import_dataset_proteomediscoverer_txt: Import a label-free DDA proteomics dataset from a...

In ftwkoopmans/msdap: Mass Spectrometry Downstream Analysis Pipeline

Import a label-free DDA proteomics dataset from a ProteomeDiscoverer PSM result file

Description

ProteomeDiscoverer workflow must include Percolator so MS-DAP can parse peptide confidence scores.

Example ProteomeDiscoverer workflow:

• Processing Step: PWF_QE_Precursor_Quan_and_LFQ_SequestHT_Percolator

• Consensus Step: CWF_Comprehensive_Enhanced Annotation_LFQ_and_Precursor_Quan

• Consensus Step: add the "result exporter" (drag&drop from side panel to bottom panel)

Optionally, you can relax the output filter criteria somewhat and use MS-DAP filtering as follows;

• Consensus step –>> "peptide and protein filter" –>> Peptide Confidence At Least –>> change to medium

• While you're making changes there, you can also set "Remove Peptides Without Proteins" to "True"

Besides validating the input data table and reformatting table columns for MS-DAP, this function;

1. for each precursor (modified peptide sequence + charge state), the best PSM confidence score is retained.

2. modified peptide sequences are reformatted from input table where sequence and modifications are stored separately. e.g. Annotated Sequence = "AAGLATmISTmRPDIDNmDEYVR" and Modifications = "M7(Oxidation); M11(Oxidation); M18(Oxidation)" in input becomes modified_sequence in MS-DAP; "AAGLATM(Oxidation)ISTM(Oxidation)RPDIDNM(Oxidation)DEYVR"

Usage

import_dataset_proteomediscoverer_txt(
  filename,
  confidence_threshold = 0.01,
  remove_lowconf = TRUE,
  one_psm_per_precursor = "",
  collapse_peptide_by = "sequence_modified"
)

Arguments

filename	full path to the ProteomeDiscoverer _PSMs.txt file
confidence_threshold	confidence score threshold ('Percolator q-Value' column in the PSM file) at which a peptide is considered 'identified', default: 0.01 (target value must be lesser than or equals)
remove_lowconf	boolean value indicating whether peptides classified as 'low confidence' by ProteomeDiscoverer should be removed from the results
one_psm_per_precursor	optionally, retain for each precursor in each sample only the peakarea for 1 PSM. This parameter allows you to control how abundance values from precursors matched by multiple PSM are handled, as this might depend on your ProteomeDiscoverer settings. If ProteomeDiscoverer performed peak integration and reports the same (redundant) peak intensity for each PSM of the same precursor, we suggest to use one_psm_per_precursor = "intensity". Note that relevant statitics for your dataset will be printed to the console/log (e.g. fraction of redundant PSM that contain unique intensity values). Set to "" to disable this filtering and use the sum of all PSM intensity values per precursor*sample (default). Use one_psm_per_precursor = "intensity" to select the highest intensity value (within the subset of PSM where confidence < confidence_threshold). Use one_psm_per_precursor = "confidence" to select the intensity value from the PSM with best/lowest confidence value
collapse_peptide_by	if multiple data points are available for a peptide sequence in a sample, at what level should these be combined? options: "sequence_modified" (recommended default), "sequence_plain", ""

ftwkoopmans/msdap documentation built on March 5, 2025, 12:15 a.m.