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Commit 175fc2f0 authored by Andreas Kusalananda Kähäri's avatar Andreas Kusalananda Kähäri
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Added DESCRIPTION.

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......@@ -44,6 +44,91 @@ classes.
-method => 'coverage'
) };
=head1 DESCRIPTION
This is the abstract base class for feature collections.
In short, this class replaces the object creation routines in
Bio::EnsEMBL::DBSQL::BaseFeatureAdaptor with routines that creates
flat arrays. It also provides a way of binning features on a slice in
various different ways (see below).
A feature collection provides a compact representation of features of
a particular type on a slice. Each feature is represented by a short
array of attribute data. This data is divided into two halfs:
=over 4
=item 1.
Basic feature representation.
=item 2.
Extended feature representation.
=back
=head2 Basic feature representation
The basic feature representation is common to all features of any type
and consists of a minimal set of values. Each feature is represented by
an array that contains at least the following data (in this order)
=over 4
=item 1.
Ensembl internal database ID.
=item 2.
Ensembl internal sequence region ID.
=item 3.
Feature start position.
=item 4.
Feature end position.
=item 5.
Feature strand.
=back
The module defines a number of constants that may be used in place
of the index numbers 0 to 4: FEATURE_DBID, FEATURE_SEQREGIONID,
FEATURE_START, FEATURE_END, FEATURE_STRAND. For a feature $f,
$f->[Bio::EnsEMBL::Collection::FEATURE_END] will thus be the end
position for the feature that the array @{$f} represents.
The position of the feature is in the same coordinate system as the
slice used to fetch the features.
=head2 Extended feature representation
A sub-class of this abstract base class will specify further
data to be added to the features in order to account for the
particular feature type. A feature from a gene feature collection
(Bio::EnsEMBL::Collection::Gene) might, for example, contain the Ensembl
Stable ID of the gene.
The extended feature representation is defined by the method
_create_feature() or _create_feature_fast() which is implemented by the
sub-class. The extended representation is also documented in the POD of
each sub-class.
=head2 Light-weight features
A light-weight feature is a feature whose representation does not
contain the extended feature representation.
Light-weight features may be fetched by using the argument
'-lightweight=>1' in the fetch_bins_by_Slice() method.
=cut
use strict;
......
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