BasicProteinInferenceAlgorithm

class pyopenms.BasicProteinInferenceAlgorithm

Bases: object

Cython implementation of _BasicProteinInferenceAlgorithm

Documentation is available at http://www.openms.de/current_doxygen/html/classOpenMS_1_1BasicProteinInferenceAlgorithm.html

– Inherits from [‘DefaultParamHandler’, ‘ProgressLogger’]

It has multiple parameter options like the aggregation method, when to distinguish peptidoforms, and if you want to use shared peptides (“use_shared_peptides”). First, the best PSM per spectrum is used, then only the best PSM per peptidoform is aggregated. Peptidoforms can optionally be distinguished via the treat_X_separate parameters: - Modifications (modified sequence string) - Charge states The algorithm assumes posteriors or posterior error probabilities and converts to posteriors initially. Possible aggregation methods that can be set via the parameter “aggregation_method” are: - “best” (default) - “sum” - “product” (ignoring zeroes) Annotation of the number of peptides used for aggregation can be disabled (see parameters). Supports multiple runs but goes through them one by one iterating over the full PeptideIdentification vector. Warning: Does not “link” the peptides to the resulting protein run. If you wish to do that you have to do it manually. —– Usage:

from pyopenms import * from urllib.request import urlretrieve urlretrieve(”https://raw.githubusercontent.com/OpenMS/OpenMS/develop/src/tests/class_tests/openms/data/newMergerTest_out.idXML”, “BasicProteinInference_test.idXML”) proteins = [] peptides = [] idf = IdXMLFile() idf.load(“BasicProteinInference_test.idXML”, proteins, peptides); bpia = BasicProteinInferenceAlgorithm() p = bpia.getParameters(); p.setValue(“min_peptides_per_protein”, 0); bpia.setParameters(p); bpia.run(peptides, proteins); # hits = proteins[0].getHits() print(hits[0].getScore()) # 0.6 print(hits[5].getScore()) # 0.9 print(hits[0].getMetaValue(“nr_found_peptides”)) # 1 print(hits[3].getMetaValue(“nr_found_peptides”)) # 2

__init__()

Cython signature: void BasicProteinInferenceAlgorithm()

Methods

__init__	Cython signature: void BasicProteinInferenceAlgorithm()
endProgress	Cython signature: void endProgress() Ends the progress display
getDefaults	Cython signature: Param getDefaults() Returns the default parameters
getLogType	Cython signature: LogType getLogType() Returns the type of progress log being used
getName	Cython signature: String getName() Returns the name
getParameters	Cython signature: Param getParameters() Returns the parameters
getSubsections	Cython signature: libcpp_vector[String] getSubsections()
nextProgress	Cython signature: void nextProgress() Increment progress by 1 (according to range begin-end)
run	Cython signature: void run(libcpp_vector[PeptideIdentification] & pep_ids, libcpp_vector[ProteinIdentification] & prot_ids)
setLogType	Cython signature: void setLogType(LogType) Sets the progress log that should be used.
setName	Cython signature: void setName(const String &) Sets the name
setParameters	Cython signature: void setParameters(Param & param) Sets the parameters
setProgress	Cython signature: void setProgress(ptrdiff_t value) Sets the current progress
startProgress	Cython signature: void startProgress(ptrdiff_t begin, ptrdiff_t end, String label)

endProgress()

Cython signature: void endProgress() Ends the progress display

getDefaults()

Cython signature: Param getDefaults() Returns the default parameters

getLogType()

Cython signature: LogType getLogType() Returns the type of progress log being used

getName()

Cython signature: String getName() Returns the name

getParameters()

Cython signature: Param getParameters() Returns the parameters

getSubsections()

Cython signature: libcpp_vector[String] getSubsections()

nextProgress()

Cython signature: void nextProgress() Increment progress by 1 (according to range begin-end)

run()

• Cython signature: void run(libcpp_vector[PeptideIdentification] & pep_ids, libcpp_vector[ProteinIdentification] & prot_ids)

Parameters

• pep_ids – Vector of peptide identifications

• prot_ids – Vector of protein identification runs. Scores will be overwritten and groups added.

Returns

Writes its results into prot_ids - Cython signature: void run(libcpp_vector[PeptideIdentification] & pep_ids, ProteinIdentification & prot_id)

Parameters

• pep_ids – Vector of peptide identifications

• prot_id – ProteinIdentification run with possible proteins. Scores will be overwritten and groups added.

Returns

Writes its results into prot_ids - Cython signature: void run(ConsensusMap & cmap, ProteinIdentification & prot_id, bool include_unassigned)

prot_id should contain the union of all proteins in the map. E.g. use ConsensusMapMergerAlgorithm and then pass the first=merged run. —– :param cmap: ConsensusMap = Consensus features with metadata and peptide identifications :param prot_id: ProteinIdentification run with possible proteins. Scores will be overwritten and groups added. :return: Writes its results into prot_ids

setLogType()

Cython signature: void setLogType(LogType) Sets the progress log that should be used. The default type is NONE!

setName()

Cython signature: void setName(const String &) Sets the name

setParameters()

Cython signature: void setParameters(Param & param) Sets the parameters

setProgress()

Cython signature: void setProgress(ptrdiff_t value) Sets the current progress

startProgress()

Cython signature: void startProgress(ptrdiff_t begin, ptrdiff_t end, String label)