Bio::T...ignalp(3pm)

💖 Bio::Tools::Signalp::ExtendedSignalp — the manual page, bestie edition 💖

okay so you found the Bio::T...ignalp(3pm) page, which is the User Contributed Perl Documentation for this lil module. Buckle up, we're doing bioinformatics but make it cute ✨

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✨ NAME ✨

Bio::Tools::Signalp::ExtendedSignalp — it's an enhanced parser for Signalp output. Basically the glow-up version of the original parser. 👑

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🦋 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;
}

literally the whole vibe in six lines, no cap. 🫶

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🌸 DESCRIPTION 🌸

quick PSA bestie: please direct questions and support issues to bioperl-l@bioperl.org 💌

So. It's a parser module for Signalp. 📖

It's based on the EnsEMBL module Bio::EnsEMBL::Pipeline::Runnable::Protein::Signalp, which was originally written by Marc Sohrmann (ms2 a sanger.ac.uk). Then it got written into BioPipe by Balamurugan Kumarasamy (savikalpa a fugu-sg.org), and it's cared for by the Fugu Informatics team (fuguteam@fugu-sg.org). ✨ a whole lineage, we love to see it.

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

Now the actual tea ☕ — compared to the original SignalP, this method lets you filter results out based on maxC, maxY, maxS, meanS and D factor cutoff — and that's 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 be applied on the NN method. Also, to ensure compatibility with the 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 user gives a list, then the parser will only report protein having 'YES' for each factor. all-or-nothing behaviour, very main character energy 💅

This module supports parsing for full, summary and short output form signalp. And actually — full and summary are equivalent in terms of filtering results. same thing, different font 💀

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💌 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. 📝 (yes, "reponsive" is spelled like that in the original, we're keeping it, it's iconic 🎀)

🐛 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

do NOT just suffer in silence, bestie, file the bug. 🔥

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👑 AUTHOR 👑

Based on the Bio::Tools::Signalp module

Emmanuel Quevillon <emmanuel.quevillon@versailles.inra.fr>

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🧚 APPENDIX 🧚

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

🌟 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 :

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that's the whole page, you ate it, you understood it, periodt. 💅✨

perl v5.32.1 — 2021-08-15 — that's the version and date, and this manual page was brought to you by the Bio::T...ignalp(3pm) page itself, mwah 💖