Provided by: libbio-perl-perl_1.6.901-2_all bug

NAME

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

SYNOPSIS

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

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

DESCRIPTION

       # Please direct questions and support issues to bioperl-l@bioperl.org

       Parser module for Signalp.

       Based on the EnsEMBL module Bio::EnsEMBL::Pipeline::Runnable::Protein::Signalp originally
       written by Marc Sohrmann (ms2 a sanger.ac.uk) Written in BioPipe by Balamurugan Kumarasamy
       (savikalpa a fugu-sg.org) Cared for by the Fugu Informatics team (fuguteam@fugu-sg.org)

       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.

FEEDBACK

   Mailing Lists
       User feedback is an integral part of the evolution of this and other Bioperl modules. Send
       your comments and suggestions preferably to the Bioperl mailing list.  Your participation
       is much appreciated.

         bioperl-l@bioperl.org                  - General discussion
         http://bioperl.org/wiki/Mailing_lists  - About the mailing lists

   Support
       Please direct usage questions or support issues to the mailing list:

       bioperl-l@bioperl.org

       rather than to the module maintainer directly. Many experienced and reponsive experts will
       be able look at the problem and quickly address it. Please include a thorough description
       of the problem with code and data examples if at all possible.

   Reporting Bugs
       Report bugs to the Bioperl bug tracking system to help us keep track of the bugs and their
       resolution. Bug reports can be submitted via the web:

         https://redmine.open-bio.org/projects/bioperl/

AUTHOR

        Based on the Bio::Tools::Signalp module
        Emmanuel Quevillon <emmanuel.quevillon@versailles.inra.fr>

APPENDIX

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

   new
        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

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

   _filterok
        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

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

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

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

   _parse_summary_format
        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    :

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

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

   _parse_short_format
        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    :

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

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