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lib/Bio/Chado/Schema/Result/Companalysis/Analysisfeature.pm  view on Meta::CPAN

    following semantics: * normscores are floating point numbers >= 0,
    * high normscores are better than low one. For most programs, it would be sufficient to make the normscore the same as this rawscore, providing these semantics are satisfied.

=head2 significance

  data_type: 'double precision'
  is_nullable: 1

This is some kind of expectation or probability metric, representing the probability that the analysis would appear randomly given the model. As such, any program or person querying this table can assume the following semantics:
   * 0 <= significance <= n, where n is a positive number, theoretically unbounded but unlikely to be more than 10
  * low numbers are better than high numbers.

=head2 identity

  data_type: 'double precision'
  is_nullable: 1

Percent identity between the locations compared.  Note that these 4 metrics do not cover the full range of scores possible; it would be undesirable to list every score possible, as this should be kept extensible. instead, for non-standard scores, use...

=cut

__PACKAGE__->add_columns(
  "analysisfeature_id",
  {
    data_type         => "integer",
    is_auto_increment => 1,
    is_nullable       => 0,
    sequence          => "analysisfeature_analysisfeature_id_seq",
  },
  "feature_id",
  { data_type => "integer", is_foreign_key => 1, is_nullable => 0 },
  "analysis_id",
  { data_type => "integer", is_foreign_key => 1, is_nullable => 0 },
  "rawscore",
  { data_type => "double precision", is_nullable => 1 },
  "normscore",
  { data_type => "double precision", is_nullable => 1 },
  "significance",
  { data_type => "double precision", is_nullable => 1 },
  "identity",
  { data_type => "double precision", is_nullable => 1 },
);
__PACKAGE__->set_primary_key("analysisfeature_id");
__PACKAGE__->add_unique_constraint("analysisfeature_c1", ["feature_id", "analysis_id"]);

=head1 RELATIONS

=head2 feature

Type: belongs_to

Related object: L<Bio::Chado::Schema::Result::Sequence::Feature>

=cut

__PACKAGE__->belongs_to(
  "feature",
  "Bio::Chado::Schema::Result::Sequence::Feature",
  { feature_id => "feature_id" },
  {
    cascade_copy   => 0,
    cascade_delete => 0,
    is_deferrable  => 1,
    on_delete      => "CASCADE",
    on_update      => "CASCADE",
  },
);

=head2 analysis

Type: belongs_to

Related object: L<Bio::Chado::Schema::Result::Companalysis::Analysis>

=cut

__PACKAGE__->belongs_to(
  "analysis",
  "Bio::Chado::Schema::Result::Companalysis::Analysis",
  { analysis_id => "analysis_id" },
  {
    cascade_copy   => 0,
    cascade_delete => 0,
    is_deferrable  => 1,
    on_delete      => "CASCADE",
    on_update      => "CASCADE",
  },
);

=head2 analysisfeatureprops

Type: has_many

Related object: L<Bio::Chado::Schema::Result::Companalysis::Analysisfeatureprop>

=cut

__PACKAGE__->has_many(
  "analysisfeatureprops",
  "Bio::Chado::Schema::Result::Companalysis::Analysisfeatureprop",
  { "foreign.analysisfeature_id" => "self.analysisfeature_id" },
  { cascade_copy => 0, cascade_delete => 0 },
);


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