view variant_effect_predictor/Bio/EnsEMBL/Funcgen/Collection/ResultFeature.pm @ 3:d30fa12e4cc5 default tip

Merge heads 2:a5976b2dce6f and 1:09613ce8151e which were created as a result of a recently fixed bug.

#
# Ensembl module for Bio::EnsEMBL::Funcgen::Collection::ResultFeature
#
=head1 LICENSE

  Copyright (c) 1999-2011 The European Bioinformatics Institute and
  Genome Research Limited.  All rights reserved.

  This software is distributed under a modified Apache license.
  For license details, please see

    http://www.ensembl.org/info/about/code_licence.html

=head1 CONTACT

  Please email comments or questions to the public Ensembl
  developers list at <[e-mail]>.

  Questions may also be sent to the Ensembl help desk at
  <[e-mail]>.


=head1 NAME

Bio::EnsEMBL::Funcgen::Collection::ResultFeature - A module to represent a lightweight ResultFeature collection

=head1 SYNOPSIS

use Bio::EnsEMBL::Funcgen::Collection::ResultFeature;

my $rfeature = Bio::EnsEMBL::Funcgen::Collection::ResultFeature->new_fast({
   start  => $start, 
   end    => $end, 
   scores => [ $score ]
});

my @rfeatures = @{$rset->get_displayable_ResultFeatures_by_Slice($slice)};

foreach my $rfeature (@rfeatures){
    my $score = $rfeature->score();
    my $rf_start = $rfeature->start();
    my $rf_end = $rfeature->end();
}

=head1 DESCRIPTION

This is a Collection feature which is designed to store compressed/collected 
feature information for a defined window/bin size over a complete seq_region.
Or alternatively a single feature at the natural resolution i.e. window_size == 0.
The complete seq_region collections are cropped to provide a ResultFeature on any
given Slice. ResultFeatures are primarily stored in the result_feature table, 
but can also be generated on the fly from unprocessed data in the array result
tables.


=head1 SEE ALSO

Bio::EnsEMBL::Funcgen::DBSQL::ResultFeatureAdaptor
Bio::EnsEMBL::Funcgen::Collector::ResultFeature

=cut


#This is distinct from a normal feature as the collection may have differen attributes and methods from the normal feature
#implementation.  For example a Bio::EnsEMBL::Collection::Gene would only have summary information over several genes.
#Altho', unlikely that we'll ever collect genes.

use strict;
use warnings;


package Bio::EnsEMBL::Funcgen::Collection::ResultFeature;
use base ('Bio::EnsEMBL::Feature');#@ISA

#This needs to inherit from Bio::EnsEMBL::Collection
#Which can host some of the below methods

#Reverted to hash implementation as we no longer deal with 
#huge amounts of features due to collections.
#This enables use of transform/seq_region_start/end methods
#and enable us to store on slices that do not begin at 1
#Altho need to remove code stipulating this



#To do
#Can we move any of these methods to a base Collection class?
#Should probably now use normal new method with validation?

=head2 new_fast

  Args       : Array with attributes start, end, strand, scores, probe, result_set_id, window_size, slice  IN THAT ORDER.
               WARNING: None of these are validated, hence can omit some where not needed
  Example    : none
  Description: Fast and list version of new. Only works if the code is very disciplined.
  Returntype : Bio::EnsEMBL::Funcgen::ResultFeature
  Exceptions : None
  Caller     : ResultSetAdaptor
  Status     : At Risk

=cut

sub new_fast {
  #This is agnostic towards to type of reference
  return bless ($_[1], $_[0]);

}



=head2 scores

  Example    : my $score = $rf->score();
  Description: Getter of the scores attribute for ResultFeature
               objects
  Returntype : Arrayref.
  Exceptions : None
  Caller     : General
  Status     : At Risk

=cut

sub scores {  
  return $_[0]->{scores};
}



=head2 probe

  Example    : my $probe = $rf->probe();
  Description: Getter of the probe attribute for ResultFeature
               objects
  Returntype : Bio::EnsEMBL::Funcgen::Probe
  Exceptions : None
  Caller     : General
  Status     : At Risk - This can only be used for Features with window 0.

=cut

#probe_id is currently not available in the result_feature table, so this would be a result/probe_feature query.

sub probe {  
  return $_[0]->{probe};
}


sub result_set_id {  
  return $_[0]->{result_set_id};
}

sub window_size {  
  return $_[0]->{window_size};
}


sub get_min_max_scores{
  
  if(! defined $_[0]->{'min_max_scores'}){
	my @sorted_scores = sort { $a <=> $b } @{$_[0]->{'scores'}};
	$_[0]->{'min_max_scores'} = [$sorted_scores[0], $sorted_scores[$#sorted_scores]];
  }

  return $_[0]->{'min_max_scores'};
}


1;