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Bio::DB::GFF::Adaptor::dbi::pg(3pm) User Contributed Perl Documentation Bio::DB::GFF::Adaptor::dbi::pg(3pm)

NAME

Bio::DB::GFF::Adaptor::dbi::pg -- Database adaptor for a specific postgres schema

NOTES

SQL commands that need to be executed before this adaptor will work:

  CREATE DATABASE <dbname>;

Also, select permission needs to be granted for each table in the database to the owner of the httpd process (usually 'nobody', but for some RedHat systems it is 'apache') if this adaptor is to be used with the Generic Genome Browser (gbrowse):

  CREATE USER nobody;
  GRANT SELECT ON TABLE fmeta                 TO nobody;
  GRANT SELECT ON TABLE fgroup                TO nobody;
  GRANT SELECT ON TABLE fdata                 TO nobody;
  GRANT SELECT ON TABLE fattribute_to_feature TO nobody;
  GRANT SELECT ON TABLE fdna                  TO nobody;
  GRANT SELECT ON TABLE fattribute            TO nobody;
  GRANT SELECT ON TABLE ftype                 TO nobody;

Optimizing the database

PostgreSQL generally requires some tuning before you get very good performance for large databases. For general information on tuning a PostgreSQL server, see http://www.varlena.com/GeneralBits/Tidbits/perf.html Of particular importance is executing VACUUM FULL ANALYZE whenever you change the database.

Additionally, for a GFF database, there are a few items you can tune. For each automatic class in your GBrowse conf file, there will be one or two searches done when searching for a feature. If there are lots of features, these search can take several seconds. To speed these searches, do two things:

1.
Set 'enable_seqscan = false' in your postgresql.conf file (and restart your server).
2.
Create 'partial' indexes for each automatic class, doing this for the example class 'Allele': 

  CREATE INDEX partial_allele_gclass ON 
    fgroup (lower('gname')) WHERE gclass='Allele';

And be sure to run VACUUM FULL ANALYZE after creating the indexes.

DESCRIPTION

This adaptor implements a specific postgres database schema that is compatible with Bio::DB::GFF. It inherits from Bio::DB::GFF::Adaptor::dbi, which itself inherits from Bio::DB::GFF.

The schema uses several tables:

This is the feature data table. Its columns are: 

    fid            feature ID (integer)
    fref           reference sequence name (string)
    fstart         start position relative to reference (integer)
    fstop          stop position relative to reference (integer)
    ftypeid        feature type ID (integer)
    fscore         feature score (float); may be null
    fstrand        strand; one of "+" or "-"; may be null
    fphase         phase; one of 0, 1 or 2; may be null
    gid            group ID (integer)
    ftarget_start  for similarity features, the target start position (integer)
    ftarget_stop   for similarity features, the target stop position (integer)

Note that it would be desirable to normalize the reference sequence name, since there are usually many features that share the same reference feature. However, in the current schema, query performance suffers dramatically when this additional join is added.

This is the group table. There is one row for each group. Columns: 

    gid       the group ID (integer)
    gclass    the class of the group (string)
    gname     the name of the group (string)

The group table serves multiple purposes. As you might expect, it is used to cluster features that logically belong together, such as the multiple exons of the same transcript. It is also used to assign a name and class to a singleton feature. Finally, the group table is used to identify the target of a similarity hit. This is consistent with the way in which the group field is used in the GFF version 2 format.

The fgroup.gid field joins with the fdata.gid field.

Examples:

  sql> select * from fgroup where gname='sjj_2L52.1';
  +-------+-------------+------------+
  | gid   | gclass      | gname      |
  +-------+-------------+------------+
  | 69736 | PCR_product | sjj_2L52.1 |
  +-------+-------------+------------+
  1 row in set (0.70 sec)
  sql> select fref,fstart,fstop from fdata,fgroup 
            where gclass='PCR_product' and gname = 'sjj_2L52.1' 
                  and fdata.gid=fgroup.gid;
  +---------------+--------+-------+
  | fref          | fstart | fstop |
  +---------------+--------+-------+
  | CHROMOSOME_II |   1586 |  2355 |
  +---------------+--------+-------+
  1 row in set (0.03 sec)
This table contains the feature types, one per row. Columns are: 

    ftypeid      the feature type ID (integer)
    fmethod      the feature type method name (string)
    fsource      the feature type source name (string)

The ftype.ftypeid field joins with the fdata.ftypeid field. Example:

  sql> select fref,fstart,fstop,fmethod,fsource from fdata,fgroup,ftype 
         where gclass='PCR_product' 
               and gname = 'sjj_2L52.1'
               and fdata.gid=fgroup.gid
               and fdata.ftypeid=ftype.ftypeid;
  +---------------+--------+-------+-------------+-----------+
  | fref          | fstart | fstop | fmethod     | fsource   |
  +---------------+--------+-------+-------------+-----------+
  | CHROMOSOME_II |   1586 |  2355 | PCR_product | GenePairs |
  +---------------+--------+-------+-------------+-----------+
  1 row in set (0.08 sec)
This table holds the raw DNA of the reference sequences. It has three columns: 

    fref          reference sequence name (string)
    foffset       offset of this sequence
    fdna          the DNA sequence (longblob)

To overcome problems loading large blobs, DNA is automatically fragmented into multiple segments when loading, and the position of each segment is stored in foffset. The fragment size is controlled by the -clump_size argument during initialization.

This table holds "attributes", which are tag/value pairs stuffed into the GFF line. The first tag/value pair is treated as the group, and anything else is treated as an attribute (weird, huh?). 

 CHR_I assembly_tag Finished     2032 2036 . + . Note "Right: cTel33B"
 CHR_I assembly_tag Polymorphism 668  668  . + . Note "A->C in cTel33B"

The columns of this table are:

    fid                 feature ID (integer)
    fattribute_id       ID of the attribute (integer)
    fattribute_value    text of the attribute (text)

The fdata.fid column joins with fattribute_to_feature.fid.

This table holds the normalized names of the attributes. Fields are: 

  fattribute_id      ID of the attribute (integer)
  fattribute_name    Name of the attribute (varchar)

Data Loading Methods

In addition to implementing the abstract SQL-generating methods of Bio::DB::GFF::Adaptor::dbi, this module also implements the data loading functionality of Bio::DB::GFF.

new

 Title   : new
 Usage   : $db = Bio::DB::GFF->new(@args)
 Function: create a new adaptor
 Returns : a Bio::DB::GFF object
 Args    : see below
 Status  : Public

The new constructor is identical to the "dbi" adaptor's new() method, except that the prefix "dbi:pg" is added to the database DSN identifier automatically if it is not there already.

  Argument       Description
  --------       -----------
  -dsn           the DBI data source, e.g. 'dbi:Pg:dbname=:ens0040' or "ens0040"
  -user          username for authentication
  -pass          the password for authentication

schema

 Title   : schema
 Usage   : $schema = $db->schema
 Function: return the CREATE script for the schema
 Returns : a list of CREATE statemetns
 Args    : none
 Status  : protected

This method returns a list containing the various CREATE statements needed to initialize the database tables.

setup_load

 Title   : setup_load
 Usage   : $db->setup_load
 Function: called before load_gff_line()
 Returns : void
 Args    : none
 Status  : protected

This method performs schema-specific initialization prior to loading a set of GFF records. It prepares a set of DBI statement handlers to be used in loading the data.

load_gff_line

 Title   : load_gff_line
 Usage   : $db->load_gff_line($fields)
 Function: called to load one parsed line of GFF
 Returns : true if successfully inserted
 Args    : hashref containing GFF fields
 Status  : protected

This method is called once per line of the GFF and passed a series of parsed data items that are stored into the hashref $fields. The keys are:

 ref          reference sequence
 source       annotation source
 method       annotation method
 start        annotation start
 stop         annotation stop
 score        annotation score (may be undef)
 strand       annotation strand (may be undef)
 phase        annotation phase (may be undef)
 group_class  class of annotation's group (may be undef)
 group_name   ID of annotation's group (may be undef)
 target_start start of target of a similarity hit
 target_stop  stop of target of a similarity hit
 attributes   array reference of attributes, each of which is a [tag=>value] array ref

get_table_id

 Title   : get_table_id
 Usage   : $integer = $db->get_table_id($table,@ids)
 Function: get the ID of a group or type
 Returns : an integer ID or undef
 Args    : none
 Status  : private

This internal method is called by load_gff_line to look up the integer ID of an existing feature type or group. The arguments are the name of the table, and two string identifiers. For feature types, the identifiers are the method and source. For groups, the identifiers are group name and class.

This method requires that a statement handler named lookup_$table, have been created previously by setup_load(). It is here to overcome deficiencies in mysql's INSERT syntax.

range_query

 Title   : range_query
 Usage   : $db->range_query($range_type,$refseq,$refclass,$start,$stop,$types,$order_by_group,$attributes,$binsize)
 Function: create statement handle for range/overlap queries
 Returns : a DBI statement handle
 Args    : see below
 Status  : Protected

This method constructs the statement handle for this module's central query: given a range and/or a list of feature types, fetch their GFF records. It overrides a method in dbi.pm so that the overlaps query can write SQL optimized for Postgres. Specifically, instead of writing the bin related section as a set of ORs, each bin piece is place in a separate select and then they are UNIONed together. This subroutine requires several replacements for other subroutines in dbi.pm. In this module, they are named the same as those in dbi.pm but prefixed with "pg_".

The positional arguments are as follows:

  Argument               Description
  $isrange               A flag indicating that this is a range.
                         query.  Otherwise an overlap query is
                         assumed.
  $refseq                The reference sequence name (undef if no range).
  $refclass              The reference sequence class (undef if no range).
  $start                 The start of the range (undef if none).
  $stop                  The stop of the range (undef if none).
  $types                 Array ref containing zero or feature types in the
                         format [method,source].
  $order_by_group        A flag indicating that statement handler should group
                         the features by group id (handy for iterative fetches)
  $attributes            A hash containing select attributes.
  $binsize               A bin size for generating tables of feature density.

search_notes

This PostgreSQL adaptor does not implement the search notes method because it can be very slow (although the code for the method is contained in this method but commented out). There is, however, a PostgreSQL adaptor that does implement it in a more efficient way: Bio::DB::GFF::Adaptor::dbi::pg_fts, which inherits from this adaptor and uses the optional PostgreSQL module TSearch2 for full text indexing. See that adaptor's documentation for more information.

See also Bio::DB::GFF

 Title   : search_notes
 Usage   : @search_results = $db->search_notes("full text search string",$limit)
 Function: Search the notes for a text string, using mysql full-text search
 Returns : array of results
 Args    : full text search string, and an optional row limit
 Status  : public

This is a replacement for the mysql-specific method. Given a search string, it performs a ILIKE search of the notes table and returns an array of results. Each row of the returned array is a arrayref containing the following fields:

  column 1     A Bio::DB::GFF::Featname object, suitable for passing to segment()
  column 2     The text of the note
  column 3     A relevance score.

Note that for large databases this can be very slow and may result in time out or 500-cgi errors. If this is happening on a regular basis, you should look into using Bio::DB::GFF::Adaptor::dbi::pg_fts which implements the TSearch2 full text indexing scheme.

make_meta_set_query

 Title   : make_meta_set_query
 Usage   : $sql = $db->make_meta_set_query
 Function: return SQL fragment for setting a meta parameter
 Returns : SQL fragment
 Args    : none
 Status  : public

By default this does nothing; meta parameters are not stored or retrieved.

make_features_by_name_where_part

 Title   : make_features_by_name_where_part
 Usage   : $db->make_features_by_name_where_part
 Function: Overrides a function in Bio::DB::GFF::Adaptor::dbi to insure
           that searches will be case insensitive. It creates the SQL
           fragment needed to select a feature by its group name & class
 Returns : a SQL fragment and bind arguments
 Args    : see below
 Status  : Protected
2020-01-13 perl v5.30.0