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#egpush @sp_feat, $sp_feat;}
DESCRIPTION
# Please direct questions and support issues to [email protected]
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 ([email protected])
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
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Support
Please direct usage questions or support issues to the mailing list:
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://github.com/bioperl/bioperl-live/issues
AUTHOR
Based on the Bio::Tools::Signalp moduleEmmanuel Quevillon <[email protected]>
APPENDIX
The rest of the documentation details each of the object methods.Internal methods are usually preceded with a _
new
Title : newUsage : my $obj = new Bio::Tools::Signalp::ExtendedSignalp();Function: Builds a new Bio::Tools::Signalp::ExtendedSignalp objectReturns : Bio::Tools::Signalp::ExtendedSignalpArgs : -fh/-file => $val, # for initing input, see Bio::Root::IO
next_feature
Title : next_featureUsage : my $feat = $signalp->next_featureFunction: Get the next result feature from parser dataReturns : Bio::SeqFeature::GenericArgs : none
_filterok
Title : _filterokUsage : my $feat = $signalp->_filterokFunction: Check if the factors required by the user are all ok.Returns : 1/0Args : hash reference
factors
Title : factorsUsage : my $feat = $signalp->factorsFunction: Get/Set the filters required from the userReturns : hashArgs : array reference
_parsed
Title : _parsedUsage : obj->_parsed()Function: Get/Set if the result is parsed or notReturns : 1/0 scalarArgs : On set 1
_parse
Title : _parseUsage : obj->_parseFunction: Parse the SignalP resultReturns :Args :
_parse_summary_format
Title : _parse_summary_formatUsage : $self->_parse_summary_formatFunction: Method to parse summary/full format from signalp outputIt automatically fills filtered features.Returns :Args :
_parse_nn_result
Title : _parse_nn_resultUsage : obj->_parse_nn_resultFunction: Parses the Neuronal Network (NN) part of the resultReturns : Hash referenceArgs :
_parse_hmm_result
Title : _parse_hmm_resultUsage : obj->_parse_hmm_resultFunction: Parses the Hiden Markov Model (HMM) part of the resultReturns : Hash referenceArgs :
_parse_short_format
Title : _parse_short_formatUsage : $self->_parse_short_formatFunction: Method to parse short format from signalp outputIt automatically fills filtered features.Returns :Args :
create_feature
Title : create_featureUsage : obj->create_feature(\%feature)Function: Internal(not to be used directly)Returns :Args :
seqname
Title : seqnameUsage : obj->seqname($name)Function: Internal(not to be used directly)Returns :Args :