alphabase.psm_reader.msfragger_reader

Classes:

MSFraggerPepXML()
MSFragger_PSM_TSV_Reader(*[, ...])

class alphabase.psm_reader.msfragger_reader.MSFraggerPepXML

Bases: object

Methods:

__init__()

__init__()

class alphabase.psm_reader.msfragger_reader.MSFragger_PSM_TSV_Reader(*, column_mapping: dict = None, modification_mapping: dict = None, fdr=0.01, keep_decoy=False, rt_unit='second', **kwargs)

Bases: PSMReaderBase

Methods:

__init__(*[, column_mapping, ...])

The Base class for all PSMReaders.

__init__(*, column_mapping: dict = None, modification_mapping: dict = None, fdr=0.01, keep_decoy=False, rt_unit='second', **kwargs)

The Base class for all PSMReaders. The key of the sub-classes for different search engine format is to re-define column_mapping and modification_mapping.

Parameters:

• column_mapping (dict, optional) – A dict that maps alphabase’s columns to other search engine’s. The key of the column_mapping is alphabase’s column name, and the value could be the column name or a list of column names in other engine’s result. If it is None, this dict will be init by self._init_column_mapping. The dict values could be either str or list, for exaplme: ` columns_mapping = { 'sequence': 'NakedSequence', #str 'charge': 'Charge', #str 'proteins':['Proteins','UniprotIDs'], # list, this reader will automatically detect all of them. } ` Defaults to None.

• modification_mapping (dict, optional) – A dict that maps alphabase’s modifications to other engine’s. If it is None, this dict will be init by default modification mapping for each search engine (see psm_reader_yaml). The dict values can be either str or list, for exaplme: ` modification_mapping = { 'Oxidation@M': 'Oxidation (M)', # str 'Phospho@S': ['S(Phospho (STY))','S(ph)','pS'], # list, this reader will automatically detect all of them. } ` Defaults to None.

• fdr (float, optional) – FDR level to keep PSMs. Defaults to 0.01.

• keep_decoy (bool, optional) – If keep decoy PSMs in self.psm_df. Defautls to False.

column_mapping

Dict structure same as column_mapping in Args.

Type:

dict

modification_mapping

Dict structure same as modification_mapping in Args. We must use self.set_modification_mapping(new_mapping) to update it.

Type:

dict

_psm_df

the PSM DataFrame after loading from search engines.

Type:

pd.DataFrame

psm_df

the getter of self._psm_df

Type:

pd.DataFrame

keep_fdr

The only PSMs with FDR<=keep_fdr were returned in self._psm_df.

Type:

float

keep_decoy

If keep decoy PSMs in self.psm_df.

Type:

bool

_min_max_rt_norm

if True, the ‘rt_norm’ values in self._psm_df will be normalized by rt_norm = (self.psm_df.rt-rt_min)/(rt_max-rt_min). It is useful to normalize iRT values as they contain negative values. Defaults to False.

Type:

bool