MSstatsPreprocess: Preprocess outputs from MS signal processing tools for...

In Vitek-Lab/MSstatsConvert: Import Data from Various Mass Spectrometry Signal Processing Tools to MSstats Format

Preprocess outputs from MS signal processing tools for analysis with MSstats

Description

Preprocess outputs from MS signal processing tools for analysis with MSstats

Usage

MSstatsPreprocess(
  input,
  annotation,
  feature_columns,
  remove_shared_peptides = TRUE,
  remove_single_feature_proteins = TRUE,
  feature_cleaning = list(remove_features_with_few_measurements = TRUE,
    summarize_multiple_psms = max),
  score_filtering = list(),
  exact_filtering = list(),
  pattern_filtering = list(),
  columns_to_fill = list(),
  aggregate_isotopic = FALSE,
  ...
)

Arguments

input	data.table processed by the MSstatsClean function.
annotation	annotation file generated by a signal processing tool.
feature_columns	character vector of names of columns that define spectral features.
remove_shared_peptides	logical, if TRUE shared peptides will be removed.
remove_single_feature_proteins	logical, if TRUE, proteins that only have one feature will be removed.
feature_cleaning	named list with maximum two (for MSstats converters) or three (for MSstatsTMT converter) elements. If handle_few_measurements is set to "remove", feature with less than three measurements will be removed (otherwise it should be equal to "keep"). summarize_multiple_psms is a function that will be used to aggregate multiple feature measurements in a run. It should return a scalar and accept an na.rm parameter. For MSstatsTMT converters, setting remove_psms_with_any_missing will remove features which have missing values in a run from that run.
score_filtering	a list of named lists that specify filtering options. Details are provided in the vignette.
exact_filtering	a list of named lists that specify filtering options. Details are provided in the vignette.
pattern_filtering	a list of named lists that specify filtering options. Details are provided in the vignette.
columns_to_fill	a named list of scalars. If provided, columns with names defined by the names of this list and values corresponding to its elements will be added to the output data.frame.
aggregate_isotopic	logical. If TRUE, isotopic peaks will by summed.
...	additional parameters to data.table::fread.

Value

data.table

Examples

evidence_path = system.file("tinytest/raw_data/MaxQuant/mq_ev.csv", 
                            package = "MSstatsConvert")
pg_path = system.file("tinytest/raw_data/MaxQuant/mq_pg.csv", 
                      package = "MSstatsConvert")
evidence = read.csv(evidence_path)
pg = read.csv(pg_path)
imported = MSstatsImport(list(evidence = evidence, protein_groups = pg),
                         "MSstats", "MaxQuant")
cleaned_data = MSstatsClean(imported, protein_id_col = "Proteins")
annot_path = system.file("tinytest/raw_data/MaxQuant/annotation.csv", 
                         package = "MSstatsConvert")
mq_annot = MSstatsMakeAnnotation(cleaned_data, read.csv(annot_path),
                                 Run = "Rawfile")
                               
# To filter M-peptides and oxidatin peptides 
m_filter = list(col_name = "PeptideSequence", pattern = "M", 
                filter = TRUE, drop_column = FALSE)
oxidation_filter = list(col_name = "Modifications", pattern = "Oxidation", 
                        filter = TRUE, drop_column = TRUE)
msstats_format = MSstatsPreprocess(
cleaned_data, mq_annot, 
feature_columns = c("PeptideSequence", "PrecursorCharge"),
columns_to_fill = list(FragmentIon = NA, ProductCharge = NA),
pattern_filtering = list(oxidation = oxidation_filter, m = m_filter)
)
# Output in the standard MSstats format
head(msstats_format)

Vitek-Lab/MSstatsConvert documentation built on Dec. 17, 2024, 1:14 a.m.