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ConsensusID

Computes a consensus identification from peptide identification engines.

potential predecessor tools $ \longrightarrow $ ConsensusID $ \longrightarrow $ potential successor tools
MascotAdapter (or other ID engines) FalseDiscoveryRate
IDPosteriorErrorProbability
IDMapper

This implementation (for PEPMatrix and PEPIons) is described in

Nahnsen S, Bertsch A, Rahnenfuehrer J, Nordheim A, Kohlbacher O
Probabilistic Consensus Scoring Improves Tandem Mass Spectrometry Peptide Identification
Journal of Proteome Research (2011), DOI: 10.1021/pr2002879

The input file can contain several searches, e.g., from several identification engines. In order to use the PEPMatrix or the PEPIons algorithm, posterior error probabilities (PEPs) need to be calculated using the IDPosteriorErrorProbability tool for all individual search engines. After PEP calculation, the different search engine results have to be combined using IDMerger. Identification runs can be mapped to featureXML and consensusXML with the IDMapper tool. The merged file can now be fed into into the ConsensusID tool. For the statistical assessment of the results it is recommended to use target-decoy databases for peptide identifications. The false discovery rates (FDRs) can be calculated using the FalseDiscoveryRate tool.

Note
Currently mzIdentML (mzid) is not directly supported as an input/output format of this tool. Convert mzid files to/from idXML using IDFileConverter if necessary.

The command line parameters of this tool are:

ConsensusID -- Computes a consensus identification from peptide identifications of several identification 
engines.
Version: 2.0.0 May 29 2015, 13:57:09, Revision: GIT-NOTFOUND

Usage:
  ConsensusID <options>

This tool has algorithm parameters that are not shown here! Please check the ini file for a detailed descript
ion or use the --helphelp option.

Options (mandatory options marked with '*'):
  -in <file>*          Input file (valid formats: 'idXML', 'featureXML', 'consensusXML')
  -out <file>*         Output file (valid formats: 'idXML', 'featureXML', 'consensusXML')
                       
  -rt_delta <value>    Maximum allowed precursor RT deviation between identifications. (default: '0.1' min: 
                       '0')
  -mz_delta <value>    Maximum allowed precursor m/z deviation between identifications. (default: '0.1' min: 
                       '0')
  -min_length <value>  Minimum of length of peptides for final consensus list (default: '6' min: '1')
  -use_all_hits        If 'true' not only the first hit, but all are used (peptides only)
                       
Common TOPP options:
  -ini <file>          Use the given TOPP INI file
  -threads <n>         Sets the number of threads allowed to be used by the TOPP tool (default: '1')
  -write_ini <file>    Writes the default configuration file
  --help               Shows options
  --helphelp           Shows all options (including advanced)

The following configuration subsections are valid:
 - algorithm   Consensus algorithm section

You can write an example INI file using the '-write_ini' option.
Documentation of subsection parameters can be found in the doxygen documentation or the INIFileEditor.
Have a look at the OpenMS documentation for more information.

INI file documentation of this tool:

Legend:
required parameter
advanced parameter
+ConsensusIDComputes a consensus identification from peptide identifications of several identification engines.
version2.0.0 Version of the tool that generated this parameters file.
++1Instance '1' section for 'ConsensusID'
in input fileinput file*.idXML,*.featureXML,*.consensusXML
out output fileoutput file*.idXML,*.featureXML,*.consensusXML
rt_delta0.1 Maximum allowed precursor RT deviation between identifications.0:∞
mz_delta0.1 Maximum allowed precursor m/z deviation between identifications.0:∞
min_length6 Minimum of length of peptides for final consensus list1:∞
use_all_hitsfalse If 'true' not only the first hit, but all are used (peptides only)true,false
log Name of log file (created only when specified)
debug0 Sets the debug level
threads1 Sets the number of threads allowed to be used by the TOPP tool
no_progressfalse Disables progress logging to command linetrue,false
forcefalse Overwrite tool specific checks.true,false
testfalse Enables the test mode (needed for internal use only)true,false
+++algorithmConsensus algorithm section
algorithmPEPMatrix Algorithm used for the consensus scoring.
ranked -- reorders the hits according to a consensus score computed from the ranks in the input runs. The score is normalized to the interval (0,100). The PeptideIdentifications do not need to have the same score type.
average -- reorders the hits according to the average score of the input runs. Make sure to use PeptideIdentifications with the same score type only!
PEPMatrix -- calculates a consensus score based on posterior error probabilities and scoring matrices for siimilarity. This algorithm uses the PAM30MS matrix to score sequences not listed by all engines. Make sure to use PeptideIdentifications with score types converted to PEPs only!
PEPIons -- calculates a consensus score based on posterior error probabilities and fragment ion siimilarity. Make sure to use PeptideIdentifications with score types converted to PEPs only!
Minimum -- calculates a consensus score based on the minimal score. Make sure to use PeptideIdentifications with score types converted to PEPs only!
ranked,average,PEPMatrix,PEPIons,Minimum
considered_hits10 The number of top hits that are used for the consensus scoring.1:∞
number_of_runs0 The number of runs used as input. This information is used in 'Ranked' and 'Average' to compute the new scores. If not given, the number of input identifications is taken.0:∞
++++PEPIons
MinNumberOfFragments2 The minimal number of similar (between two suggested sequences) fragment ion masses that is necessary to evaluate the shared peak count similarity (SPC).0:∞
common1.1 Similarity threshold to accept the best score. E.g. for a given spectrum: engine 1 -> pep 1 with score x1 and engine2 -> pep2 with score x2. The better score from {x1,x2} will be used if the degree of similarity between pep1 and pep2 >= common, Note that 0 <= degree of similarity <= 1. Values > 1 will disable this option.0:1.1
++++PEPMatrix
common1.1 Similarity threshold to accept the best score. E.g. for a given spectrum: engine 1 -> pep 1 with score x1 and engine2 -> pep2 with score x2. The better score from {x1,x2} will be used if the degree of similarity between pep1 and pep2 >= common, Note that 0 <= degree of similarity <= 1. Values > 1 will disable this option.0:1.1
penalty5 Give the gap penalty (the same penalty will be used for opening and extension) as a positive integer

For the parameters of the algorithm section see the algorithms documentation:
Consensus algorithm


OpenMS / TOPP release 2.0.0 Documentation generated on Fri May 29 2015 17:20:33 using doxygen 1.8.9.1