From SPCTools

Contents 1 Introduction 1.1 About Tutorial 1.2 Requirements and TPP Versions 1.3 Description of Data 2 Tutorial 2.1 Searching the Data 2.2 Validating PSMs and Inferring Proteins

Introduction

About Tutorial

This tutorial provides basic instruction on the use of StPeter for label-free quantification of proteins inferred from shotgun MS/MS spectra. It is recommended that users are familiar with performing data conversion, database searches, peptide validation, and protein inference within TPP. For additional instruction on how to perform these tasks, we recommend the broader [[TPP_Tutorial|TPP Tutorial]. For simplicity, the tutorial makes use of the Petunia interface. However, advanced users can replicate all steps from the command line.

Requirements and TPP Versions

1. Proteome Exchange dataset PXD001819 (RAW files only)
2. This FASTA sequence database
3. TPP Version 5.0 or newer

Description of Data

Tutorial

Searching the Data

• Log into the Petunia interface and set the pipeline to Comet.
• Navigate to TPP Tools > mzML/mzXML
• Convert all Thermo RAW files from PXD001819 to mzML.
• Navigate to TPP Tools > Comet Search
• Search all mzML files with the provided FASTA file and with the following Comet search parameters (leaving all other as default):
  • add_C_cysteine = 57.021464
  • variable_mod01 = 15.9949 M 0 3 -1 0 0
  • peptide_mass_tolerance = 25
  • peptide_mass_units = 2
  • isotope_error = 1
  • fragment_bin_tol = 1.0005
  • fragment_bin_offset = 0.4

The results at this stage of the tutorial are pepXML files for each of the 27 input data files.

Validating PSMs and Inferring Proteins

• Navigate to TPP Tools > Analyze Peptides
• For each of the 27 pepXML files, individually run PeptideProphet, iProphet, and ProteinProphet.
  • Give each output a unique name for identification.
  • Under PEPTIDEPROPHET OPTIONS:
    • Filter out results below this PeptideProphet probability: 0
    • Use accurate mass binning, using PPM
    • Only use Expect Score as the discriminant
    • Use decoy hits to pin down the negative distribution. Decoy protein names begin with: reverse
    • Use Non-parameteric model
    • Report decoy hits with a computed probability.
  • Under IPROPHET OPTIONS:
    • Select RUN iProphet
    • Select Also run ProteinProphet on these results