Repository revision
11:73d288112aef

Repository 'openms_idposteriorerrorprobability'
hg clone https://toolshed.g2.bx.psu.edu/repos/galaxyp/openms_idposteriorerrorprobability

IDPosteriorErrorProbability tool metadata
Miscellaneous
Estimates probabilities for incorrectly assigned peptide sequences and a set of search engine scores using a mixture model.
IDPosteriorErrorProbability
toolshed.g2.bx.psu.edu/repos/galaxyp/openms_idposteriorerrorprobability/IDPosteriorErrorProbability/2.5+galaxy0
2.5+galaxy0
None
True
Version lineage of this tool (guids ordered most recent to oldest)
toolshed.g2.bx.psu.edu/repos/galaxyp/openms_idposteriorerrorprobability/IDPosteriorErrorProbability/2.6+galaxy0
toolshed.g2.bx.psu.edu/repos/galaxyp/openms_idposteriorerrorprobability/IDPosteriorErrorProbability/2.5+galaxy0 (this tool)
toolshed.g2.bx.psu.edu/repos/galaxyp/openms_idposteriorerrorprobability/IDPosteriorErrorProbability/2.3.0
toolshed.g2.bx.psu.edu/repos/galaxyp/openms_idposteriorerrorprobability/IDPosteriorErrorProbability/2.2.0
toolshed.g2.bx.psu.edu/repos/galaxyp/openms_idposteriorerrorprobability/IDPosteriorErrorProbability/2.1.0
IDPosteriorErrorProbability
Requirements (dependencies defined in the <requirements> tag set)
name version type
openms 2.5 package
openms-thirdparty 2.5 package
blast 2.9.0 package
openjdk 8.0.192 package
ctdopts 1.4 package
Functional tests
name inputs outputs required files
Test-1 in: IDPosteriorErrorProbability_Mascot_input.idXML
split_charge: False
top_hits_only: False
ignore_bad_data: False
prob_correct: False
fit_algorithm|number_of_bins: 100
fit_algorithm|incorrectly_assigned: Gumbel
fit_algorithm|max_nr_iterations: 1000
fit_algorithm|neg_log_delta: 6
fit_algorithm|outlier_handling: ignore_iqr_outliers
adv_opts_cond|fdr_for_targets_smaller: 0.05
adv_opts_cond|force: False
adv_opts_cond|test: true
adv_opts_cond|adv_opts_selector: advanced
OPTIONAL_OUTPUTS: ctd_out_FLAG
name: value
name: value
IDPosteriorErrorProbability_Mascot_input.idXML
value
Test-2 in: IDPosteriorErrorProbability_XTandem_input.idXML
split_charge: False
top_hits_only: False
ignore_bad_data: False
prob_correct: False
fit_algorithm|number_of_bins: 100
fit_algorithm|incorrectly_assigned: Gumbel
fit_algorithm|max_nr_iterations: 1000
fit_algorithm|neg_log_delta: 6
fit_algorithm|outlier_handling: ignore_iqr_outliers
adv_opts_cond|fdr_for_targets_smaller: 0.05
adv_opts_cond|force: False
adv_opts_cond|test: true
adv_opts_cond|adv_opts_selector: advanced
OPTIONAL_OUTPUTS: ctd_out_FLAG
name: value
name: value
IDPosteriorErrorProbability_XTandem_input.idXML
value
Test-3 in: IDPosteriorErrorProbability_OMSSA_input.idXML
split_charge: False
top_hits_only: False
ignore_bad_data: False
prob_correct: False
fit_algorithm|number_of_bins: 100
fit_algorithm|incorrectly_assigned: Gumbel
fit_algorithm|max_nr_iterations: 1000
fit_algorithm|neg_log_delta: 6
fit_algorithm|outlier_handling: ignore_iqr_outliers
adv_opts_cond|fdr_for_targets_smaller: 0.05
adv_opts_cond|force: False
adv_opts_cond|test: true
adv_opts_cond|adv_opts_selector: advanced
OPTIONAL_OUTPUTS: ctd_out_FLAG
name: value
name: value
IDPosteriorErrorProbability_OMSSA_input.idXML
value
Test-4 in: IDPosteriorErrorProbability_OMSSA_input2.idXML
split_charge: True
top_hits_only: False
ignore_bad_data: False
prob_correct: False
fit_algorithm|number_of_bins: 100
fit_algorithm|incorrectly_assigned: Gumbel
fit_algorithm|max_nr_iterations: 1000
fit_algorithm|neg_log_delta: 6
fit_algorithm|outlier_handling: ignore_iqr_outliers
adv_opts_cond|fdr_for_targets_smaller: 0.05
adv_opts_cond|force: False
adv_opts_cond|test: true
adv_opts_cond|adv_opts_selector: advanced
OPTIONAL_OUTPUTS: ctd_out_FLAG
name: value
name: value
IDPosteriorErrorProbability_OMSSA_input2.idXML
value
Test-5 in: IDPosteriorErrorProbability_XTandem_input2.idXML
split_charge: True
top_hits_only: False
ignore_bad_data: False
prob_correct: False
fit_algorithm|number_of_bins: 100
fit_algorithm|incorrectly_assigned: Gumbel
fit_algorithm|max_nr_iterations: 1000
fit_algorithm|neg_log_delta: 6
fit_algorithm|outlier_handling: ignore_iqr_outliers
adv_opts_cond|fdr_for_targets_smaller: 0.05
adv_opts_cond|force: False
adv_opts_cond|test: true
adv_opts_cond|adv_opts_selector: advanced
OPTIONAL_OUTPUTS: ctd_out_FLAG
name: value
name: value
IDPosteriorErrorProbability_XTandem_input2.idXML
value
Test-6 in: IDPosteriorErrorProbability_Mascot_input2.idXML
split_charge: True
top_hits_only: False
ignore_bad_data: False
prob_correct: False
fit_algorithm|number_of_bins: 100
fit_algorithm|incorrectly_assigned: Gumbel
fit_algorithm|max_nr_iterations: 1000
fit_algorithm|neg_log_delta: 6
fit_algorithm|outlier_handling: ignore_iqr_outliers
adv_opts_cond|fdr_for_targets_smaller: 0.05
adv_opts_cond|force: False
adv_opts_cond|test: true
adv_opts_cond|adv_opts_selector: advanced
OPTIONAL_OUTPUTS: ctd_out_FLAG
name: value
name: value
IDPosteriorErrorProbability_Mascot_input2.idXML
value
Test-7 in: IDPosteriorErrorProbability_bad_data.idXML
split_charge: False
top_hits_only: False
ignore_bad_data: True
prob_correct: False
fit_algorithm|number_of_bins: 100
fit_algorithm|incorrectly_assigned: Gumbel
fit_algorithm|max_nr_iterations: 1000
fit_algorithm|neg_log_delta: 6
fit_algorithm|outlier_handling: ignore_iqr_outliers
adv_opts_cond|fdr_for_targets_smaller: 0.05
adv_opts_cond|force: False
adv_opts_cond|test: true
adv_opts_cond|adv_opts_selector: advanced
OPTIONAL_OUTPUTS: ctd_out_FLAG
name: value
name: value
IDPosteriorErrorProbability_bad_data.idXML
value
Test-8 in: IDPosteriorErrorProbability_OMSSA_input.idXML
split_charge: False
top_hits_only: False
ignore_bad_data: False
prob_correct: True
fit_algorithm|number_of_bins: 100
fit_algorithm|incorrectly_assigned: Gumbel
fit_algorithm|max_nr_iterations: 1000
fit_algorithm|neg_log_delta: 6
fit_algorithm|outlier_handling: ignore_iqr_outliers
adv_opts_cond|fdr_for_targets_smaller: 0.05
adv_opts_cond|force: False
adv_opts_cond|test: true
adv_opts_cond|adv_opts_selector: advanced
OPTIONAL_OUTPUTS: ctd_out_FLAG
name: value
name: value
IDPosteriorErrorProbability_OMSSA_input.idXML
value