DataStructures - Alignment¶

This document contains information about the data structures used in the TRIC algorithm.

Run contains all data pertaining to a LC-MS/MS run, particularly references to measured precursors
PrecursorGroup represents a set of precursors (e.g. precursors deriving from the same peptide sequence but identified by different charge states and isotopic labelling); see also CyPrecursorGroup for a Cython implementation
A Precursor represents a single precursor (e.g. a single measured analyte with a precursor m/z identified by its chemical formula, charge state and isotopic labelling)
- PrecursorBase is a base implementation of a Precursor
- Precursor is the implementation of a Precursor using minimal memory, see also CyPrecursorWrapperOnly for a Cython implementation
- GeneralPrecursor is the default implementation of a Precursor
A peak group represents a single RT region in the chromatogram of a single Precursor
- PeakGroupBase is a base implementation of a Peakgroup
- MinimalPeakGroup is the implementation of a Peakgroup using minimal memory, see also CyPeakgroupWrapperOnly for a Cython implementation
- GeneralPeakGroup is the default implementation of a Peakgroup
- GuiPeakGroup is the implementation used by the GUI

`Run` Module¶

Run¶

class msproteomicstoolslib.data_structures.Run.Run(header, header_dict, runid, orig_input_filename=None, filename=None, aligned_filename=None, useCython=False)¶

A run contains references to identified precursor groups and precursors.

The run stores a reference to precursor groups (heavy/light pairs) identified in the run. It has a unique id and stores the headers from the csv

A run has the following attributes:

an identifier that is unique to this run
a filename where it originally came from
a dictionary of precursor groups which are accessible through the following functions - getPrecursorGroup - hasPrecursor - getPrecursor - addPrecursor

Parameters:	header (str) – Run header header_dict (dict) – Run header dictionary runid (str) – Run header dictionary orig_input_filename (str) – Original filname of the csv file filename (str) – Original filname of the mzML (e.g. the column “filename”) aligned_filename (str) – Aligned filename (e.g. the column “align_origfilename”)

addPrecursor(precursor, peptide_group_label)¶

Add a new precursor to the run using a specific peptide label.

If the corresponding precursor group does not yet exist, a new precursor group is created. Otherwise the precursor is added to the precursor group.

Parameters:	precursor (`CyPrecursor`, `Precursor` or `GeneralPrecursor`) – Precursor to be added (e.g. PEPT[+98]IDE/2) peptide_group_label (str) – Label of the corresponding peptide group (e.g. PEPTIDE)

getPrecursor(peptide_group_label, trgr_id)¶: Return precursor corresponding to the given peptide label group and the transition group id

getPrecursorGroup(curr_id)¶

get_aligned_filename()¶

get_best_peaks()¶: Return the best peakgroup for each peptide precursor

get_best_peaks_with_cutoff(cutoff)¶: Return the best peak per run (with cutoff)

get_id()¶

get_openswath_filename()¶

get_original_filename()¶

hasPrecursor(peptide_group_label, trgr_id)¶

`PrecursorGroup` Module¶

PrecursorGroup¶

class msproteomicstoolslib.data_structures.PrecursorGroup.PrecursorGroup(peptide_group_label, run)¶

Bases: object

A set of precursors that are isotopically modified versions or different charge states of each other.

A collection of precursors that are isotopically modified versions or different charge states of the same underlying peptide sequence. Generally these are heavy/light forms. This class groups these Precursors together.

- self.peptide_group_label_: Identifier or precursor group

- self.run_: Reference to the Run where this PrecursorGroup is from

- self.precursors_: List of actual precursors

addPrecursor(self, precursor)¶: Add precursor to peptide group

getAllPeakgroups(self)¶: Generator of all peakgroups attached to the precursors in this group

getAllPrecursors(self)¶: Return a list of all precursors in this precursor group

getOverallBestPeakgroup(self)¶: Get the best peakgroup (by fdr score) of all precursors contained in this precursor group

getPeptideGroupLabel(self)¶: Get peptide group label

getPrecursor(self, curr_id)¶: Get the precursor for the given transition group id

get_decoy()¶

Whether the current peptide is a decoy or not

Returns:	decoy – Whether the peptide is decoy or not
Return type:	bool

peptide_group_label_¶

precursors_¶

run_¶

`Precursor` Module¶

PrecursorBase¶

class msproteomicstoolslib.data_structures.Precursor.PrecursorBase(this_id, run)¶

Bases: object

find_closest_in_iRT(delta_assay_rt)¶

get_all_peakgroups()¶

get_best_peakgroup()¶

get_decoy()¶

get_id()¶

get_selected_peakgroup()¶

select_pg(this_id)¶

set_decoy(decoy)¶

unselect_pg(id)¶

GeneralPrecursor¶

class msproteomicstoolslib.data_structures.Precursor.GeneralPrecursor(this_id, run)¶

Bases: msproteomicstoolslib.data_structures.Precursor.PrecursorBase

A set of peakgroups that belong to the same precursor in a single run.

== Implementation details ==

This is a plain implementation where all peakgroup objects are stored in a simple list, this is not very efficient since many objects need to be created which in Python takes a lot of memory.

add_peakgroup(peakgroup)¶

append(transitiongroup)¶

find_closest_in_iRT(delta_assay_rt)¶

getProteinName()¶

getRun()¶

getRunId()¶

getSequence()¶

get_all_peakgroups()¶

get_best_peakgroup()¶: Return the best peakgroup according to fdr score

get_run_id()¶

get_selected_peakgroup()¶

id¶

peakgroups¶

precursor_group¶

protein_name¶

run¶

sequence¶

setProteinName(p)¶

setSequence(s)¶

set_precursor_group(p)¶

Precursor¶

class msproteomicstoolslib.data_structures.Precursor.Precursor(this_id, run)¶

Bases: msproteomicstoolslib.data_structures.Precursor.PrecursorBase

A set of peakgroups that belong to the same precursor in a single run.

Each precursor has a backreference to its precursor group (heavy/light pair) it belongs to, the run it belongs to as well as its amino acid sequence. Furthermore, a unique id for the precursor and the protein name are stored.

A precursor can return its best transition group, the selected peakgroup, or can return the transition group that is closest to a given iRT time. Its id is the transition_group_id (e.g. the id of the chromatogram)

The “selected” peakgroup is represented by the peakgroup that belongs to cluster number 1 (cluster_id == 1) which in this case is “special”.

== Implementation details ==

For memory reasons, we store all information about the peakgroup in a tuple (invariable). This tuple contains a unique feature id, a score and a retention time. Additionally, we also store, in which cluster the peakgroup belongs (if the user sets this).

A peakgroup has the following attributes:

an identifier that is unique among all other precursors
a set of peakgroups
a back-reference to the run it belongs to

add_peakgroup_tpl(pg_tuple, tpl_id, cluster_id=-1)¶

Adds a peakgroup to this precursor.

The peakgroup should be a tuple of length 4 with the following components:

id
quality score (FDR)
retention time (normalized)

3. intensity (4. d_score optional)

cluster_ids_¶

find_closest_in_iRT(delta_assay_rt)¶

getAllPeakgroups()¶

getClusteredPeakgroups()¶

getPrecursorGroup()¶

getProteinName()¶

getRun()¶

getRunId()¶

getSequence()¶

get_all_peakgroups()¶

get_best_peakgroup()¶

get_id()¶

get_run_id()¶

get_selected_peakgroup()¶

id¶

peakgroups_¶

precursor_group¶

protein_name¶

run¶

select_pg(this_id)¶

sequence¶

setClusterID(this_id, cl_id)¶

setProteinName(p)¶

setSequence(s)¶

set_precursor_group(p)¶

unselect_all()¶

unselect_pg(this_id)¶

`PeakGroup` Module¶

PeakGroupBase¶

class msproteomicstoolslib.data_structures.PeakGroup.PeakGroupBase¶

Bases: object

A single peakgroup that is defined by a retention time in a chromatogram of multiple transitions. Additionally it has an fdr_score and it has an aligned RT (e.g. retention time in normalized space). A peakgroup can be selected for quantification or not (this is stored as having cluster_id == 1).

For each precursor, there can be multiple clusters of peakgroups, with the first (or best) one generally being in cluster 1, therefore we store a cluster id. Generally, an alignment algorithm will assign a cluster id to zero, one or more peakgroups of each precursor.

cluster_id_¶

fdr_score¶

get_cluster_id()¶

get_fdr_score()¶

get_feature_id()¶

get_intensity()¶

get_normalized_retentiontime()¶

get_value(value)¶

id_¶

intensity_¶

is_selected()¶

normalized_retentiontime¶

select_this_peakgroup()¶

set_fdr_score(fdr_score)¶

set_feature_id(id_)¶

set_intensity(intensity)¶

set_normalized_retentiontime(normalized_retentiontime)¶

set_value(key, value)¶

MinimalPeakGroup¶

class msproteomicstoolslib.data_structures.PeakGroup.MinimalPeakGroup(unique_id, fdr_score, assay_rt, selected, cluster_id, peptide, intensity=None, dscore=None)¶

Bases: msproteomicstoolslib.data_structures.PeakGroup.PeakGroupBase

See PeakGroupBase for a detailed description.

This implementation is designed to be immutable as the actual data is stored in the Precursor class which generates this object on-the-fly to improve memory performance.

getPeptide()¶

get_cluster_id()¶

get_dscore()¶

print_out()¶

select_this_peakgroup()¶: Select this peakgroup for quantification (assigns cluster id 1; works since it calls back to its Precursor obj)

setClusterID(id_)¶: Set cluster id (works since it calls back to its Precursor obj)

set_fdr_score(fdr_score)¶: Raises exception as this object is immutable

set_feature_id(id_)¶: Raises exception as this object is immutable

set_intensity(intensity)¶: Raises exception as this object is immutable

set_normalized_retentiontime(normalized_retentiontime)¶: Raises exception as this object is immutable

GuiPeakGroup¶

class msproteomicstoolslib.data_structures.PeakGroup.GuiPeakGroup(fdr_score, intensity, leftWidth, rightWidth, assay_rt, peptide)¶

Bases: msproteomicstoolslib.data_structures.PeakGroup.PeakGroupBase

See PeakGroupBase for a detailed description.

This implementation stores additional information including left/right width.

get_value(value)¶

GeneralPeakGroup¶

class msproteomicstoolslib.data_structures.PeakGroup.GeneralPeakGroup(row, run, peptide)¶

Bases: msproteomicstoolslib.data_structures.PeakGroup.PeakGroupBase

See PeakGroupBase for a detailed description.

This implementation stores the full row read from the CSV file including all meta-data. It is generally not recommended to use this implementation unless for toy examples.

getPeptide()¶

get_dscore()¶

get_value(value)¶

peptide¶

print_out()¶

row¶

run¶

setClusterID(clid)¶

set_value(key, value)¶

DataStructures - Basic¶

`Aminoacides` Module¶

Aminoacid¶

class msproteomicstoolslib.data_structures.aminoacides.Aminoacid(name, code, code3, composition)¶

Class to hold information about a single Amino Acid (AA)

code = None¶: One letter code

code3 = None¶: Three letter code

composition = None¶: Elemental composition

elementsLib = None¶: Library of elements

name = None¶: Full name of the AA

Aminoacides¶

class msproteomicstoolslib.data_structures.aminoacides.Aminoacides¶

addAminoacid(aminoacid)¶

getAminoacid(code)¶

initAminoacides()¶

`Modifications` Module¶

Modification¶

class msproteomicstoolslib.data_structures.modifications.Modification(aminoacid, tpp_Mod, unimodAccession, peakViewAccession, is_labeling, composition)¶

A modification on an Aminoacid

codes = ['TPP', 'unimod', 'ProteinPilot']¶: Available modification formats

getcode(code)¶

Modifications¶

class msproteomicstoolslib.data_structures.modifications.Modifications(default_mod_file=None)¶

A collection of modifications

appendModification(modification)¶

is_bool(expression)¶

printModifications()¶

readModificationsFile(modificationsfile)¶: It reads a tsv file with additional modifications. Modifications will be appended to the default modifications of this class. Tsv file headers & an example: modified-AA TPP-nomenclature Unimod-Accession ProteinPilot-nomenclature is_a_labeling composition-dictionary S S[167] 21 [Pho] False {‘H’ : 1,’O’ : 3, ‘P’ : 1}

translateModificationsFromSequence(sequence, code, aaLib=None)¶: Returns a Peptide object, given a sequence with modifications in any of the available codes. The code (TPP, Unimod,...) to be translated must be given.

`Peak` Module¶

Peak¶

class msproteomicstoolslib.data_structures.peak.Peak(str=None, spectraST=False)¶

Represents one peak of a spectrum.

init_with_self(peak)¶

initialize(peak, intensity, peak_annotation, statistics)¶

parse_str(peak)¶

to_write_string()¶

`Peptide` Module¶

Peptide¶

class msproteomicstoolslib.data_structures.peptide.Peptide(sequence, modifications={}, protein='', aminoacidLib=None)¶

addSpectrum(spectrum)¶: Deprecated definition

all_ions(ionseries=None, frg_z_list=[1, 2], fragmentlossgains=[0], mass_limits=None, label='')¶: Returns all the fragment ions of the peptide in a tuple of two objects: (annotated, ionmasses_only) annotated is a list of tuples as : (ion_type, ion_number, ion_charge, lossgain, fragment_mz) ionmasses_only is a list of fragment masses. When ionseries is not provided, all existing ion series (see: Peptide.iontypes) will be calculated. When frg_z_list is not provided, fragment ion charge states +1 and +2 will be used.

calIsoforms(switchingModification, modLibrary)¶: This returns the full list of peptide species of the same peptide family (isobaric, same composition, different modification site. The list is given as a list of Peptide objects. switchingModification must be given as a Modification object.

cal_UIS(otherPeptidesList, UISorder=2, ionseries=None, fragmentlossgains=[0], precision=1e-08, frg_z_list=[1, 2], mass_limits=None)¶: It calculates the UIS for a given peptide referred to a given list of other peptides. It returns a tuple of two objects all_UIS, and all_UIS_annotated. all_UIS contains only a mass list.

comparePeptideFragments(otherPeptidesList, ionseries=None, fragmentlossgains=[0], precision=1e-08, frg_z_list=[1, 2])¶: This returns a tuple of lists: (CommonFragments, differentialFragments). The differentialFragmentMasses are the masses of the __self__ peptide are not shared with any of the peptides listed in the otherPeptidesList. otherPeptidesList must be a list of Peptide objects. The fragments are reported as a tuple : (ionserie,ion_number,ion_charge,frqgmentlossgain,mass)

fragmentSequence(ion_type, frg_number)¶

getDeltaMassFromSequence(sequence)¶

getMZ(charge, label='')¶

getMZfragment(ion_type, ion_number, ion_charge, label='', fragmentlossgain=0.0)¶

getSequenceWithMods(code)¶

get_decoy_Q3(frg_serie, frg_nr, frg_z, blackList=[], max_tries=1000)¶

pseudoreverse(sequence='None')¶

shuffle_sequence()¶

`Residues` Module¶

Residues¶

class msproteomicstoolslib.data_structures.Residues.Residues(type='mono')¶

A class that contains information elements, amino acids and modifications. It stores mainly masse of these but also chemical formulas.

The most commonly used properties are:

Residues.average_elments : element weights

Residues.monoisotopic_elments : element weights

Residues.aa_codes : Three and One letter amino acid codes

Residues.aa_names : English names of the amino acids

Residues.aa_sum_formulas_text : Chemical formulas of all amino acids

Residues.aa_sum_formulas: Chemical formulas of all amino acids as hash

Residues.mass_xxx: monoisotopic masses of different compounds (NH3, H2O, CO, HPO4 etc)

Residues.average_data: average weight of amino acids

Residues.monoisotopic_data: monoisotopic weight of amino acids

Residues.monoisotopic_mod: monoisotopic modification data

Residues.mod_mapping: mapping of + notation to absolute weight notation (K[+8] to K[136])

Residues.Hydropathy: Hydropathy of amino acids (gravy scores)

TODO hydrophobicity of amino acids

TODO basicity of amino acids

TODO helicity of amino acids

Residues.pI: pI of amino acids

`DDB` Module¶

DDB¶

Abstraction layer to the 2DDB software framework.

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DataStructures - Alignment¶

`Run` Module¶

Run¶

`PrecursorGroup` Module¶

PrecursorGroup¶

`Precursor` Module¶

PrecursorBase¶

GeneralPrecursor¶

Precursor¶

`PeakGroup` Module¶

PeakGroupBase¶

MinimalPeakGroup¶

GuiPeakGroup¶

GeneralPeakGroup¶

DataStructures - Basic¶

`Aminoacides` Module¶

Aminoacid¶

Aminoacides¶

`Modifications` Module¶

Modification¶

Modifications¶

`Peak` Module¶

Peak¶

`Peptide` Module¶

Peptide¶

`Residues` Module¶

Residues¶

`DDB` Module¶

DDB¶

DataStructures - Alignment¶

Run Module¶

Run¶

PrecursorGroup Module¶

PrecursorGroup¶

Precursor Module¶

PrecursorBase¶

GeneralPrecursor¶

Precursor¶

PeakGroup Module¶

PeakGroupBase¶

MinimalPeakGroup¶

GuiPeakGroup¶

GeneralPeakGroup¶

DataStructures - Basic¶

Aminoacides Module¶

Aminoacid¶

Aminoacides¶

Modifications Module¶

Modification¶

Modifications¶

Peak Module¶

Peak¶

Peptide Module¶

Peptide¶

Residues Module¶

Residues¶

DDB Module¶

DDB¶

`Run` Module¶

`PrecursorGroup` Module¶

`Precursor` Module¶

`PeakGroup` Module¶

`Aminoacides` Module¶

`Modifications` Module¶

`Peak` Module¶

`Peptide` Module¶

`Residues` Module¶

`DDB` Module¶