PeptideIndexing#
- class pyopenms.PeptideIndexing#
Bases:
objectCython implementation of _PeptideIndexing
- Original C++ documentation is available here
– Inherits from [‘DefaultParamHandler’]
Refreshes the protein references for all peptide hits in a vector of PeptideIdentifications and adds target/decoy information
All peptide and protein hits are annotated with target/decoy information, using the meta value “target_decoy”. For proteins the possible values are “target” and “decoy”, depending on whether the protein accession contains the decoy pattern (parameter decoy_string) as a suffix or prefix, respectively (see parameter prefix). For peptides, the possible values are “target”, “decoy” and “target+decoy”, depending on whether the peptide sequence is found only in target proteins, only in decoy proteins, or in both. The target/decoy information is crucial for the @ref TOPP_FalseDiscoveryRate tool. (For FDR calculations, “target+decoy” peptide hits count as target hits.)
- __init__()#
Overload:
- __init__(self) None
Overload:
- __init__(self, in_0: PeptideIndexing) None
Methods
getDecoyString(self)getDefaults(self)Returns the default parameters
getName(self)Returns the name
getParameters(self)Returns the parameters
getSubsections(self)isPrefix(self)run(self, proteins, prot_ids, pep_ids)setName(self, in_0)Sets the name
setParameters(self, param)Sets the parameters
- PeptideIndexing_ExitCodes#
alias of
__PeptideIndexing_ExitCodes
- getSubsections(self) List[bytes]#
- isPrefix(self) bool#
- run(self, proteins: List[FASTAEntry], prot_ids: List[ProteinIdentification], pep_ids: PeptideIdentificationList) int#