Optionally an additional msstats.csv file can be uploaded if a corresponding global profiling run was performed. Site localization is performed and only high probability localizations are kept.

Usage

FragPipetoMSstatsPTMFormat(
  input,
  annotation = NULL,
  input_protein = NULL,
  annotation_protein = NULL,
  use_unmod_peptides = FALSE,
  label_type = "TMT",
  protein_id_col = "Protein",
  peptide_id_col = "Peptide.Sequence",
  mod_id_col = "STY",
  localization_cutoff = 0.75,
  remove_unlocalized_peptides = TRUE,
  Purity_cutoff = 0.6,
  PeptideProphet_prob_cutoff = 0.7,
  useUniquePeptide = TRUE,
  rmPSM_withfewMea_withinRun = FALSE,
  rmPeptide_OxidationM = TRUE,
  rmProtein_with1Feature = FALSE,
  summaryforMultipleRows = sum,
  use_log_file = TRUE,
  append = FALSE,
  verbose = TRUE,
  log_file_path = NULL
)

Arguments

input	data.frame of msstats.csv file produced by Philosopher
annotation	annotation with Run, Fraction, TechRepMixture, Mixture, Channel, BioReplicate, Condition columns or a path to file. Refer to the example 'annotation' for the meaning of each column. Channel column should be consistent with the channel columns (Ignore the prefix "Channel ") in msstats.csv file. Run column should be consistent with the Spectrum.File columns in msstats.csv file.
input_protein	same as input for global profiling run. Default is NULL.
annotation_protein	same as annotation for global profiling run. Default is NULL.
use_unmod_peptides	Boolean if the unmodified peptides in the input file should be used to construct the unmodified protein output. Only used if input_protein is not provided. Default is FALSE.
label_type	Type of labeling used for experiment. Must be one of "LF" or "TMT". Default is "TMT".
protein_id_col	Use 'Protein'(default) column for TMT. This needs to be changed to "ProteinName" for label free. For TMT, 'Master.Protein.Accessions' can be used instead to get the protein ID with single protein.
peptide_id_col	Use 'Peptide.Sequence'(default) column for TMT. Must be changed to "PeptideSequence" for label free. "Modified.Peptide.Sequence" can be used instead to get the modified peptide sequence.
mod_id_col	Column containing the modified Amino Acids. For example, a Phosphorylation experiment may pass STY. The corresponding column with STY combined with the mass (e.x. STY.79.9663) will be selected. Default is STY.
localization_cutoff	Minimum localization score required to keep modification. Default is .75.
remove_unlocalized_peptides	Boolean indicating if peptides without all sites localized should be kept. Default is TRUE (non-localized sites will be removed).
Purity_cutoff	Cutoff for purity. Default is 0.6. Purity refers to how much of the detected ion signal within a specific inclusion window belongs to the target molecule or its closely related forms, compared to any other unwanted signals or noise. Higher values indicate greater purity.
PeptideProphet_prob_cutoff	Cutoff for the peptide identification probability. Default is 0.7. The probability is confidence score determined by PeptideProphet and higher values indicate greater confidence.
useUniquePeptide	logical, if TRUE (default) removes peptides that are assigned for more than one proteins. We assume to use unique peptide for each protein.
rmPSM_withfewMea_withinRun	TRUE (default) will remove the features that have 1 or 2 measurements within each Run.
rmPeptide_OxidationM	TRUE (default) will remove the peptides including oxidation (M) sequence.
rmProtein_with1Feature	TRUE will remove the proteins which have only 1 peptide and charge. Defaut is FALSE.
summaryforMultipleRows	sum (default) or max - when there are multiple measurements for certain feature in certain run, select the feature with the largest summation or maximal value.
use_log_file	logical. If TRUE, information about data processing will be saved to a file.
append	logical. If TRUE, information about data processing will be added to an existing log file.
verbose	logical. If TRUE, information about data processing wil be printed to the console.
log_file_path	character. Path to a file to which information about data processing will be saved. If not provided, such a file will be created automatically. If 'append = TRUE', has to be a valid path to a file.

Value

list of one or two data.frame of class MSstatsTMT, named PTM and PROTEIN

Examples

# TMT Example (with global profiling run)
head(fragpipe_input)
head(fragpipe_annotation)
head(fragpipe_input_protein)
head(fragpipe_annotation_protein)

msstats_data = FragPipetoMSstatsPTMFormat(fragpipe_input,
                                          fragpipe_annotation,
                                          fragpipe_input_protein, 
                                          fragpipe_annotation_protein,
                                          label_type="TMT",
                                          mod_id_col = "STY",
                                          localization_cutoff=.75,
                                          remove_unlocalized_peptides=TRUE)
head(msstats_data$PTM)
head(msstats_data$PROTEIN)

# LFQ Example (w/out global profiling run)
input = system.file("tinytest/raw_data/Fragpipe/MSstats.csv", 
                                        package = "MSstatsPTM")
input = data.table::fread(input)
annot = system.file("tinytest/raw_data/Fragpipe/experiment_annotation.tsv", 
                                        package = "MSstatsPTM")
annot = data.table::fread(annot)                                        

msstats_data = FragPipetoMSstatsPTMFormat(input,
                                          annot,
                                          label_type="LF",
                                          mod_id_col = "STY",
                                          localization_cutoff=.75,
                                          protein_id_col = "ProteinName",
                                          peptide_id_col = "PeptideSequence")
head(msstats_data$PTM)

# Note that this is NULL because we did not include a global profiling run.
# Ideally, you should include an independent global profiling run.
head(msstats_data$PROTEIN)

Vitek-Lab/MSstatsPTM documentation built on Sept. 26, 2024, 9:28 p.m.