OpenMS
FalseDiscoveryRate.h
Go to the documentation of this file.
1 // --------------------------------------------------------------------------
2 // OpenMS -- Open-Source Mass Spectrometry
3 // --------------------------------------------------------------------------
4 // Copyright The OpenMS Team -- Eberhard Karls University Tuebingen,
5 // ETH Zurich, and Freie Universitaet Berlin 2002-2023.
6 //
7 // This software is released under a three-clause BSD license:
8 // * Redistributions of source code must retain the above copyright
9 // notice, this list of conditions and the following disclaimer.
10 // * Redistributions in binary form must reproduce the above copyright
11 // notice, this list of conditions and the following disclaimer in the
12 // documentation and/or other materials provided with the distribution.
13 // * Neither the name of any author or any participating institution
14 // may be used to endorse or promote products derived from this software
15 // without specific prior written permission.
16 // For a full list of authors, refer to the file AUTHORS.
17 // --------------------------------------------------------------------------
18 // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
19 // AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
20 // IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
21 // ARE DISCLAIMED. IN NO EVENT SHALL ANY OF THE AUTHORS OR THE CONTRIBUTING
22 // INSTITUTIONS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
23 // EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
24 // PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;
25 // OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
26 // WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR
27 // OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF
28 // ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
29 //
30 // --------------------------------------------------------------------------
31 // $Maintainer: Chris Bielow $
32 // $Authors: Andreas Bertsch, Chris Bielow $
33 // --------------------------------------------------------------------------
34 
35 #pragma once
36 
42 
43 #include <unordered_map>
44 
45 #include <vector>
46 #include <unordered_set>
47 
48 namespace OpenMS
49 {
50 
51  struct ScoreToTgtDecLabelPairs;
52 
77  class OPENMS_DLLAPI FalseDiscoveryRate :
78  public DefaultParamHandler
79  {
80 public:
83 
90  void apply(std::vector<PeptideIdentification>& fwd_ids, std::vector<PeptideIdentification>& rev_ids) const;
91 
98  void apply(std::vector<PeptideIdentification>& id, bool annotate_peptide_fdr = false) const;
99 
106  void apply(std::vector<ProteinIdentification>& fwd_ids, std::vector<ProteinIdentification>& rev_ids) const;
107 
113  void apply(std::vector<ProteinIdentification>& ids) const;
114 
120  void applyEstimated(std::vector<ProteinIdentification>& ids) const;
121 
131  double applyEvaluateProteinIDs(const std::vector<ProteinIdentification>& ids, double pepCutoff = 1.0, UInt fpCutoff = 50, double diffWeight = 0.2) const;
141  double applyEvaluateProteinIDs(const ProteinIdentification& ids, double pepCutoff = 1.0, UInt fpCutoff = 50, double diffWeight = 0.2) const;
142 
152  double applyEvaluateProteinIDs(ScoreToTgtDecLabelPairs& score_to_tgt_dec_fraction_pairs, double pepCutoff = 1.0, UInt fpCutoff = 50, double diffWeight = 0.2) const;
153 
155  void applyBasic(const std::vector<ProteinIdentification> & run_info, std::vector<PeptideIdentification> & ids);
156 
158  void applyBasic(std::vector<PeptideIdentification> & ids, bool higher_score_better, int charge = 0, String identifier = "", bool only_best_per_pep = false);
161  void applyBasicPeptideLevel(std::vector<PeptideIdentification> & ids);
164  void applyBasicPeptideLevel(ConsensusMap & ids, bool use_unassigned_peptides = true);
166  void applyBasic(ConsensusMap & cmap, bool use_unassigned_peptides = true);
168  void applyBasic(ProteinIdentification & id, bool groups_too = true);
169 
179  void applyPickedProteinFDR(ProteinIdentification& id, String decoy_string = "", bool prefix = true, bool groups_too = true);
180 
183  double rocN(const std::vector<PeptideIdentification>& ids, Size fp_cutoff) const;
184 
187  double rocN(const std::vector<PeptideIdentification>& ids, Size fp_cutoff, const String& identifier) const;
188 
191  double rocN(const ConsensusMap& ids, Size fp_cutoff, bool include_unassigned_peptides = false) const;
192 
195  double rocN(const ConsensusMap& ids, Size fp_cutoff, const String& identifier, bool include_unassigned_peptides = false) const;
196 
197  //TODO the next two methods could potentially be merged for speed (they iterate over the same structure)
198  //But since they have different cutoff types and it is more generic, I leave it like this.
200  double diffEstimatedEmpirical(const ScoreToTgtDecLabelPairs& scores_labels, double pepCutoff = 1.0) const;
201 
204  double rocN(const ScoreToTgtDecLabelPairs& scores_labels, Size fpCutoff = 50) const;
205 
215 
220  {
221  public:
225  struct Result
226  {
227  bool success;
229  bool is_prefix;
230  };
231 
239  };
240 private:
241 
244 
247 
249  void calculateFDRs_(std::map<double, double>& score_to_fdr, std::vector<double>& target_scores, std::vector<double>& decoy_scores, bool q_value, bool higher_score_better) const;
250 
255  std::vector<double>& target_scores,
256  std::vector<double>& decoy_scores,
257  std::map<IdentificationData::IdentifiedMolecule, bool>& molecule_to_decoy,
258  std::map<IdentificationData::ObservationMatchRef, double>& match_to_score) const;
259 
262  void calculateEstimatedQVal_(std::map<double, double> &scores_to_FDR,
263  ScoreToTgtDecLabelPairs &scores_labels,
264  bool higher_score_better) const;
265 
271  void calculateFDRBasic_(std::map<double,double>& scores_to_FDR, ScoreToTgtDecLabelPairs& scores_labels, bool qvalue, bool higher_score_better) const;
272 
275  double trapezoidal_area_xEqy(double exp1, double exp2, double act1, double act2) const;
276 
278  double trapezoidal_area(double x1, double x2, double y1, double y2) const;
279  };
280 
281 } // namespace OpenMS
A container for consensus elements.
Definition: ConsensusMap.h:92
A base class for all classes handling default parameters.
Definition: DefaultParamHandler.h:92
Finds decoy strings in ProteinIdentification runs.
Definition: FalseDiscoveryRate.h:220
bool is_prefix
on success, was it a prefix or suffix
Definition: FalseDiscoveryRate.h:229
bool success
did more than 30% of proteins have the *same* prefix or suffix
Definition: FalseDiscoveryRate.h:227
static Result findDecoyString(const ProteinIdentification &proteins)
String name
on success, what was the decoy string?
Definition: FalseDiscoveryRate.h:228
Finds the most common decoy string in the accessions of proteins. Checks for suffix and prefix and so...
Definition: FalseDiscoveryRate.h:226
Calculates false discovery rates (FDR) from identifications.
Definition: FalseDiscoveryRate.h:79
void applyBasic(ConsensusMap &cmap, bool use_unassigned_peptides=true)
simpler reimplementation of the apply function above for peptides in ConsensusMaps.
double applyEvaluateProteinIDs(const std::vector< ProteinIdentification > &ids, double pepCutoff=1.0, UInt fpCutoff=50, double diffWeight=0.2) const
Calculate a linear combination of the area of the difference in estimated vs. empirical (TD) FDR and ...
FalseDiscoveryRate & operator=(const FalseDiscoveryRate &)
Not implemented.
void apply(std::vector< PeptideIdentification > &fwd_ids, std::vector< PeptideIdentification > &rev_ids) const
Calculates the FDR of two runs, a forward run and a decoy run on peptide level.
double rocN(const std::vector< PeptideIdentification > &ids, Size fp_cutoff) const
double rocN(const ConsensusMap &ids, Size fp_cutoff, const String &identifier, bool include_unassigned_peptides=false) const
void apply(std::vector< PeptideIdentification > &id, bool annotate_peptide_fdr=false) const
Calculates the FDR of one run from a concatenated sequence DB search.
void applyBasicPeptideLevel(ConsensusMap &ids, bool use_unassigned_peptides=true)
void applyBasic(const std::vector< ProteinIdentification > &run_info, std::vector< PeptideIdentification > &ids)
simpler reimplementation of the apply function above for PSMs. With charge and identifier info from r...
void applyPickedProteinFDR(ProteinIdentification &id, String decoy_string="", bool prefix=true, bool groups_too=true)
Applies a picked protein FDR. Behaves like a normal target-decoy FDR where only the score of the best...
void applyBasicPeptideLevel(std::vector< PeptideIdentification > &ids)
void apply(std::vector< ProteinIdentification > &fwd_ids, std::vector< ProteinIdentification > &rev_ids) const
Calculates the FDR of two runs, a forward run and decoy run on protein level.
FalseDiscoveryRate()
Default constructor.
void applyBasic(std::vector< PeptideIdentification > &ids, bool higher_score_better, int charge=0, String identifier="", bool only_best_per_pep=false)
simpler reimplementation of the apply function above for PSMs or peptides.
double diffEstimatedEmpirical(const ScoreToTgtDecLabelPairs &scores_labels, double pepCutoff=1.0) const
calculates the area of the difference between estimated and empirical FDR on the fly....
void applyEstimated(std::vector< ProteinIdentification > &ids) const
Calculate the FDR based on PEPs or PPs (if present) and modifies the IDs inplace.
IdentificationData::ScoreTypeRef applyToObservationMatches(IdentificationData &id_data, IdentificationData::ScoreTypeRef score_ref) const
Calculate FDR on the level of observation matches (e.g. peptide-spectrum matches) for "general" ident...
void calculateFDRBasic_(std::map< double, double > &scores_to_FDR, ScoreToTgtDecLabelPairs &scores_labels, bool qvalue, bool higher_score_better) const
FalseDiscoveryRate(const FalseDiscoveryRate &)
Not implemented.
double applyEvaluateProteinIDs(ScoreToTgtDecLabelPairs &score_to_tgt_dec_fraction_pairs, double pepCutoff=1.0, UInt fpCutoff=50, double diffWeight=0.2) const
Calculate a linear combination of the area of the difference in estimated vs. empirical (TD) FDR and ...
void apply(std::vector< ProteinIdentification > &ids) const
Calculate the FDR of one run from a concatenated sequence db search.
double rocN(const std::vector< PeptideIdentification > &ids, Size fp_cutoff, const String &identifier) const
double rocN(const ConsensusMap &ids, Size fp_cutoff, bool include_unassigned_peptides=false) const
double trapezoidal_area_xEqy(double exp1, double exp2, double act1, double act2) const
void handleObservationMatch_(IdentificationData::ObservationMatchRef match_ref, IdentificationData::ScoreTypeRef score_ref, std::vector< double > &target_scores, std::vector< double > &decoy_scores, std::map< IdentificationData::IdentifiedMolecule, bool > &molecule_to_decoy, std::map< IdentificationData::ObservationMatchRef, double > &match_to_score) const
Helper function for applyToObservationMatches()
void calculateFDRs_(std::map< double, double > &score_to_fdr, std::vector< double > &target_scores, std::vector< double > &decoy_scores, bool q_value, bool higher_score_better) const
calculates the FDR, given two vectors of scores
double trapezoidal_area(double x1, double x2, double y1, double y2) const
calculates the trapezoidal area for a trapezoid with a flat horizontal base e.g. for an AUC
void applyBasic(ProteinIdentification &id, bool groups_too=true)
simpler reimplementation of the apply function above for proteins.
double applyEvaluateProteinIDs(const ProteinIdentification &ids, double pepCutoff=1.0, UInt fpCutoff=50, double diffWeight=0.2) const
Calculate a linear combination of the area of the difference in estimated vs. empirical (TD) FDR and ...
double rocN(const ScoreToTgtDecLabelPairs &scores_labels, Size fpCutoff=50) const
void calculateEstimatedQVal_(std::map< double, double > &scores_to_FDR, ScoreToTgtDecLabelPairs &scores_labels, bool higher_score_better) const
Definition: IdentificationData.h:113
Representation of a protein identification run.
Definition: ProteinIdentification.h:76
A more convenient string class.
Definition: String.h:60
unsigned int UInt
Unsigned integer type.
Definition: Types.h:94
size_t Size
Size type e.g. used as variable which can hold result of size()
Definition: Types.h:127
static String prefix(const String &this_s, size_t length)
Definition: StringUtilsSimple.h:147
Main OpenMS namespace.
Definition: FeatureDeconvolution.h:48
Wrapper that adds operator< to iterators, so they can be used as (part of) keys in maps/sets or multi...
Definition: MetaData.h:46
Definition: IDScoreGetterSetter.h:57