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Bio::Tools::Signalp::ExtendedSignalp - enhanced parser for Signalp output


 use Bio::Tools::Signalp::ExtendedSignalp;
 my $params = [qw(maxC maxY maxS meanS D)];
 my $parser = new Bio::Tools::Signalp::ExtendedSignalp(
                                                       -fh      => $filehandle
                                                       -factors => $params

 while( my $sp_feat = $parser->next_feature ) {
       #do something
       push @sp_feat, $sp_feat;


# Please direct questions and support issues to

Parser module for Signalp.

Based on the EnsEMBL module Bio::EnsEMBL::Pipeline::Runnable::Protein::Signalp originally written by Marc Sohrmann (ms2 a Written in BioPipe by Balamurugan Kumarasamy (savikalpa a Cared for by the Fugu Informatics team (

You may distribute this module under the same terms as perl itself

Compared to the original SignalP, this method allow the user to filter results out based on maxC maxY maxS meanS and D factor cutoff for the Neural Network (NN) method only. The HMM method does not give any filters with 'YES' or 'NO' as result.

The user must be aware that the filters can only by applied on NN method. Also, to ensure the compatibility with original Signalp parsing module, the user must know that by default, if filters are empty, max Y and mean S filters are automatically used to filter results.

If the used gives a list, then the parser will only report protein having 'YES' for each factor.

This module supports parsing for full, summary and short output form signalp. Actually, full and summary are equivalent in terms of filtering results.


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 Based on the Bio::Tools::Signalp module
 Emmanuel Quevillon <>


 The rest of the documentation details each of the object methods.
 Internal methods are usually preceded with a _


 Title   : new
 Usage   : my $obj = new Bio::Tools::Signalp::ExtendedSignalp();
 Function: Builds a new Bio::Tools::Signalp::ExtendedSignalp object
 Returns : Bio::Tools::Signalp::ExtendedSignalp
 Args    : -fh/-file => $val, # for initing input, see Bio::Root::IO


 Title   : next_feature
 Usage   : my $feat = $signalp->next_feature
 Function: Get the next result feature from parser data
 Returns : Bio::SeqFeature::Generic
 Args    : none


 Title   : _filterok
 Usage   : my $feat = $signalp->_filterok
 Function: Check if the factors required by the user are all ok.
 Returns : 1/0
 Args    : hash reference


 Title   : factors
 Usage   : my $feat = $signalp->factors
 Function: Get/Set the filters required from the user
 Returns : hash
 Args    : array reference


 Title   : _parsed
 Usage   : obj->_parsed()
 Function: Get/Set if the result is parsed or not
 Returns : 1/0 scalar
 Args    : On set 1


 Title   : _parse
 Usage   : obj->_parse
 Function: Parse the SignalP result
 Returns :
 Args    :


 Title   : _parse_summary_format
 Usage   : $self->_parse_summary_format
 Function: Method to parse summary/full format from signalp output
           It automatically fills filtered features.
 Returns :
 Args    :


 Title   : _parse_nn_result
 Usage   : obj->_parse_nn_result
 Function: Parses the Neuronal Network (NN) part of the result
 Returns : Hash reference
 Args    :


 Title   : _parse_hmm_result
 Usage   : obj->_parse_hmm_result
 Function: Parses the Hiden Markov Model (HMM) part of the result
 Returns : Hash reference
 Args    :


 Title   : _parse_short_format
 Usage   : $self->_parse_short_format
 Function: Method to parse short format from signalp output
           It automatically fills filtered features.
 Returns :
 Args    :


 Title   : create_feature
 Usage   : obj->create_feature(\%feature)
 Function: Internal(not to be used directly)
 Returns :
 Args    :


 Title   : seqname
 Usage   : obj->seqname($name)
 Function: Internal(not to be used directly)
 Returns :
 Args    :