Epifany

Runs a Bayesian protein inference.

Web Documentation for Epifany

Options

version
Version of the tool that generated this parameters file.
protein_fdr
Additionally calculate the target-decoy FDR on protein-level based on the posteriors
conservative_fdr
Use (D+1)/(T) instead of (D+1)/(T+D) for reporting protein FDRs.
picked_fdr
Use picked protein FDRs.
picked_decoy_string
If using picked protein FDRs, which decoy string was used? Leave blank for auto-detection.
picked_decoy_prefix
If using picked protein FDRs, was the decoy string a prefix or suffix? Ignored during auto-detection.
greedy_group_resolution
Post-process inference output with greedy resolution of shared peptides based on the parent protein probabilities. Also adds the resolved ambiguity groups to output.
min_psms_extreme_probability
Set PSMs with probability lower than this to this minimum probability.
max_psms_extreme_probability
Set PSMs with probability higher than this to this maximum probability.
log
Name of log file (created only when specified)
debug
Sets the debug level
threads
Sets the number of threads allowed to be used by the TOPP tool
no_progress
Disables progress logging to command line
force
Overrides tool-specific checks
test
Enables the test mode (needed for internal use only)
psm_probability_cutoff
Remove PSMs with probabilities less than this cutoff
top_PSMs
Consider only top X PSMs per spectrum. 0 considers all.
keep_best_PSM_only
Epifany uses the best PSM per peptide for inference. Discard the rest (true) or keepe.g. for quantification/reporting?
update_PSM_probabilities
(Experimental:) Update PSM probabilities with their posteriors under consideration of the protein probabilities.
user_defined_priors
(Experimental:) Uses the current protein scores as user-defined priors.
annotate_group_probabilities
Annotates group probabilities for indistinguishable protein groups (indistinguishable by experimentally observed PSMs).
use_ids_outside_features
(Only consensusXML) Also use IDs without associated features for inference?
prot_prior
Protein prior probability ('gamma' parameter). Negative values enable grid search for this param.
pep_emission
Peptide emission probability ('alpha' parameter). Negative values enable grid search for this param.
pep_spurious_emission
Spurious peptide identification probability ('beta' parameter). Usually much smaller than emission from proteins. Negative values enable grid search for this param.
pep_prior
Peptide prior probability (experimental, should be covered by combinations of the other params).
regularize
Regularize the number of proteins that produce a peptide together (experimental, should be activated when using higher p-norms).
extended_model
Uses information from different peptidoforms also across runs (automatically activated if an experimental design is given!)
scheduling_type
(Not used yet) How to pick the next message: priority = based on difference to last message (higher = more important). fifo = first in first out. subtree = message passing follows a random spanning tree in each iteration
convergence_threshold
Initial threshold under which MSE difference a message is considered to be converged.
dampening_lambda
Initial value for how strongly should messages be updated in each step. 0 = new message overwrites old completely (no dampening; only recommended for trees),0.5 = equal contribution of old and new message (stay below that),In-between it will be a convex combination of both. Prevents oscillations but hinders convergence.
max_nr_iterations
(Usually auto-determined by estimated but you can set a hard limit here). If not all messages converge, how many iterations should be done at max per connected component?
p_norm_inference
P-norm used for marginalization of multidimensional factors. 1 == sum-product inference (all configurations vote equally) (default),<= 0 == infinity = max-product inference (only best configurations propagate)The higher the value the more important high probability configurations get.
aucweight
How important is target decoy AUC vs calibration of the posteriors? 0 = maximize calibration only, 1 = maximize AUC only, between = convex combination.
conservative_fdr
Use (D+1)/(T) instead of (D+1)/(T+D) for parameter estimation.
regularized_fdr
Use a regularized FDR for proteins without unique peptides.

Input Ports

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Input: identification results [idXML,consensusXML]
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(Currently unused) Input: experimental design [tsv,opt.]

Output Ports

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Output: identification results with scored/grouped proteins [idXML,consensusXML]

Views

Epifany Std Output
The text sent to standard out during the execution of Epifany.
Epifany Error Output
The text sent to standard error during the execution of Epifany. (If it appears in gray, it's the output of a previously failing run which is preserved for your trouble shooting.)

Workflows

Links

Developers

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