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Filter Proteome Discoverer DDA output

filter_features_pd_dda.Rd

This function filters the output .txt files (peptide groups or PSMs) from Proteome Discoverer for DDA, based on various criteria:

  1. Remove features without a master protein

  2. Remove features without a unique master protein (i.e. Number.of.Protein.Groups == 1)

  3. Remove features matching a contaminant protein

  4. Remove features matching any protein associated with a contaminant protein (see below)

  5. Remove features without quantification values

Usage

filter_features_pd_dda(
  obj,
  master_protein_col = "Master.Protein.Accessions",
  protein_col = "Protein.Accessions",
  unique_master = TRUE,
  filter_contaminant = TRUE,
  contaminant_proteins = NULL,
  crap_proteins = NULL,
  filter_associated_contaminant = TRUE,
  remove_no_quant = TRUE,
  cont_string = "Cont_"
)

Arguments

obj

SummarisedExperiment containing output from Proteome Discoverer. Use readQFeatures to read in .txt file

master_protein_col

string. Name of column containing master proteins.

protein_col

string. Name of column containing all protein matches.

unique_master

logical. Filter out features without a unique master protein.

filter_contaminant

logical. Filter out features which match a contaminant protein.

contaminant_proteins

character vector. The protein IDs form the contaminant proteins

crap_proteins

character vector. Same as contaminant_proteins. Available for backwards compatibility. Default is NULL. If both contaminant_proteins and crap_proteins are set, an error is thrown.

filter_associated_contaminant

logical. Filter out features which match a contaminant associated protein.

remove_no_quant

logical. Remove features with no quantification

cont_string

string. string to search for contaminants

Value

Returns a SummarisedExperiment with the filtered Proteome Discoverer output.

Details

Associated contaminant proteins are proteins which have at least one feature shared with a contaminant protein. It has been observed that the contaminant fasta files often do not contain all possible contaminant proteins e.g. some features can be assigned to a keratin which is not in the provided contaminant database.

In the example below, using filter_associated_contaminant = TRUE will filter out f2 and f3 in addition to f1, regardless of the value in the Master.Protein.Accession column.

feature  Protein.Accessions         Master.Protein.Accessions
f1       protein1, protein2, contaminant,  protein1,
f2       protein1, protein3         protein3,
f3       protein2                   protein2

Examples

if (FALSE) { # \dontrun{

#### PSMs.txt example ####
# load PD PSMs.txt output
tmt_qf <- readQFeatures(assayData = psm_tmt_total,
 quantCols = 36:45,
 name = "psms_raw")

# extract the UniProt accessions from the contaminant FASTA headers
contaminant_accessions <- get_contaminant_fasta_accessions(contaminant_fasta_inf)

# filter the PSMs
psm2 <- filter_features_pd_dda(
  obj = tmt_qf[['psms_raw']],
  master_protein_col = "Master.Protein.Accessions",
  protein_col = "Protein.Accessions",
  unique_master = TRUE,
  TMT = TRUE,
  filter_contaminant = TRUE,
  contaminant_proteins = contaminant_accessions,
  filter_associated_contaminant = TRUE
)


} # }