| Bio::Tools::Signalp::ExtendedSignalp(3pm) | User Contributed Perl Documentation | Bio::Tools::Signalp::ExtendedSignalp(3pm) |
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
);
$parser->factors($params);
while( my $sp_feat = $parser->next_feature ) {
#do something
#eg
push @sp_feat, $sp_feat;
}
# 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.
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
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.
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://github.com/bioperl/bioperl-live/issues
Based on the Bio::Tools::Signalp module Emmanuel Quevillon <emmanuel.quevillon@versailles.inra.fr>
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 :
| 2021-08-15 | perl v5.32.1 |