peptdeep.spec_lib.library_factory

Library classes to predict library from sequences, modified peptides, precursors, or proteins (fasta files).

Classes:

FastaLibraryMaker([model_manager])	For fasta or a list of fasta files
LibraryMakerProvider()	Factory class for library makers
PSMReaderLibraryMaker([model_manager])
PeptideLibraryMaker([model_manager])	For input dataframe of modified sequences
PrecursorLibraryMaker([model_manager])	For input dataframe of charged modified sequences
PredictLibraryMakerBase([model_manager])	Base class to predict libraries
SequenceLibraryMaker([model_manager])	For input dataframe of AA sequences

Functions:

load_dfs(infiles)

class peptdeep.spec_lib.library_factory.FastaLibraryMaker(model_manager: ModelManager = None)

Bases: PredictLibraryMakerBase

For fasta or a list of fasta files

class peptdeep.spec_lib.library_factory.LibraryMakerProvider

Bases: object

Factory class for library makers

Methods:

__init__()
get_maker(maker_name, *[, model_manager])
register_maker(maker_name, maker_class)

__init__()

get_maker(maker_name: str, *, model_manager=None) → PredictLibraryMakerBase

register_maker(maker_name: str, maker_class)

class peptdeep.spec_lib.library_factory.PSMReaderLibraryMaker(model_manager: ModelManager = None)

Bases: PredictLibraryMakerBase

class peptdeep.spec_lib.library_factory.PeptideLibraryMaker(model_manager: ModelManager = None)

Bases: PrecursorLibraryMaker

For input dataframe of modified sequences

class peptdeep.spec_lib.library_factory.PrecursorLibraryMaker(model_manager: ModelManager = None)

Bases: PredictLibraryMakerBase

For input dataframe of charged modified sequences

class peptdeep.spec_lib.library_factory.PredictLibraryMakerBase(model_manager: ModelManager = None)

Bases: object

Base class to predict libraries

Methods:

__init__([model_manager])
make_library(infiles)	Predict a library for the infiles, this function runs the following methods.
translate_library([translate_mod_dict])	Translate predicted DataFrames into a single DataFrame in SWATH library format
translate_to_tsv(tsv_path[, translate_mod_dict])	Translate the predicted DataFrames into a TSV file

Attributes:

fragment_intensity_df
fragment_mz_df
precursor_df

__init__(model_manager: ModelManager = None)

property fragment_intensity_df: DataFrame

property fragment_mz_df: DataFrame

make_library(infiles: str | list | DataFrame)

Predict a library for the infiles, this function runs the following methods.

• self._input(infiles)

• self._check_df()

• self._predict()

Parameters:

_input – _input file or source

Raises:

ValueError – ValueError for some reasons

property precursor_df: DataFrame

translate_library(translate_mod_dict: dict = None) → DataFrame

Translate predicted DataFrames into a single DataFrame in SWATH library format

translate_to_tsv(tsv_path: str, translate_mod_dict: dict = None)

Translate the predicted DataFrames into a TSV file

class peptdeep.spec_lib.library_factory.SequenceLibraryMaker(model_manager: ModelManager = None)

Bases: PeptideLibraryMaker

For input dataframe of AA sequences

peptdeep.spec_lib.library_factory.load_dfs(infiles)