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PeptideProphet

Felipe da Veiga Leprevost edited this page Feb 25, 2019 · 7 revisions

Statistical validation of peptide assignments for MS/MS Proteomics data

Version

PeptidProphet v5.01

Usage

philosopher peptideprophet [flags] [files]

Flags

--accmass

Use Accurate Mass model binning.

--clevel

Set Conservative Level in neg_stdev from the neg_mean, low numbers are less conservative, high numbers are more conservative.

--combine

Combine the results from PeptideProphet into a single result file.

--database

Path to the database file.

--decoy

Semi-supervised mode, protein name prefix to identify Decoy entries.

--decoyprobs

Compute possible non-zero probabilities for Decoy entries on the last iteration.

--enzyme

Enzyme used in sample

--exclude

Exclude deltaCn*, Mascot*, and Comet* results from results (default Penalize * results).

--expectscore

Use expectation value as the only contributor to the f-value for modeling.

--forcedistr

Bypass quality control checks, report model despite bad modeling.

--glyc

Enable peptide Glyco motif model.

--icat

Apply ICAT model (default Auto detect ICAT).

--ignorechg

Can be used multiple times to specify all charge states to exclude from modeling.

--instrwarn

Warn and continue if combined data was generated by different instrument models.

--leave

Leave alone deltaCn*, Mascot*, and Comet* results from results (default Penalize * results).

--maldi

Enable MALDI mode.

--masswidth

model mass width (default 5.0)

--minpintt

Minimum number of NTT in a peptide used for positive pI model (default 2).

--minpiprob

Minimum probability after first pass of a peptide used for positive pI model (default 0.9).

--minprob

Report results with minimum probability (default 0.05).

--minrtntt

Minimum number of NTT in a peptide used for positive RT model.

--minrtprob

Minimum probability after first pass of a peptide used for positive RT model.

--neggamma

Use Gamma distribution to model the negative hits.

--noicat

Do no apply ICAT model (default Auto detect ICAT).

--nomass

Disable mass model.

--nonmc

Disable NMC missed cleavage model.

--nonparam

Use semi-parametric modeling, must be used in conjunction with --decoy option.

--nontt

Disable NTT enzymatic termini model.

--optimizefval

(SpectraST only) optimize f-value function f(dot,delta) using PCA.

--output

Output name prefix (default "interact").

--perfectlib

Multiply by SpectraST library probability.

--phospho

Enable peptide Phospho motif model.

--pi

Enable peptide pI model.

--ppm

Use ppm mass error instead of Dalton for mass modeling.

--rtcat

Enable peptide RT model, use <rtcatalog_file> peptide RTs when available as the theoretical value.

--zero

Report results with minimum probability 0 (default 0.05).

Example

Process two pepXML files, combining them into a single output called combined_samples. The analysis will compute possible non-zero probabilities for decoy entries using an accurate mass model for binning.

philosopher peptideprophet --database db.fasta --combine --decoyprobs --accmass --nonparam --output combined_samples sample1.pepxml sample2.pepxml

FAQ

Do I need TPP installed for running this ?

No