OpenMS
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Implements a mixture model of the inverse gumbel and the gauss distribution or a gaussian mixture. More...
#include <OpenMS/MATH/STATISTICS/PosteriorErrorProbabilityModel.h>
Public Member Functions | |
PosteriorErrorProbabilityModel () | |
default constructor More... | |
~PosteriorErrorProbabilityModel () override | |
Destructor. More... | |
bool | fit (std::vector< double > &search_engine_scores, const String &outlier_handling) |
fits the distributions to the data points(search_engine_scores). Estimated parameters for the distributions are saved in member variables. computeProbability can be used afterwards. Uses two Gaussians to fit. And Gauss+Gauss or Gumbel+Gauss to plot and calculate final probabilities. More... | |
bool | fitGumbelGauss (std::vector< double > &search_engine_scores, const String &outlier_handling) |
fits the distributions to the data points(search_engine_scores). Estimated parameters for the distributions are saved in member variables. computeProbability can be used afterwards. Uses Gumbel+Gauss for everything. Fits Gumbel by maximizing log likelihood. More... | |
bool | fit (std::vector< double > &search_engine_scores, std::vector< double > &probabilities, const String &outlier_handling) |
fits the distributions to the data points(search_engine_scores) and writes the computed probabilities into the given vector (the second one). More... | |
void | fillDensities (const std::vector< double > &x_scores, std::vector< double > &incorrect_density, std::vector< double > &correct_density) |
Writes the distributions densities into the two vectors for a set of scores. Incorrect_densities represent the incorrectly assigned sequences. More... | |
void | fillLogDensities (const std::vector< double > &x_scores, std::vector< double > &incorrect_density, std::vector< double > &correct_density) |
Writes the log distributions densities into the two vectors for a set of scores. Incorrect_densities represent the incorrectly assigned sequences. More... | |
void | fillLogDensitiesGumbel (const std::vector< double > &x_scores, std::vector< double > &incorrect_density, std::vector< double > &correct_density) |
Writes the log distributions of gumbel and gauss densities into the two vectors for a set of scores. Incorrect_densities represent the incorrectly assigned sequences. More... | |
double | computeLogLikelihood (const std::vector< double > &incorrect_density, const std::vector< double > &correct_density) const |
computes the Likelihood with a log-likelihood function. More... | |
double | computeLLAndIncorrectPosteriorsFromLogDensities (const std::vector< double > &incorrect_log_density, const std::vector< double > &correct_log_density, std::vector< double > &incorrect_posterior) const |
std::pair< double, double > | pos_neg_mean_weighted_posteriors (const std::vector< double > &x_scores, const std::vector< double > &incorrect_posteriors) |
std::pair< double, double > | pos_neg_sigma_weighted_posteriors (const std::vector< double > &x_scores, const std::vector< double > &incorrect_posteriors, const std::pair< double, double > &pos_neg_mean) |
GaussFitter::GaussFitResult | getCorrectlyAssignedFitResult () const |
returns estimated parameters for correctly assigned sequences. Fit should be used before. More... | |
GaussFitter::GaussFitResult | getIncorrectlyAssignedFitResult () const |
returns estimated parameters for correctly assigned sequences. Fit should be used before. More... | |
GumbelMaxLikelihoodFitter::GumbelDistributionFitResult | getIncorrectlyAssignedGumbelFitResult () const |
returns estimated parameters for correctly assigned sequences. Fit should be used before. More... | |
double | getNegativePrior () const |
returns the estimated negative prior probability. More... | |
double | computeProbability (double score) const |
TextFile | initPlots (std::vector< double > &x_scores) |
initializes the plots More... | |
const String | getGumbelGnuplotFormula (const GaussFitter::GaussFitResult ¶ms) const |
returns the gnuplot formula of the fitted gumbel distribution. Only x0 and sigma are used as local parameter alpha and scale parameter beta, respectively. More... | |
const String | getGaussGnuplotFormula (const GaussFitter::GaussFitResult ¶ms) const |
returns the gnuplot formula of the fitted gauss distribution. More... | |
const String | getBothGnuplotFormula (const GaussFitter::GaussFitResult &incorrect, const GaussFitter::GaussFitResult &correct) const |
returns the gnuplot formula of the fitted mixture distribution. More... | |
void | plotTargetDecoyEstimation (std::vector< double > &target, std::vector< double > &decoy) |
plots the estimated distribution against target and decoy hits More... | |
double | getSmallestScore () const |
returns the smallest score used in the last fit More... | |
void | tryGnuplot (const String &gp_file) |
try to invoke 'gnuplot' on the file to create PDF automatically More... | |
Public Member Functions inherited from DefaultParamHandler | |
DefaultParamHandler (const String &name) | |
Constructor with name that is displayed in error messages. More... | |
DefaultParamHandler (const DefaultParamHandler &rhs) | |
Copy constructor. More... | |
virtual | ~DefaultParamHandler () |
Destructor. More... | |
DefaultParamHandler & | operator= (const DefaultParamHandler &rhs) |
Assignment operator. More... | |
virtual bool | operator== (const DefaultParamHandler &rhs) const |
Equality operator. More... | |
void | setParameters (const Param ¶m) |
Sets the parameters. More... | |
const Param & | getParameters () const |
Non-mutable access to the parameters. More... | |
const Param & | getDefaults () const |
Non-mutable access to the default parameters. More... | |
const String & | getName () const |
Non-mutable access to the name. More... | |
void | setName (const String &name) |
Mutable access to the name. More... | |
const std::vector< String > & | getSubsections () const |
Non-mutable access to the registered subsections. More... | |
Static Public Member Functions | |
static std::map< String, std::vector< std::vector< double > > > | extractAndTransformScores (const std::vector< ProteinIdentification > &protein_ids, const std::vector< PeptideIdentification > &peptide_ids, const bool split_charge, const bool top_hits_only, const bool target_decoy_available, const double fdr_for_targets_smaller) |
extract and transform score types to a range and score orientation that the PEP model can handle More... | |
static void | updateScores (const PosteriorErrorProbabilityModel &PEP_model, const String &search_engine, const Int charge, const bool prob_correct, const bool split_charge, std::vector< ProteinIdentification > &protein_ids, std::vector< PeptideIdentification > &peptide_ids, bool &unable_to_fit_data, bool &data_might_not_be_well_fit) |
update score entries with PEP (or 1-PEP) estimates More... | |
static double | getGumbel_ (double x, const GaussFitter::GaussFitResult ¶ms) |
computes the gumbel density at position x with parameters params. More... | |
Static Public Member Functions inherited from DefaultParamHandler | |
static void | writeParametersToMetaValues (const Param &write_this, MetaInfoInterface &write_here, const String &key_prefix="") |
Writes all parameters to meta values. More... | |
Private Member Functions | |
void | processOutliers_ (std::vector< double > &x_scores, const String &outlier_handling) const |
transform different score types to a range and score orientation that the model can handle (engine string is assumed in upper-case) More... | |
PosteriorErrorProbabilityModel & | operator= (const PosteriorErrorProbabilityModel &rhs) |
assignment operator (not implemented) More... | |
PosteriorErrorProbabilityModel (const PosteriorErrorProbabilityModel &rhs) | |
Copy constructor (not implemented) More... | |
Static Private Member Functions | |
static double | transformScore_ (const String &engine, const PeptideHit &hit, const String ¤t_score_type) |
static double | getScore_ (const std::vector< String > &requested_score_types, const PeptideHit &hit, const String &actual_score_type) |
Private Attributes | |
GaussFitter::GaussFitResult | incorrectly_assigned_fit_param_ |
stores parameters for incorrectly assigned sequences. If gumbel fit was used, A can be ignored. Furthermore, in this case, x0 and sigma are the local parameter alpha and scale parameter beta, respectively. More... | |
GumbelMaxLikelihoodFitter::GumbelDistributionFitResult | incorrectly_assigned_fit_gumbel_param_ |
GaussFitter::GaussFitResult | correctly_assigned_fit_param_ |
stores gauss parameters More... | |
double | negative_prior_ |
stores final prior probability for negative peptides More... | |
double | max_incorrectly_ |
peak of the incorrectly assigned sequences distribution More... | |
double | max_correctly_ |
peak of the gauss distribution (correctly assigned sequences) More... | |
double | smallest_score_ |
smallest score which was used for fitting the model More... | |
const String(PosteriorErrorProbabilityModel::* | getNegativeGnuplotFormula_ )(const GaussFitter::GaussFitResult ¶ms) const |
points either to getGumbelGnuplotFormula or getGaussGnuplotFormula depending on whether one uses the gumbel or the gaussian distribution for incorrectly assigned sequences. More... | |
const String(PosteriorErrorProbabilityModel::* | getPositiveGnuplotFormula_ )(const GaussFitter::GaussFitResult ¶ms) const |
points to getGumbelGnuplotFormula More... | |
Additional Inherited Members | |
Protected Member Functions inherited from DefaultParamHandler | |
virtual void | updateMembers_ () |
This method is used to update extra member variables at the end of the setParameters() method. More... | |
void | defaultsToParam_ () |
Updates the parameters after the defaults have been set in the constructor. More... | |
Protected Attributes inherited from DefaultParamHandler | |
Param | param_ |
Container for current parameters. More... | |
Param | defaults_ |
Container for default parameters. This member should be filled in the constructor of derived classes! More... | |
std::vector< String > | subsections_ |
Container for registered subsections. This member should be filled in the constructor of derived classes! More... | |
String | error_name_ |
Name that is displayed in error messages during the parameter checking. More... | |
bool | check_defaults_ |
If this member is set to false no checking if parameters in done;. More... | |
bool | warn_empty_defaults_ |
If this member is set to false no warning is emitted when defaults are empty;. More... | |
Implements a mixture model of the inverse gumbel and the gauss distribution or a gaussian mixture.
This class fits either a Gumbel distribution and a Gauss distribution to a set of data points or two Gaussian distributions using the EM algorithm. One can output the fit as a gnuplot formula using getGumbelGnuplotFormula() and getGaussGnuplotFormula() after fitting.
test performance and make fitGumbelGauss available via parameters.
allow charge state based fitting
allow semi-supervised by using decoy annotations
allow non-parametric via kernel density estimation
Name | Type | Default | Restrictions | Description |
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out_plot | string | If given, the some output files will be saved in the following manner: |
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number_of_bins | int | 100 | Number of bins used for visualization. Only needed if each iteration step of the EM-Algorithm will be visualized | |
incorrectly_assigned | string | Gumbel | Gumbel, Gauss | for 'Gumbel', the Gumbel distribution is used to plot incorrectly assigned sequences. For 'Gauss', the Gauss distribution is used. |
max_nr_iterations | int | 1000 | Bounds the number of iterations for the EM algorithm when convergence is slow. | |
neg_log_delta | int | 6 | The negative logarithm of the convergence threshold for the likelihood increase. | |
outlier_handling | string | ignore_iqr_outliers | ignore_iqr_outliers, set_iqr_to_closest_valid, ignore_extreme_percentiles, none | What to do with outliers: - ignore_iqr_outliers: ignore outliers outside of 3*IQR from Q1/Q3 for fitting - set_iqr_to_closest_valid: set IQR-based outliers to the last valid value for fitting - ignore_extreme_percentiles: ignore everything outside 99th and 1st percentile (also removes equal values like potential censored max values in XTandem) - none: do nothing |
default constructor
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override |
Destructor.
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private |
Copy constructor (not implemented)
double computeLLAndIncorrectPosteriorsFromLogDensities | ( | const std::vector< double > & | incorrect_log_density, |
const std::vector< double > & | correct_log_density, | ||
std::vector< double > & | incorrect_posterior | ||
) | const |
computes the posteriors for the datapoints to belong to the incorrect distribution
[in] | incorrect_log_density | ... |
[in] | correct_log_density | ... |
[out] | incorrect_posterior | resulting posteriors; same size as incorrect_log_density |
double computeLogLikelihood | ( | const std::vector< double > & | incorrect_density, |
const std::vector< double > & | correct_density | ||
) | const |
computes the Likelihood with a log-likelihood function.
double computeProbability | ( | double | score | ) | const |
Returns the computed posterior error probability for a given score.
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static |
extract and transform score types to a range and score orientation that the PEP model can handle
protein_ids | the protein identifications |
peptide_ids | the peptide identifications |
split_charge | whether different charge states should be treated separately |
top_hits_only | only consider rank 1 |
target_decoy_available | whether target decoy information is stored as meta value |
fdr_for_targets_smaller | fdr threshold for targets |
void fillDensities | ( | const std::vector< double > & | x_scores, |
std::vector< double > & | incorrect_density, | ||
std::vector< double > & | correct_density | ||
) |
Writes the distributions densities into the two vectors for a set of scores. Incorrect_densities represent the incorrectly assigned sequences.
void fillLogDensities | ( | const std::vector< double > & | x_scores, |
std::vector< double > & | incorrect_density, | ||
std::vector< double > & | correct_density | ||
) |
Writes the log distributions densities into the two vectors for a set of scores. Incorrect_densities represent the incorrectly assigned sequences.
void fillLogDensitiesGumbel | ( | const std::vector< double > & | x_scores, |
std::vector< double > & | incorrect_density, | ||
std::vector< double > & | correct_density | ||
) |
Writes the log distributions of gumbel and gauss densities into the two vectors for a set of scores. Incorrect_densities represent the incorrectly assigned sequences.
bool fit | ( | std::vector< double > & | search_engine_scores, |
const String & | outlier_handling | ||
) |
fits the distributions to the data points(search_engine_scores). Estimated parameters for the distributions are saved in member variables. computeProbability can be used afterwards. Uses two Gaussians to fit. And Gauss+Gauss or Gumbel+Gauss to plot and calculate final probabilities.
search_engine_scores | a vector which holds the data points |
outlier_handling | Valid values are in the Param 'outlier_handling' |
bool fit | ( | std::vector< double > & | search_engine_scores, |
std::vector< double > & | probabilities, | ||
const String & | outlier_handling | ||
) |
fits the distributions to the data points(search_engine_scores) and writes the computed probabilities into the given vector (the second one).
search_engine_scores | a vector which holds the data points | |
[out] | probabilities | Probability for each data point after running this function. If it has some content it will be overwritten. |
outlier_handling | Valid values are in the Param 'outlier_handling' |
bool fitGumbelGauss | ( | std::vector< double > & | search_engine_scores, |
const String & | outlier_handling | ||
) |
fits the distributions to the data points(search_engine_scores). Estimated parameters for the distributions are saved in member variables. computeProbability can be used afterwards. Uses Gumbel+Gauss for everything. Fits Gumbel by maximizing log likelihood.
search_engine_scores | a vector which holds the data points |
outlier_handling | Valid values are in the Param 'outlier_handling' |
const String getBothGnuplotFormula | ( | const GaussFitter::GaussFitResult & | incorrect, |
const GaussFitter::GaussFitResult & | correct | ||
) | const |
returns the gnuplot formula of the fitted mixture distribution.
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inline |
returns estimated parameters for correctly assigned sequences. Fit should be used before.
const String getGaussGnuplotFormula | ( | const GaussFitter::GaussFitResult & | params | ) | const |
returns the gnuplot formula of the fitted gauss distribution.
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inlinestatic |
computes the gumbel density at position x with parameters params.
References GaussFitter::GaussFitResult::sigma, and GaussFitter::GaussFitResult::x0.
const String getGumbelGnuplotFormula | ( | const GaussFitter::GaussFitResult & | params | ) | const |
returns the gnuplot formula of the fitted gumbel distribution. Only x0 and sigma are used as local parameter alpha and scale parameter beta, respectively.
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inline |
returns estimated parameters for correctly assigned sequences. Fit should be used before.
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inline |
returns estimated parameters for correctly assigned sequences. Fit should be used before.
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inline |
returns the estimated negative prior probability.
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staticprivate |
gets a specific score (either main score [preferred] or metavalue)
requested_score_types | the requested score_types in order of preference (will be tested with a "_score" suffix as well) |
hit | the PeptideHit to extract from |
actual_score_type | the current score type to take preference if matching |
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inline |
returns the smallest score used in the last fit
TextFile initPlots | ( | std::vector< double > & | x_scores | ) |
initializes the plots
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private |
assignment operator (not implemented)
void plotTargetDecoyEstimation | ( | std::vector< double > & | target, |
std::vector< double > & | decoy | ||
) |
plots the estimated distribution against target and decoy hits
std::pair<double, double> pos_neg_mean_weighted_posteriors | ( | const std::vector< double > & | x_scores, |
const std::vector< double > & | incorrect_posteriors | ||
) |
x_scores | Scores observed "on the x-axis" |
incorrect_posteriors | Posteriors/responsibilities of belonging to the incorrect component |
std::pair<double, double> pos_neg_sigma_weighted_posteriors | ( | const std::vector< double > & | x_scores, |
const std::vector< double > & | incorrect_posteriors, | ||
const std::pair< double, double > & | pos_neg_mean | ||
) |
x_scores | Scores observed "on the x-axis" |
incorrect_posteriors | Posteriors/responsibilities of belonging to the incorrect component |
pos_neg_mean | Positive(correct) and negative(incorrect) means, respectively |
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private |
transform different score types to a range and score orientation that the model can handle (engine string is assumed in upper-case)
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staticprivate |
transform different score types to a range and score orientation that the model can handle (engine string is assumed in upper-case)
engine | the search engine name as in the SE param object |
hit | the PeptideHit to extract transformed scores from |
current_score_type | the current score type of the PeptideIdentification to take precedence |
void tryGnuplot | ( | const String & | gp_file | ) |
try to invoke 'gnuplot' on the file to create PDF automatically
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static |
update score entries with PEP (or 1-PEP) estimates
PEP_model | the PEP model used to update the scores |
search_engine | the score of search_engine will be updated |
charge | identifications with the given charge will be updated |
prob_correct | report 1-PEP |
split_charge | if charge states have been treated separately |
protein_ids | the protein identifications |
peptide_ids | the peptide identifications |
unable_to_fit_data | there was a problem fitting the data (probabilities are all smaller 0 or larger 1) |
data_might_not_be_well_fit | fit was successful but of bad quality (probabilities are all smaller 0.8 and larger 0.2) |
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private |
stores gauss parameters
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private |
points either to getGumbelGnuplotFormula or getGaussGnuplotFormula depending on whether one uses the gumbel or the gaussian distribution for incorrectly assigned sequences.
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private |
points to getGumbelGnuplotFormula
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private |
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private |
stores parameters for incorrectly assigned sequences. If gumbel fit was used, A can be ignored. Furthermore, in this case, x0 and sigma are the local parameter alpha and scale parameter beta, respectively.
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private |
peak of the gauss distribution (correctly assigned sequences)
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private |
peak of the incorrectly assigned sequences distribution
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private |
stores final prior probability for negative peptides
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private |
smallest score which was used for fitting the model