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revision 1.62, Sun Jul 30 05:44:57 2006 UTC revision 1.85, Mon Jul 16 19:59:33 2007 UTC
# Line 7  Line 7 
7      use PageBuilder;      use PageBuilder;
8      use ERDBLoad;      use ERDBLoad;
9      use FIG;      use FIG;
10        use FIGRules;
11      use Sprout;      use Sprout;
12      use Stats;      use Stats;
13      use BasicLocation;      use BasicLocation;
# Line 80  Line 81 
81  Either the name of the file containing the list of trusted subsystems or a reference  Either the name of the file containing the list of trusted subsystems or a reference
82  to a list of subsystem names. If nothing is specified, all NMPDR subsystems will be  to a list of subsystem names. If nothing is specified, all NMPDR subsystems will be
83  considered trusted. (A subsystem is considered NMPDR if it has a file named C<NMPDR>  considered trusted. (A subsystem is considered NMPDR if it has a file named C<NMPDR>
84  in its data directory.) Only subsystem data related to the trusted subsystems is loaded.  in its data directory.) Only subsystem data related to the NMPDR subsystems is loaded.
85    
86  =item options  =item options
87    
# Line 120  Line 121 
121                      # an omitted access code can be defaulted to 1.                      # an omitted access code can be defaulted to 1.
122                      for my $genomeLine (@genomeList) {                      for my $genomeLine (@genomeList) {
123                          my ($genomeID, $accessCode) = split("\t", $genomeLine);                          my ($genomeID, $accessCode) = split("\t", $genomeLine);
124                          if (undef $accessCode) {                          if (! defined($accessCode)) {
125                              $accessCode = 1;                              $accessCode = 1;
126                          }                          }
127                          $genomes{$genomeID} = $accessCode;                          $genomes{$genomeID} = $accessCode;
# Line 138  Line 139 
139          if (! defined $subsysFile || $subsysFile eq '') {          if (! defined $subsysFile || $subsysFile eq '') {
140              # Here we want all the usable subsystems. First we get the whole list.              # Here we want all the usable subsystems. First we get the whole list.
141              my @subs = $fig->all_subsystems();              my @subs = $fig->all_subsystems();
142              # Loop through, checking for usability.              # Loop through, checking for the NMPDR file.
143              for my $sub (@subs) {              for my $sub (@subs) {
144                  if ($fig->usable_subsystem($sub)) {                  if ($fig->nmpdr_subsystem($sub)) {
145                      $subsystems{$sub} = 1;                      $subsystems{$sub} = 1;
146                  }                  }
147              }              }
# Line 163  Line 164 
164                  Confess("Invalid subsystem parameter in SproutLoad constructor.");                  Confess("Invalid subsystem parameter in SproutLoad constructor.");
165              }              }
166          }          }
167            # Go through the subsys hash again, creating the keyword list for each subsystem.
168            for my $subsystem (keys %subsystems) {
169                my $name = $subsystem;
170                $name =~ s/_/ /g;
171                my $classes = $fig->subsystem_classification($subsystem);
172                $name .= " " . join(" ", @{$classes});
173                $subsystems{$subsystem} = $name;
174      }      }
175        }
176        # Get the list of NMPDR-oriented attribute keys.
177        my @propKeys = $fig->get_group_keys("NMPDR");
178      # Get the data directory from the Sprout object.      # Get the data directory from the Sprout object.
179      my ($directory) = $sprout->LoadInfo();      my ($directory) = $sprout->LoadInfo();
180      # Create the Sprout load object.      # Create the Sprout load object.
# Line 175  Line 186 
186                    loadDirectory => $directory,                    loadDirectory => $directory,
187                    erdb => $sprout,                    erdb => $sprout,
188                    loaders => [],                    loaders => [],
189                    options => $options                    options => $options,
190                      propKeys => \@propKeys,
191                   };                   };
192      # Bless and return it.      # Bless and return it.
193      bless $retVal, $class;      bless $retVal, $class;
# Line 195  Line 207 
207      return $self->{options}->{loadOnly};      return $self->{options}->{loadOnly};
208  }  }
209    
 =head3 PrimaryOnly  
   
 C<< my $flag = $spl->PrimaryOnly; >>  
   
 Return TRUE if only the main entity is to be loaded, else FALSE.  
   
 =cut  
   
 sub PrimaryOnly {  
     my ($self) = @_;  
     return $self->{options}->{primaryOnly};  
 }  
210    
211  =head3 LoadGenomeData  =head3 LoadGenomeData
212    
# Line 247  Line 247 
247      my $genomeCount = (keys %{$genomeHash});      my $genomeCount = (keys %{$genomeHash});
248      # Create load objects for each of the tables we're loading.      # Create load objects for each of the tables we're loading.
249      my $loadGenome = $self->_TableLoader('Genome');      my $loadGenome = $self->_TableLoader('Genome');
250      my $loadHasContig = $self->_TableLoader('HasContig', $self->PrimaryOnly);      my $loadHasContig = $self->_TableLoader('HasContig');
251      my $loadContig = $self->_TableLoader('Contig', $self->PrimaryOnly);      my $loadContig = $self->_TableLoader('Contig');
252      my $loadIsMadeUpOf = $self->_TableLoader('IsMadeUpOf', $self->PrimaryOnly);      my $loadIsMadeUpOf = $self->_TableLoader('IsMadeUpOf');
253      my $loadSequence = $self->_TableLoader('Sequence', $self->PrimaryOnly);      my $loadSequence = $self->_TableLoader('Sequence');
254      if ($self->{options}->{loadOnly}) {      if ($self->{options}->{loadOnly}) {
255          Trace("Loading from existing files.") if T(2);          Trace("Loading from existing files.") if T(2);
256      } else {      } else {
# Line 266  Line 266 
266              my $extra = join " ", @extraData;              my $extra = join " ", @extraData;
267              # Get the full taxonomy.              # Get the full taxonomy.
268              my $taxonomy = $fig->taxonomy_of($genomeID);              my $taxonomy = $fig->taxonomy_of($genomeID);
269                # Get the version. If no version is specified, we default to the genome ID by itself.
270                my $version = $fig->genome_version($genomeID);
271                if (! defined($version)) {
272                    $version = $genomeID;
273                }
274                # Get the DNA size.
275                my $dnaSize = $fig->genome_szdna($genomeID);
276                # Open the NMPDR group file for this genome.
277                my $group;
278                if (open(TMP, "<$FIG_Config::organisms/$genomeID/NMPDR") &&
279                    defined($group = <TMP>)) {
280                    # Clean the line ending.
281                    chomp $group;
282                } else {
283                    # No group, so use the default.
284                    $group = $FIG_Config::otherGroup;
285                }
286                close TMP;
287              # Output the genome record.              # Output the genome record.
288              $loadGenome->Put($genomeID, $accessCode, $fig->is_complete($genomeID), $genus,              $loadGenome->Put($genomeID, $accessCode, $fig->is_complete($genomeID),
289                               $species, $extra, $taxonomy);                               $dnaSize, $genus, $group, $species, $extra, $version, $taxonomy);
290              # Now we loop through each of the genome's contigs.              # Now we loop through each of the genome's contigs.
291              my @contigs = $fig->all_contigs($genomeID);              my @contigs = $fig->all_contigs($genomeID);
292              for my $contigID (@contigs) {              for my $contigID (@contigs) {
# Line 306  Line 324 
324      return $retVal;      return $retVal;
325  }  }
326    
 =head3 LoadCouplingData  
   
 C<< my $stats = $spl->LoadCouplingData(); >>  
   
 Load the coupling and evidence data from FIG into Sprout.  
   
 The coupling data specifies which genome features are functionally coupled. The  
 evidence data explains why the coupling is functional.  
   
 The following relations are loaded by this method.  
   
     Coupling  
     IsEvidencedBy  
     PCH  
     ParticipatesInCoupling  
     UsesAsEvidence  
   
 =over 4  
   
 =item RETURNS  
   
 Returns a statistics object for the loads.  
   
 =back  
   
 =cut  
 #: Return Type $%;  
 sub LoadCouplingData {  
     # Get this object instance.  
     my ($self) = @_;  
     # Get the FIG object.  
     my $fig = $self->{fig};  
     # Get the genome hash.  
     my $genomeFilter = $self->{genomes};  
     # Set up an ID counter for the PCHs.  
     my $pchID = 0;  
     # Start the loads.  
     my $loadCoupling = $self->_TableLoader('Coupling');  
     my $loadIsEvidencedBy = $self->_TableLoader('IsEvidencedBy', $self->PrimaryOnly);  
     my $loadPCH = $self->_TableLoader('PCH', $self->PrimaryOnly);  
     my $loadParticipatesInCoupling = $self->_TableLoader('ParticipatesInCoupling', $self->PrimaryOnly);  
     my $loadUsesAsEvidence = $self->_TableLoader('UsesAsEvidence', $self->PrimaryOnly);  
     if ($self->{options}->{loadOnly}) {  
         Trace("Loading from existing files.") if T(2);  
     } else {  
         Trace("Generating coupling data.") if T(2);  
         # Loop through the genomes found.  
         for my $genome (sort keys %{$genomeFilter}) {  
             Trace("Generating coupling data for $genome.") if T(3);  
             $loadCoupling->Add("genomeIn");  
             # Create a hash table for holding coupled pairs. We use this to prevent  
             # duplicates. For example, if A is coupled to B, we don't want to also  
             # assert that B is coupled to A, because we already know it. Fortunately,  
             # all couplings occur within a genome, so we can keep the hash table  
             # size reasonably small.  
             my %dupHash = ();  
             # Get all of the genome's PEGs.  
             my @pegs = $fig->pegs_of($genome);  
             # Loop through the PEGs.  
             for my $peg1 (@pegs) {  
                 $loadCoupling->Add("pegIn");  
                 Trace("Processing PEG $peg1 for $genome.") if T(4);  
                 # Get a list of the coupled PEGs.  
                 my @couplings = $fig->coupled_to($peg1);  
                 # For each coupled PEG, we need to verify that a coupling already  
                 # exists. If not, we have to create one.  
                 for my $coupleData (@couplings) {  
                     my ($peg2, $score) = @{$coupleData};  
                     # Compute the coupling ID.  
                     my $coupleID = $self->{erdb}->CouplingID($peg1, $peg2);  
                     if (! exists $dupHash{$coupleID}) {  
                         $loadCoupling->Add("couplingIn");  
                         # Here we have a new coupling to store in the load files.  
                         Trace("Storing coupling ($coupleID) with score $score.") if T(4);  
                         # Ensure we don't do this again.  
                         $dupHash{$coupleID} = $score;  
                         # Write the coupling record.  
                         $loadCoupling->Put($coupleID, $score);  
                         # Connect it to the coupled PEGs.  
                         $loadParticipatesInCoupling->Put($peg1, $coupleID, 1);  
                         $loadParticipatesInCoupling->Put($peg2, $coupleID, 2);  
                         # Get the evidence for this coupling.  
                         my @evidence = $fig->coupling_evidence($peg1, $peg2);  
                         # Organize the evidence into a hash table.  
                         my %evidenceMap = ();  
                         # Process each evidence item.  
                         for my $evidenceData (@evidence) {  
                             $loadPCH->Add("evidenceIn");  
                             my ($peg3, $peg4, $usage) = @{$evidenceData};  
                             # Only proceed if the evidence is from a Sprout  
                             # genome.  
                             if ($genomeFilter->{$fig->genome_of($peg3)}) {  
                                 $loadUsesAsEvidence->Add("evidenceChosen");  
                                 my $evidenceKey = "$coupleID $peg3 $peg4";  
                                 # We store this evidence in the hash if the usage  
                                 # is nonzero or no prior evidence has been found. This  
                                 # insures that if there is duplicate evidence, we  
                                 # at least keep the meaningful ones. Only evidence in  
                                 # the hash makes it to the output.  
                                 if ($usage || ! exists $evidenceMap{$evidenceKey}) {  
                                     $evidenceMap{$evidenceKey} = $evidenceData;  
                                 }  
                             }  
                         }  
                         for my $evidenceID (keys %evidenceMap) {  
                             # Get the ID for this evidence.  
                             $pchID++;  
                             # Create the evidence record.  
                             my ($peg3, $peg4, $usage) = @{$evidenceMap{$evidenceID}};  
                             $loadPCH->Put($pchID, $usage);  
                             # Connect it to the coupling.  
                             $loadIsEvidencedBy->Put($coupleID, $pchID);  
                             # Connect it to the features.  
                             $loadUsesAsEvidence->Put($pchID, $peg3, 1);  
                             $loadUsesAsEvidence->Put($pchID, $peg4, 2);  
                         }  
                     }  
                 }  
             }  
         }  
     }  
     # All done. Finish the load.  
     my $retVal = $self->_FinishAll();  
     return $retVal;  
 }  
   
327  =head3 LoadFeatureData  =head3 LoadFeatureData
328    
329  C<< my $stats = $spl->LoadFeatureData(); >>  C<< my $stats = $spl->LoadFeatureData(); >>
# Line 444  Line 336 
336    
337      Feature      Feature
338      FeatureAlias      FeatureAlias
339        IsAliasOf
340      FeatureLink      FeatureLink
341      FeatureTranslation      FeatureTranslation
342      FeatureUpstream      FeatureUpstream
343      IsLocatedIn      IsLocatedIn
344      HasFeature      HasFeature
345        HasRoleInSubsystem
346        FeatureEssential
347        FeatureVirulent
348        FeatureIEDB
349        CDD
350        IsPresentOnProteinOf
351    
352  =over 4  =over 4
353    
# Line 463  Line 362 
362  sub LoadFeatureData {  sub LoadFeatureData {
363      # Get this object instance.      # Get this object instance.
364      my ($self) = @_;      my ($self) = @_;
365      # Get the FIG object.      # Get the FIG and Sprout objects.
366      my $fig = $self->{fig};      my $fig = $self->{fig};
367        my $sprout = $self->{sprout};
368      # Get the table of genome IDs.      # Get the table of genome IDs.
369      my $genomeHash = $self->{genomes};      my $genomeHash = $self->{genomes};
370      # Create load objects for each of the tables we're loading.      # Create load objects for each of the tables we're loading.
371      my $loadFeature = $self->_TableLoader('Feature');      my $loadFeature = $self->_TableLoader('Feature');
372      my $loadIsLocatedIn = $self->_TableLoader('IsLocatedIn', $self->PrimaryOnly);      my $loadIsLocatedIn = $self->_TableLoader('IsLocatedIn');
373      my $loadFeatureAlias = $self->_TableLoader('FeatureAlias');      my $loadFeatureAlias = $self->_TableLoader('FeatureAlias');
374        my $loadIsAliasOf = $self->_TableLoader('IsAliasOf');
375      my $loadFeatureLink = $self->_TableLoader('FeatureLink');      my $loadFeatureLink = $self->_TableLoader('FeatureLink');
376      my $loadFeatureTranslation = $self->_TableLoader('FeatureTranslation');      my $loadFeatureTranslation = $self->_TableLoader('FeatureTranslation');
377      my $loadFeatureUpstream = $self->_TableLoader('FeatureUpstream');      my $loadFeatureUpstream = $self->_TableLoader('FeatureUpstream');
378      my $loadHasFeature = $self->_TableLoader('HasFeature');      my $loadHasFeature = $self->_TableLoader('HasFeature');
379        my $loadHasRoleInSubsystem = $self->_TableLoader('HasRoleInSubsystem');
380        my $loadFeatureEssential = $self->_TableLoader('FeatureEssential');
381        my $loadFeatureVirulent = $self->_TableLoader('FeatureVirulent');
382        my $loadFeatureIEDB = $self->_TableLoader('FeatureIEDB');
383        my $loadCDD = $self->_TableLoader('CDD');
384        my $loadIsPresentOnProteinOf = $self->_TableLoader('IsPresentOnProteinOf');
385        # Get the subsystem hash.
386        my $subHash = $self->{subsystems};
387        # Get the property keys.
388        my $propKeys = $self->{propKeys};
389        # Create a hashes to hold CDD and alias values.
390        my %CDD = ();
391        my %alias = ();
392      # Get the maximum sequence size. We need this later for splitting up the      # Get the maximum sequence size. We need this later for splitting up the
393      # locations.      # locations.
394      my $chunkSize = $self->{sprout}->MaxSegment();      my $chunkSize = $self->{sprout}->MaxSegment();
# Line 487  Line 401 
401              Trace("Loading features for genome $genomeID.") if T(3);              Trace("Loading features for genome $genomeID.") if T(3);
402              $loadFeature->Add("genomeIn");              $loadFeature->Add("genomeIn");
403              # Get the feature list for this genome.              # Get the feature list for this genome.
404              my $features = $fig->all_features_detailed($genomeID);              my $features = $fig->all_features_detailed_fast($genomeID);
405              # Sort and count the list.              # Sort and count the list.
406              my @featureTuples = sort { $a->[0] cmp $b->[0] } @{$features};              my @featureTuples = sort { $a->[0] cmp $b->[0] } @{$features};
407              my $count = scalar @featureTuples;              my $count = scalar @featureTuples;
408                my @fids = map { $_->[0] } @featureTuples;
409              Trace("$count features found for genome $genomeID.") if T(3);              Trace("$count features found for genome $genomeID.") if T(3);
410                # Get the attributes for this genome and put them in a hash by feature ID.
411                my $attributes = GetGenomeAttributes($fig, $genomeID, \@fids, $propKeys);
412              # Set up for our duplicate-feature check.              # Set up for our duplicate-feature check.
413              my $oldFeatureID = "";              my $oldFeatureID = "";
414              # Loop through the features.              # Loop through the features.
415              for my $featureTuple (@featureTuples) {              for my $featureTuple (@featureTuples) {
416                  # Split the tuple.                  # Split the tuple.
417                  my ($featureID, $locations, undef, $type) = @{$featureTuple};                  my ($featureID, $locations, undef, $type, $minloc, $maxloc, $assignment, $user, $quality) = @{$featureTuple};
418                  # Check for duplicates.                  # Check for duplicates.
419                  if ($featureID eq $oldFeatureID) {                  if ($featureID eq $oldFeatureID) {
420                      Trace("Duplicate feature $featureID found.") if T(1);                      Trace("Duplicate feature $featureID found.") if T(1);
# Line 505  Line 422 
422                      $oldFeatureID = $featureID;                      $oldFeatureID = $featureID;
423                      # Count this feature.                      # Count this feature.
424                      $loadFeature->Add("featureIn");                      $loadFeature->Add("featureIn");
425                      # Create the feature record.                      # Fix the quality. It is almost always a space, but some odd stuff might sneak through, and the
426                      $loadFeature->Put($featureID, 1, $type);                      # Sprout database requires a single character.
427                      # Link it to the parent genome.                      if (! defined($quality) || $quality eq "") {
428                      $loadHasFeature->Put($genomeID, $featureID, $type);                          $quality = " ";
429                        }
430                        # Begin building the keywords. We start with the genome ID, the
431                        # feature ID, the taxonomy, and the organism name.
432                        my @keywords = ($genomeID, $featureID, $fig->genus_species($genomeID),
433                                        $fig->taxonomy_of($genomeID));
434                      # Create the aliases.                      # Create the aliases.
435                      for my $alias ($fig->feature_aliases($featureID)) {                      for my $alias ($fig->feature_aliases($featureID)) {
436                          $loadFeatureAlias->Put($featureID, $alias);                          #Connect this alias to this feature.
437                      }                          $loadIsAliasOf->Put($alias, $featureID);
438                            push @keywords, $alias;
439                            # If this is a locus tag, also add its natural form as a keyword.
440                            my $naturalName = AliasAnalysis::Type(LocusTag => $alias);
441                            if ($naturalName) {
442                                push @keywords, $naturalName;
443                            }
444                            # If this is the first time for the specified alias, create its
445                            # alias record.
446                            if (! exists $alias{$alias}) {
447                                $loadFeatureAlias->Put($alias);
448                                $alias{$alias} = 1;
449                            }
450                        }
451                        Trace("Assignment for $featureID is: $assignment") if T(4);
452                        # Break the assignment into words and shove it onto the
453                        # keyword list.
454                        push @keywords, split(/\s+/, $assignment);
455                        # Link this feature to the parent genome.
456                        $loadHasFeature->Put($genomeID, $featureID, $type);
457                      # Get the links.                      # Get the links.
458                      my @links = $fig->fid_links($featureID);                      my @links = $fig->fid_links($featureID);
459                      for my $link (@links) {                      for my $link (@links) {
# Line 531  Line 472 
472                              $loadFeatureUpstream->Put($featureID, $upstream);                              $loadFeatureUpstream->Put($featureID, $upstream);
473                          }                          }
474                      }                      }
475                        # Now we need to find the subsystems this feature participates in.
476                        # We also add the subsystems to the keyword list. Before we do that,
477                        # we must convert underscores to spaces and tack on the classifications.
478                        my @subsystems = $fig->peg_to_subsystems($featureID);
479                        for my $subsystem (@subsystems) {
480                            # Only proceed if we like this subsystem.
481                            if (exists $subHash->{$subsystem}) {
482                                # Store the has-role link.
483                                $loadHasRoleInSubsystem->Put($featureID, $subsystem, $genomeID, $type);
484                                # Save the subsystem's keyword data.
485                                my $subKeywords = $subHash->{$subsystem};
486                                push @keywords, split /\s+/, $subKeywords;
487                                # Now we need to get this feature's role in the subsystem.
488                                my $subObject = $fig->get_subsystem($subsystem);
489                                my @roleColumns = $subObject->get_peg_roles($featureID);
490                                my @allRoles = $subObject->get_roles();
491                                for my $col (@roleColumns) {
492                                    my $role = $allRoles[$col];
493                                    push @keywords, split /\s+/, $role;
494                                    push @keywords, $subObject->get_role_abbr($col);
495                                }
496                            }
497                        }
498                        # There are three special attributes computed from property
499                        # data that we build next. If the special attribute is non-empty,
500                        # its name will be added to the keyword list. First, we get all
501                        # the attributes for this feature. They will come back as
502                        # 4-tuples: [peg, name, value, URL]. We use a 3-tuple instead:
503                        # [name, value, value with URL]. (We don't need the PEG, since
504                        # we already know it.)
505                        my @attributes = map { [$_->[1], $_->[2], Tracer::CombineURL($_->[2], $_->[3])] }
506                                             @{$attributes->{$featureID}};
507                        # Now we process each of the special attributes.
508                        if (SpecialAttribute($featureID, \@attributes,
509                                             1, [0,2], '^(essential|potential_essential)$',
510                                             $loadFeatureEssential)) {
511                            push @keywords, 'essential';
512                            $loadFeature->Add('essential');
513                        }
514                        if (SpecialAttribute($featureID, \@attributes,
515                                             0, [2], '^virulen',
516                                             $loadFeatureVirulent)) {
517                            push @keywords, 'virulent';
518                            $loadFeature->Add('virulent');
519                        }
520                        if (SpecialAttribute($featureID, \@attributes,
521                                             0, [0,2], '^iedb_',
522                                             $loadFeatureIEDB)) {
523                            push @keywords, 'iedb';
524                            $loadFeature->Add('iedb');
525                        }
526                        # Now we have some other attributes we need to process. Currently,
527                        # this is CDD and CELLO, but we expect the number to increase.
528                        my %attributeHash = ();
529                        for my $attrRow (@{$attributes->{$featureID}}) {
530                            my (undef, $key, @values) = @{$attrRow};
531                            $key =~ /^([^:]+)::(.+)/;
532                            if (exists $attributeHash{$1}) {
533                                $attributeHash{$1}->{$2} = \@values;
534                            } else {
535                                $attributeHash{$1} = {$2 => \@values};
536                            }
537                        }
538                        my $celloValue = "unknown";
539                        # Pull in the CELLO attribute. There will never be more than one.
540                        # If we have one, it's a feature attribute AND a keyword.
541                        my @celloData = keys %{$attributeHash{CELLO}};
542                        if (@celloData) {
543                            $celloValue = $celloData[0];
544                            push @keywords, $celloValue;
545                        }
546                        # Now we handle CDD. This is a bit more complicated, because
547                        # there are multiple CDDs per protein.
548                        if (exists $attributeHash{CDD}) {
549                            # Get the hash of CDD IDs to scores for this feature. We
550                            # already know it exists because of the above IF.
551                            my $cddHash = $attributeHash{CDD};
552                            my @cddData = sort keys %{$cddHash};
553                            for my $cdd (@cddData) {
554                                # Extract the score for this CDD and decode it.
555                                my ($codeScore) = split(/\s*,\s*/, $cddHash->{$cdd}->[0]);
556                                my $realScore = FIGRules::DecodeScore($codeScore);
557                                # Create the connection.
558                                $loadIsPresentOnProteinOf->Put($cdd, $featureID, $realScore);
559                                # If this CDD does not yet exist, create its record.
560                                if (! exists $CDD{$cdd}) {
561                                    $CDD{$cdd} = 1;
562                                    $loadCDD->Put($cdd);
563                                }
564                            }
565                        }
566                        # Now we need to bust up hyphenated words in the keyword
567                        # list. We keep them separate and put them at the end so
568                        # the original word order is available.
569                        my $keywordString = "";
570                        my $bustedString = "";
571                        for my $keyword (@keywords) {
572                            if (length $keyword >= 3) {
573                                $keywordString .= " $keyword";
574                                if ($keyword =~ /-/) {
575                                    my @words = split /-/, $keyword;
576                                    $bustedString .= join(" ", "", @words);
577                                }
578                            }
579                        }
580                        $keywordString .= $bustedString;
581                        # Get rid of annoying punctuation.
582                        $keywordString =~ s/[();]//g;
583                        # Clean the keyword list.
584                        my $cleanWords = $sprout->CleanKeywords($keywordString);
585                        Trace("Keyword string for $featureID: $cleanWords") if T(4);
586                        # Now we need to process the feature's locations. First, we split them up.
587                        my @locationList = split /\s*,\s*/, $locations;
588                        # Next, we convert them to Sprout location objects.
589                        my @locObjectList = map { BasicLocation->new("$genomeID:$_") } @locationList;
590                      # This part is the roughest. We need to relate the features to contig                      # This part is the roughest. We need to relate the features to contig
591                      # locations, and the locations must be split so that none of them exceed                      # locations, and the locations must be split so that none of them exceed
592                      # the maximum segment size. This simplifies the genes_in_region processing                      # the maximum segment size. This simplifies the genes_in_region processing
593                      # for Sprout.                      # for Sprout. To start, we create the location position indicator.
                     my @locationList = split /\s*,\s*/, $locations;  
                     # Create the location position indicator.  
594                      my $i = 1;                      my $i = 1;
595                      # Loop through the locations.                      # Loop through the locations.
596                      for my $location (@locationList) {                      for my $locObject (@locObjectList) {
597                          # Parse the location.                          # Split this location into a list of chunks.
                         my $locObject = BasicLocation->new("$genomeID:$location");  
                         # Split it into a list of chunks.  
598                          my @locOList = ();                          my @locOList = ();
599                          while (my $peeling = $locObject->Peel($chunkSize)) {                          while (my $peeling = $locObject->Peel($chunkSize)) {
600                              $loadIsLocatedIn->Add("peeling");                              $loadIsLocatedIn->Add("peeling");
# Line 557  Line 609 
609                              $i++;                              $i++;
610                          }                          }
611                      }                      }
612                  }                      # Finally, reassemble the location objects into a list of Sprout location strings.
613              }                      $locations = join(", ", map { $_->String } @locObjectList);
614          }                      # Create the feature record.
615      }                      $loadFeature->Put($featureID, 1, $user, $quality, $celloValue, $type, $assignment, $cleanWords, $locations);
     # Finish the loads.  
     my $retVal = $self->_FinishAll();  
     return $retVal;  
 }  
   
 =head3 LoadBBHData  
   
 C<< my $stats = $spl->LoadBBHData(); >>  
   
 Load the bidirectional best hit data from FIG into Sprout.  
   
 Sprout does not store information on similarities. Instead, it has only the  
 bi-directional best hits. Even so, the BBH table is one of the largest in  
 the database.  
   
 The following relations are loaded by this method.  
   
     IsBidirectionalBestHitOf  
   
 =over 4  
   
 =item RETURNS  
   
 Returns a statistics object for the loads.  
   
 =back  
   
 =cut  
 #: Return Type $%;  
 sub LoadBBHData {  
     # Get this object instance.  
     my ($self) = @_;  
     # Get the FIG object.  
     my $fig = $self->{fig};  
     # Get the table of genome IDs.  
     my $genomeHash = $self->{genomes};  
     # Create load objects for each of the tables we're loading.  
     my $loadIsBidirectionalBestHitOf = $self->_TableLoader('IsBidirectionalBestHitOf');  
     if ($self->{options}->{loadOnly}) {  
         Trace("Loading from existing files.") if T(2);  
     } else {  
         Trace("Generating BBH data.") if T(2);  
         # Now we loop through the genomes, generating the data for each one.  
         for my $genomeID (sort keys %{$genomeHash}) {  
             $loadIsBidirectionalBestHitOf->Add("genomeIn");  
             Trace("Processing features for genome $genomeID.") if T(3);  
             # Get the feature list for this genome.  
             my $features = $fig->all_features_detailed($genomeID);  
             # Loop through the features.  
             for my $featureData (@{$features}) {  
                 # Split the tuple.  
                 my ($featureID, $locations, $aliases, $type) = @{$featureData};  
                 # Get the bi-directional best hits.  
                 my @bbhList = $fig->bbhs($featureID);  
                 for my $bbhEntry (@bbhList) {  
                     # Get the target feature ID and the score.  
                     my ($targetID, $score) = @{$bbhEntry};  
                     # Check the target feature's genome.  
                     my $targetGenomeID = $fig->genome_of($targetID);  
                     # Only proceed if it's one of our genomes.  
                     if ($genomeHash->{$targetGenomeID}) {  
                         $loadIsBidirectionalBestHitOf->Put($featureID, $targetID, $targetGenomeID,  
                                                            $score);  
                     }  
616                  }                  }
617              }              }
618          }          }
# Line 652  Line 640 
640      SubsystemClass      SubsystemClass
641      Role      Role
642      RoleEC      RoleEC
643        IsIdentifiedByEC
644      SSCell      SSCell
645      ContainsFeature      ContainsFeature
646      IsGenomeOf      IsGenomeOf
# Line 693  Line 682 
682      # Get the map list.      # Get the map list.
683      my @maps = $fig->all_maps;      my @maps = $fig->all_maps;
684      # Create load objects for each of the tables we're loading.      # Create load objects for each of the tables we're loading.
685      my $loadDiagram = $self->_TableLoader('Diagram', $self->PrimaryOnly);      my $loadDiagram = $self->_TableLoader('Diagram');
686      my $loadRoleOccursIn = $self->_TableLoader('RoleOccursIn', $self->PrimaryOnly);      my $loadRoleOccursIn = $self->_TableLoader('RoleOccursIn');
687      my $loadSubsystem = $self->_TableLoader('Subsystem');      my $loadSubsystem = $self->_TableLoader('Subsystem');
688      my $loadRole = $self->_TableLoader('Role', $self->PrimaryOnly);      my $loadRole = $self->_TableLoader('Role');
689      my $loadRoleEC = $self->_TableLoader('RoleEC', $self->PrimaryOnly);      my $loadRoleEC = $self->_TableLoader('RoleEC');
690      my $loadCatalyzes = $self->_TableLoader('Catalyzes', $self->PrimaryOnly);      my $loadIsIdentifiedByEC = $self->_TableLoader('IsIdentifiedByEC');
691      my $loadSSCell = $self->_TableLoader('SSCell', $self->PrimaryOnly);      my $loadCatalyzes = $self->_TableLoader('Catalyzes');
692      my $loadContainsFeature = $self->_TableLoader('ContainsFeature', $self->PrimaryOnly);      my $loadSSCell = $self->_TableLoader('SSCell');
693      my $loadIsGenomeOf = $self->_TableLoader('IsGenomeOf', $self->PrimaryOnly);      my $loadContainsFeature = $self->_TableLoader('ContainsFeature');
694      my $loadIsRoleOf = $self->_TableLoader('IsRoleOf', $self->PrimaryOnly);      my $loadIsGenomeOf = $self->_TableLoader('IsGenomeOf');
695      my $loadOccursInSubsystem = $self->_TableLoader('OccursInSubsystem', $self->PrimaryOnly);      my $loadIsRoleOf = $self->_TableLoader('IsRoleOf');
696      my $loadParticipatesIn = $self->_TableLoader('ParticipatesIn', $self->PrimaryOnly);      my $loadOccursInSubsystem = $self->_TableLoader('OccursInSubsystem');
697      my $loadHasSSCell = $self->_TableLoader('HasSSCell', $self->PrimaryOnly);      my $loadParticipatesIn = $self->_TableLoader('ParticipatesIn');
698      my $loadRoleSubset = $self->_TableLoader('RoleSubset', $self->PrimaryOnly);      my $loadHasSSCell = $self->_TableLoader('HasSSCell');
699      my $loadGenomeSubset = $self->_TableLoader('GenomeSubset', $self->PrimaryOnly);      my $loadRoleSubset = $self->_TableLoader('RoleSubset');
700      my $loadConsistsOfRoles = $self->_TableLoader('ConsistsOfRoles', $self->PrimaryOnly);      my $loadGenomeSubset = $self->_TableLoader('GenomeSubset');
701      my $loadConsistsOfGenomes = $self->_TableLoader('ConsistsOfGenomes', $self->PrimaryOnly);      my $loadConsistsOfRoles = $self->_TableLoader('ConsistsOfRoles');
702      my $loadHasRoleSubset = $self->_TableLoader('HasRoleSubset', $self->PrimaryOnly);      my $loadConsistsOfGenomes = $self->_TableLoader('ConsistsOfGenomes');
703      my $loadHasGenomeSubset = $self->_TableLoader('HasGenomeSubset', $self->PrimaryOnly);      my $loadHasRoleSubset = $self->_TableLoader('HasRoleSubset');
704      my $loadSubsystemClass = $self->_TableLoader('SubsystemClass', $self->PrimaryOnly);      my $loadHasGenomeSubset = $self->_TableLoader('HasGenomeSubset');
705        my $loadSubsystemClass = $self->_TableLoader('SubsystemClass');
706      if ($self->{options}->{loadOnly}) {      if ($self->{options}->{loadOnly}) {
707          Trace("Loading from existing files.") if T(2);          Trace("Loading from existing files.") if T(2);
708      } else {      } else {
709          Trace("Generating subsystem data.") if T(2);          Trace("Generating subsystem data.") if T(2);
710          # This hash will contain the role for each EC. When we're done, this          # This hash will contain the roles for each EC. When we're done, this
711          # information will be used to generate the Catalyzes table.          # information will be used to generate the Catalyzes table.
712          my %ecToRoles = ();          my %ecToRoles = ();
713          # Loop through the subsystems. Our first task will be to create the          # Loop through the subsystems. Our first task will be to create the
# Line 731  Line 721 
721              # Get the subsystem object.              # Get the subsystem object.
722              my $sub = $fig->get_subsystem($subsysID);              my $sub = $fig->get_subsystem($subsysID);
723              # Only proceed if the subsystem has a spreadsheet.              # Only proceed if the subsystem has a spreadsheet.
724              if (! $sub->{empty_ss}) {              if (defined($sub) && ! $sub->{empty_ss}) {
725                  Trace("Creating subsystem $subsysID.") if T(3);                  Trace("Creating subsystem $subsysID.") if T(3);
726                  $loadSubsystem->Add("subsystemIn");                  $loadSubsystem->Add("subsystemIn");
727                  # Create the subsystem record.                  # Create the subsystem record.
728                  my $curator = $sub->get_curator();                  my $curator = $sub->get_curator();
729                  my $notes = $sub->get_notes();                  my $notes = $sub->get_notes();
730                  $loadSubsystem->Put($subsysID, $curator, $notes);                  $loadSubsystem->Put($subsysID, $curator, $notes);
731                  my $class = $fig->subsystem_classification($subsysID);                  # Now for the classification string. This comes back as a list
732                  if ($class) {                  # reference and we convert it to a space-delimited string.
733                      $loadSubsystemClass->Put($subsysID, $class);                  my $classList = $fig->subsystem_classification($subsysID);
734                  }                  my $classString = join($FIG_Config::splitter, grep { $_ } @$classList);
735                    $loadSubsystemClass->Put($subsysID, $classString);
736                  # Connect it to its roles. Each role is a column in the subsystem spreadsheet.                  # Connect it to its roles. Each role is a column in the subsystem spreadsheet.
737                  for (my $col = 0; defined($roleID = $sub->get_role($col)); $col++) {                  for (my $col = 0; defined($roleID = $sub->get_role($col)); $col++) {
738                        # Get the role's abbreviation.
739                        my $abbr = $sub->get_role_abbr($col);
740                      # Connect to this role.                      # Connect to this role.
741                      $loadOccursInSubsystem->Add("roleIn");                      $loadOccursInSubsystem->Add("roleIn");
742                      $loadOccursInSubsystem->Put($roleID, $subsysID, $col);                      $loadOccursInSubsystem->Put($roleID, $subsysID, $abbr, $col);
743                      # If it's a new role, add it to the role table.                      # If it's a new role, add it to the role table.
744                      if (! exists $roleData{$roleID}) {                      if (! exists $roleData{$roleID}) {
745                          # Get the role's abbreviation.                          # Get the role's abbreviation.
                         my $abbr = $sub->get_role_abbr($col);  
746                          # Add the role.                          # Add the role.
747                          $loadRole->Put($roleID, $abbr);                          $loadRole->Put($roleID);
748                          $roleData{$roleID} = 1;                          $roleData{$roleID} = 1;
749                          # Check for an EC number.                          # Check for an EC number.
750                          if ($roleID =~ /\(EC ([^.]+\.[^.]+\.[^.]+\.[^)]+)\)\s*$/) {                          if ($roleID =~ /\(EC (\d+\.\d+\.\d+\.\d+)\s*\)\s*$/) {
751                              my $ec = $1;                              my $ec = $1;
752                              $loadRoleEC->Put($roleID, $ec);                              $loadIsIdentifiedByEC->Put($roleID, $ec);
753                              $ecToRoles{$ec} = $roleID;                              # Check to see if this is our first encounter with this EC.
754                                if (exists $ecToRoles{$ec}) {
755                                    # No, so just add this role to the EC list.
756                                    push @{$ecToRoles{$ec}}, $roleID;
757                                } else {
758                                    # Output this EC.
759                                    $loadRoleEC->Put($ec);
760                                    # Create its role list.
761                                    $ecToRoles{$ec} = [$roleID];
762                                }
763                          }                          }
764                      }                      }
765                  }                  }
# Line 883  Line 884 
884          my @reactions = $fig->all_reactions();          my @reactions = $fig->all_reactions();
885          for my $reactionID (@reactions) {          for my $reactionID (@reactions) {
886              # Get this reaction's list of roles. The results will be EC numbers.              # Get this reaction's list of roles. The results will be EC numbers.
887              my @roles = $fig->catalyzed_by($reactionID);              my @ecs = $fig->catalyzed_by($reactionID);
888              # Loop through the roles, creating catalyzation records.              # Loop through the roles, creating catalyzation records.
889              for my $thisRole (@roles) {              for my $thisEC (@ecs) {
890                  if (exists $ecToRoles{$thisRole}) {                  if (exists $ecToRoles{$thisEC}) {
891                      $loadCatalyzes->Put($ecToRoles{$thisRole}, $reactionID);                      for my $thisRole (@{$ecToRoles{$thisEC}}) {
892                            $loadCatalyzes->Put($thisRole, $reactionID);
893                        }
894                  }                  }
895              }              }
896          }          }
# Line 935  Line 938 
938      my $genomeHash = $self->{genomes};      my $genomeHash = $self->{genomes};
939      # Create load objects for each of the tables we're loading.      # Create load objects for each of the tables we're loading.
940      my $loadProperty = $self->_TableLoader('Property');      my $loadProperty = $self->_TableLoader('Property');
941      my $loadHasProperty = $self->_TableLoader('HasProperty', $self->PrimaryOnly);      my $loadHasProperty = $self->_TableLoader('HasProperty');
942      if ($self->{options}->{loadOnly}) {      if ($self->{options}->{loadOnly}) {
943          Trace("Loading from existing files.") if T(2);          Trace("Loading from existing files.") if T(2);
944      } else {      } else {
# Line 943  Line 946 
946          # Create a hash for storing property IDs.          # Create a hash for storing property IDs.
947          my %propertyKeys = ();          my %propertyKeys = ();
948          my $nextID = 1;          my $nextID = 1;
949            # Get the attributes we intend to store in the property table.
950            my $propKeys = $self->{propKeys};
951          # Loop through the genomes.          # Loop through the genomes.
952          for my $genomeID (keys %{$genomeHash}) {          for my $genomeID (sort keys %{$genomeHash}) {
953              $loadProperty->Add("genomeIn");              $loadProperty->Add("genomeIn");
954              Trace("Generating properties for $genomeID.") if T(3);              Trace("Generating properties for $genomeID.") if T(3);
955              # Get the genome's features. The feature ID is the first field in the              # Initialize a counter.
             # tuples returned by "all_features_detailed". We use "all_features_detailed"  
             # rather than "all_features" because we want all features regardless of type.  
             my @features = map { $_->[0] } @{$fig->all_features_detailed($genomeID)};  
             my $featureCount = 0;  
956              my $propertyCount = 0;              my $propertyCount = 0;
957              # Loop through the features, creating HasProperty records.              # Get the properties for this genome's features.
958              for my $fid (@features) {              my @attributes = $fig->get_attributes("fig|$genomeID%", $propKeys);
959                  # Get all attributes for this feature. We do this one feature at a time              Trace("Property list built for $genomeID.") if T(3);
960                  # to insure we do not get any genome attributes.              # Loop through the results, creating HasProperty records.
961                  my @attributeList = $fig->get_attributes($fid, '', '', '');              for my $attributeData (@attributes) {
962                  if (scalar @attributeList) {                  # Pull apart the attribute tuple.
963                      $featureCount++;                  my ($fid, $key, $value, $url) = @{$attributeData};
                 }  
                 # Loop through the attributes.  
                 for my $tuple (@attributeList) {  
                     $propertyCount++;  
                     # Get this attribute value's data. Note that we throw away the FID,  
                     # since it will always be the same as the value if "$fid".  
                     my (undef, $key, $value, $url) = @{$tuple};  
964                      # Concatenate the key and value and check the "propertyKeys" hash to                      # Concatenate the key and value and check the "propertyKeys" hash to
965                      # see if we already have an ID for it. We use a tab for the separator                      # see if we already have an ID for it. We use a tab for the separator
966                      # character.                      # character.
# Line 984  Line 978 
978                      # Create the HasProperty entry for this feature/property association.                      # Create the HasProperty entry for this feature/property association.
979                      $loadHasProperty->Put($fid, $propertyID, $url);                      $loadHasProperty->Put($fid, $propertyID, $url);
980                  }                  }
             }  
981              # Update the statistics.              # Update the statistics.
982              Trace("$propertyCount attributes processed for $featureCount features.") if T(3);              Trace("$propertyCount attributes processed.") if T(3);
             $loadHasProperty->Add("featuresIn", $featureCount);  
983              $loadHasProperty->Add("propertiesIn", $propertyCount);              $loadHasProperty->Add("propertiesIn", $propertyCount);
984          }          }
985      }      }
# Line 1032  Line 1024 
1024      my $genomeHash = $self->{genomes};      my $genomeHash = $self->{genomes};
1025      # Create load objects for each of the tables we're loading.      # Create load objects for each of the tables we're loading.
1026      my $loadAnnotation = $self->_TableLoader('Annotation');      my $loadAnnotation = $self->_TableLoader('Annotation');
1027      my $loadIsTargetOfAnnotation = $self->_TableLoader('IsTargetOfAnnotation', $self->PrimaryOnly);      my $loadIsTargetOfAnnotation = $self->_TableLoader('IsTargetOfAnnotation');
1028      my $loadSproutUser = $self->_TableLoader('SproutUser', $self->PrimaryOnly);      my $loadSproutUser = $self->_TableLoader('SproutUser');
1029      my $loadUserAccess = $self->_TableLoader('UserAccess', $self->PrimaryOnly);      my $loadUserAccess = $self->_TableLoader('UserAccess');
1030      my $loadMadeAnnotation = $self->_TableLoader('MadeAnnotation', $self->PrimaryOnly);      my $loadMadeAnnotation = $self->_TableLoader('MadeAnnotation');
1031      if ($self->{options}->{loadOnly}) {      if ($self->{options}->{loadOnly}) {
1032          Trace("Loading from existing files.") if T(2);          Trace("Loading from existing files.") if T(2);
1033      } else {      } else {
# Line 1139  Line 1131 
1131      # Get the genome hash.      # Get the genome hash.
1132      my $genomeHash = $self->{genomes};      my $genomeHash = $self->{genomes};
1133      # Create load objects for each of the tables we're loading.      # Create load objects for each of the tables we're loading.
1134      my $loadComesFrom = $self->_TableLoader('ComesFrom', $self->PrimaryOnly);      my $loadComesFrom = $self->_TableLoader('ComesFrom');
1135      my $loadSource = $self->_TableLoader('Source');      my $loadSource = $self->_TableLoader('Source');
1136      my $loadSourceURL = $self->_TableLoader('SourceURL');      my $loadSourceURL = $self->_TableLoader('SourceURL');
1137      if ($self->{options}->{loadOnly}) {      if ($self->{options}->{loadOnly}) {
# Line 1276  Line 1268 
1268      Compound      Compound
1269      CompoundName      CompoundName
1270      CompoundCAS      CompoundCAS
1271        IsIdentifiedByCAS
1272        HasCompoundName
1273      IsAComponentOf      IsAComponentOf
1274    
1275  This method proceeds reaction by reaction rather than genome by genome.  This method proceeds reaction by reaction rather than genome by genome.
# Line 1297  Line 1291 
1291      my $fig = $self->{fig};      my $fig = $self->{fig};
1292      # Create load objects for each of the tables we're loading.      # Create load objects for each of the tables we're loading.
1293      my $loadReaction = $self->_TableLoader('Reaction');      my $loadReaction = $self->_TableLoader('Reaction');
1294      my $loadReactionURL = $self->_TableLoader('ReactionURL', $self->PrimaryOnly);      my $loadReactionURL = $self->_TableLoader('ReactionURL');
1295      my $loadCompound = $self->_TableLoader('Compound', $self->PrimaryOnly);      my $loadCompound = $self->_TableLoader('Compound');
1296      my $loadCompoundName = $self->_TableLoader('CompoundName', $self->PrimaryOnly);      my $loadCompoundName = $self->_TableLoader('CompoundName');
1297      my $loadCompoundCAS = $self->_TableLoader('CompoundCAS', $self->PrimaryOnly);      my $loadCompoundCAS = $self->_TableLoader('CompoundCAS');
1298      my $loadIsAComponentOf = $self->_TableLoader('IsAComponentOf', $self->PrimaryOnly);      my $loadIsAComponentOf = $self->_TableLoader('IsAComponentOf');
1299        my $loadIsIdentifiedByCAS = $self->_TableLoader('IsIdentifiedByCAS');
1300        my $loadHasCompoundName = $self->_TableLoader('HasCompoundName');
1301      if ($self->{options}->{loadOnly}) {      if ($self->{options}->{loadOnly}) {
1302          Trace("Loading from existing files.") if T(2);          Trace("Loading from existing files.") if T(2);
1303      } else {      } else {
1304          Trace("Generating annotation data.") if T(2);          Trace("Generating reaction data.") if T(2);
1305            # We need some hashes to prevent duplicates.
1306            my %compoundNames = ();
1307            my %compoundCASes = ();
1308          # First we create the compounds.          # First we create the compounds.
1309          my @compounds = $fig->all_compounds();          my @compounds = $fig->all_compounds();
1310          for my $cid (@compounds) {          for my $cid (@compounds) {
# Line 1314  Line 1313 
1313              # Each name will be given a priority number, starting with 1.              # Each name will be given a priority number, starting with 1.
1314              my $prio = 1;              my $prio = 1;
1315              for my $name (@names) {              for my $name (@names) {
1316                  $loadCompoundName->Put($cid, $name, $prio++);                  if (! exists $compoundNames{$name}) {
1317                        $loadCompoundName->Put($name);
1318                        $compoundNames{$name} = 1;
1319                    }
1320                    $loadHasCompoundName->Put($cid, $name, $prio++);
1321              }              }
1322              # Create the main compound record. Note that the first name              # Create the main compound record. Note that the first name
1323              # becomes the label.              # becomes the label.
# Line 1323  Line 1326 
1326              # Check for a CAS ID.              # Check for a CAS ID.
1327              my $cas = $fig->cas($cid);              my $cas = $fig->cas($cid);
1328              if ($cas) {              if ($cas) {
1329                  $loadCompoundCAS->Put($cid, $cas);                  $loadIsIdentifiedByCAS->Put($cid, $cas);
1330                    if (! exists $compoundCASes{$cas}) {
1331                        $loadCompoundCAS->Put($cas);
1332                        $compoundCASes{$cas} = 1;
1333                    }
1334              }              }
1335          }          }
1336          # All the compounds are set up, so we need to loop through the reactions next. First,          # All the compounds are set up, so we need to loop through the reactions next. First,
# Line 1360  Line 1367 
1367      return $retVal;      return $retVal;
1368  }  }
1369    
 =head3 LoadGroupData  
   
 C<< my $stats = $spl->LoadGroupData(); >>  
   
 Load the genome Groups into Sprout.  
   
 The following relations are loaded by this method.  
   
     GenomeGroups  
   
 There is no direct support for genome groups in FIG, so we access the SEED  
 files directly.  
   
 =over 4  
   
 =item RETURNS  
   
 Returns a statistics object for the loads.  
   
 =back  
   
 =cut  
 #: Return Type $%;  
 sub LoadGroupData {  
     # Get this object instance.  
     my ($self) = @_;  
     # Get the FIG object.  
     my $fig = $self->{fig};  
     # Get the genome hash.  
     my $genomeHash = $self->{genomes};  
     # Create a load object for the table we're loading.  
     my $loadGenomeGroups = $self->_TableLoader('GenomeGroups');  
     if ($self->{options}->{loadOnly}) {  
         Trace("Loading from existing files.") if T(2);  
     } else {  
         Trace("Generating group data.") if T(2);  
         # Loop through the genomes.  
         my $line;  
         for my $genomeID (keys %{$genomeHash}) {  
             Trace("Processing $genomeID.") if T(3);  
             # Open the NMPDR group file for this genome.  
             if (open(TMP, "<$FIG_Config::organisms/$genomeID/NMPDR") &&  
                 defined($line = <TMP>)) {  
                 # Clean the line ending.  
                 chomp $line;  
                 # Add the group to the table. Note that there can only be one group  
                 # per genome.  
                 $loadGenomeGroups->Put($genomeID, $line);  
             }  
             close TMP;  
         }  
     }  
     # Finish the load.  
     my $retVal = $self->_FinishAll();  
     return $retVal;  
 }  
   
1370  =head3 LoadSynonymData  =head3 LoadSynonymData
1371    
1372  C<< my $stats = $spl->LoadSynonymData(); >>  C<< my $stats = $spl->LoadSynonymData(); >>
# Line 1458  Line 1408 
1408          Trace("Generating synonym group data.") if T(2);          Trace("Generating synonym group data.") if T(2);
1409          # Get the database handle.          # Get the database handle.
1410          my $dbh = $fig->db_handle();          my $dbh = $fig->db_handle();
1411          # Ask for the synonyms.          # Ask for the synonyms. Note that "maps_to" is a group name, and "syn_id" is a PEG ID or alias.
1412          my $sth = $dbh->prepare_command("SELECT maps_to, syn_id FROM peg_synonyms ORDER BY maps_to");          my $sth = $dbh->prepare_command("SELECT maps_to, syn_id FROM peg_synonyms ORDER BY maps_to");
1413          my $result = $sth->execute();          my $result = $sth->execute();
1414          if (! defined($result)) {          if (! defined($result)) {
# Line 1470  Line 1420 
1420              my $featureCount = 0;              my $featureCount = 0;
1421              # Loop through the synonym/peg pairs.              # Loop through the synonym/peg pairs.
1422              while (my @row = $sth->fetchrow()) {              while (my @row = $sth->fetchrow()) {
1423                  # Get the synonym ID and feature ID.                  # Get the synonym group ID and feature ID.
1424                  my ($syn_id, $peg) = @row;                  my ($syn_id, $peg) = @row;
1425                  # Insure it's for one of our genomes.                  # Insure it's for one of our genomes.
1426                  my $genomeID = FIG::genome_of($peg);                  my $genomeID = FIG::genome_of($peg);
# Line 1506  Line 1456 
1456  The following relations are loaded by this method.  The following relations are loaded by this method.
1457    
1458      Family      Family
1459      ContainsFeature      IsFamilyForFeature
1460    
1461  The source information for these relations is taken from the C<families_for_protein>,  The source information for these relations is taken from the C<families_for_protein>,
1462  C<family_function>, and C<sz_family> methods of the B<FIG> object.  C<family_function>, and C<sz_family> methods of the B<FIG> object.
# Line 1530  Line 1480 
1480      my $genomeHash = $self->{genomes};      my $genomeHash = $self->{genomes};
1481      # Create load objects for the tables we're loading.      # Create load objects for the tables we're loading.
1482      my $loadFamily = $self->_TableLoader('Family');      my $loadFamily = $self->_TableLoader('Family');
1483      my $loadContainsFeature = $self->_TableLoader('ContainsFeature');      my $loadIsFamilyForFeature = $self->_TableLoader('IsFamilyForFeature');
1484      if ($self->{options}->{loadOnly}) {      if ($self->{options}->{loadOnly}) {
1485          Trace("Loading from existing files.") if T(2);          Trace("Loading from existing files.") if T(2);
1486      } else {      } else {
# Line 1542  Line 1492 
1492              Trace("Processing features for $genomeID.") if T(2);              Trace("Processing features for $genomeID.") if T(2);
1493              # Loop through this genome's PEGs.              # Loop through this genome's PEGs.
1494              for my $fid ($fig->all_features($genomeID, "peg")) {              for my $fid ($fig->all_features($genomeID, "peg")) {
1495                  $loadContainsFeature->Add("features", 1);                  $loadIsFamilyForFeature->Add("features", 1);
1496                  # Get this feature's families.                  # Get this feature's families.
1497                  my @families = $fig->families_for_protein($fid);                  my @families = $fig->families_for_protein($fid);
1498                  # Loop through the families, connecting them to the feature.                  # Loop through the families, connecting them to the feature.
1499                  for my $family (@families) {                  for my $family (@families) {
1500                      $loadContainsFeature->Put($family, $fid);                      $loadIsFamilyForFeature->Put($family, $fid);
1501                      # If this is a new family, create a record for it.                      # If this is a new family, create a record for it.
1502                      if (! exists $familyHash{$family}) {                      if (! exists $familyHash{$family}) {
1503                          $familyHash{$family} = 1;                          $familyHash{$family} = 1;
# Line 1565  Line 1515 
1515      return $retVal;      return $retVal;
1516  }  }
1517    
1518    =head3 LoadDrugData
1519    
1520    C<< my $stats = $spl->LoadDrugData(); >>
1521    
1522    Load the drug target data into Sprout.
1523    
1524    The following relations are loaded by this method.
1525    
1526        PDB
1527        DocksWith
1528        IsProteinForFeature
1529        Ligand
1530    
1531    The source information for these relations is taken from attributes. The
1532    C<PDB> attribute links a PDB to a feature, and is used to build B<IsProteinForFeature>.
1533    The C<zinc_name> attribute describes the ligands. The C<docking_results>
1534    attribute contains the information for the B<DocksWith> relationship. It is
1535    expected that additional attributes and tables will be added in the future.
1536    
1537    =over 4
1538    
1539    =item RETURNS
1540    
1541    Returns a statistics object for the loads.
1542    
1543    =back
1544    
1545    =cut
1546    #: Return Type $%;
1547    sub LoadDrugData {
1548        # Get this object instance.
1549        my ($self) = @_;
1550        # Get the FIG object.
1551        my $fig = $self->{fig};
1552        # Get the genome hash.
1553        my $genomeHash = $self->{genomes};
1554        # Create load objects for the tables we're loading.
1555        my $loadPDB = $self->_TableLoader('PDB');
1556        my $loadLigand = $self->_TableLoader('Ligand');
1557        my $loadIsProteinForFeature = $self->_TableLoader('IsProteinForFeature');
1558        my $loadDocksWith = $self->_TableLoader('DocksWith');
1559        if ($self->{options}->{loadOnly}) {
1560            Trace("Loading from existing files.") if T(2);
1561        } else {
1562            Trace("Generating drug target data.") if T(2);
1563            # First comes the "DocksWith" relationship. This will give us a list of PDBs.
1564            # We can also encounter PDBs when we process "IsProteinForFeature". To manage
1565            # this process, PDB information is collected in a hash table and then
1566            # unspooled after both relationships are created.
1567            my %pdbHash = ();
1568            Trace("Generating docking data.") if T(2);
1569            # Get all the docking data. This may cause problems if there are too many PDBs,
1570            # at which point we'll need another algorithm. The indicator that this is
1571            # happening will be a timeout error in the next statement.
1572            my @dockData = $fig->query_attributes('$key = ? AND $value < ?',
1573                                                  ['docking_results', $FIG_Config::dockLimit]);
1574            Trace(scalar(@dockData) . " rows of docking data found.") if T(3);
1575            for my $dockData (@dockData) {
1576                # Get the docking data components.
1577                my ($pdbID, $docking_key, @valueData) = @{$dockData};
1578                # Fix the PDB ID. It's supposed to be lower-case, but this does not always happen.
1579                $pdbID = lc $pdbID;
1580                # Strip off the object type.
1581                $pdbID =~ s/pdb://;
1582                # Extract the ZINC ID from the docking key. Note that there are two possible
1583                # formats.
1584                my (undef, $zinc_id) = $docking_key =~ /^docking_results::(ZINC)?(\d+)$/;
1585                if (! $zinc_id) {
1586                    Trace("Invalid docking result key $docking_key for $pdbID.") if T(0);
1587                    $loadDocksWith->Add("errors");
1588                } else {
1589                    # Get the pieces of the value and parse the energy.
1590                    # Note that we don't care about the rank, since
1591                    # we can sort on the energy level itself in our database.
1592                    my ($energy, $tool, $type) = @valueData;
1593                    my ($rank, $total, $vanderwaals, $electrostatic) = split /\s*;\s*/, $energy;
1594                    # Ignore predicted results.
1595                    if ($type ne "Predicted") {
1596                        # Count this docking result.
1597                        if (! exists $pdbHash{$pdbID}) {
1598                            $pdbHash{$pdbID} = 1;
1599                        } else {
1600                            $pdbHash{$pdbID}++;
1601                        }
1602                        # Write the result to the output.
1603                        $loadDocksWith->Put($pdbID, $zinc_id, $electrostatic, $type, $tool,
1604                                            $total, $vanderwaals);
1605                    }
1606                }
1607            }
1608            Trace("Connecting features.") if T(2);
1609            # Loop through the genomes.
1610            for my $genome (sort keys %{$genomeHash}) {
1611                Trace("Generating PDBs for $genome.") if T(3);
1612                # Get all of the PDBs that BLAST against this genome's features.
1613                my @attributeData = $fig->get_attributes("fig|$genome%", 'PDB::%');
1614                for my $pdbData (@attributeData) {
1615                    # The PDB ID is coded as a subkey.
1616                    if ($pdbData->[1] !~ /PDB::(.+)/i) {
1617                        Trace("Invalid PDB ID \"$pdbData->[1]\" in attribute table.") if T(0);
1618                        $loadPDB->Add("errors");
1619                    } else {
1620                        my $pdbID = $1;
1621                        # Insure the PDB is in the hash.
1622                        if (! exists $pdbHash{$pdbID}) {
1623                            $pdbHash{$pdbID} = 0;
1624                        }
1625                        # The score and locations are coded in the attribute value.
1626                        if ($pdbData->[2] !~ /^([^;]+)(.*)$/) {
1627                            Trace("Invalid PDB data for $pdbID and feature $pdbData->[0].") if T(0);
1628                            $loadIsProteinForFeature->Add("errors");
1629                        } else {
1630                            my ($score, $locData) = ($1,$2);
1631                            # The location data may not be present, so we have to start with some
1632                            # defaults and then check.
1633                            my ($start, $end) = (1, 0);
1634                            if ($locData) {
1635                                $locData =~ /(\d+)-(\d+)/;
1636                                $start = $1;
1637                                $end = $2;
1638                            }
1639                            # If we still don't have the end location, compute it from
1640                            # the feature length.
1641                            if (! $end) {
1642                                # Most features have one location, but we do a list iteration
1643                                # just in case.
1644                                my @locations = $fig->feature_location($pdbData->[0]);
1645                                $end = 0;
1646                                for my $loc (@locations) {
1647                                    my $locObject = BasicLocation->new($loc);
1648                                    $end += $locObject->Length;
1649                                }
1650                            }
1651                            # Decode the score.
1652                            my $realScore = FIGRules::DecodeScore($score);
1653                            # Connect the PDB to the feature.
1654                            $loadIsProteinForFeature->Put($pdbData->[0], $pdbID, $start, $realScore, $end);
1655                        }
1656                    }
1657                }
1658            }
1659            # We've got all our PDBs now, so we unspool them from the hash.
1660            Trace("Generating PDBs. " . scalar(keys %pdbHash) . " found.") if T(2);
1661            my $count = 0;
1662            for my $pdbID (sort keys %pdbHash) {
1663                $loadPDB->Put($pdbID, $pdbHash{$pdbID});
1664                $count++;
1665                Trace("$count PDBs processed.") if T(3) && ($count % 500 == 0);
1666            }
1667            # Finally we create the ligand table. This information can be found in the
1668            # zinc_name attribute.
1669            Trace("Loading ligands.") if T(2);
1670            # The ligand list is huge, so we have to get it in pieces. We also have to check for duplicates.
1671            my $last_zinc_id = "";
1672            my $zinc_id = "";
1673            my $done = 0;
1674            while (! $done) {
1675                # Get the next 10000 ligands. We insist that the object ID is greater than
1676                # the last ID we processed.
1677                Trace("Loading batch starting with ZINC:$zinc_id.") if T(3);
1678                my @attributeData = $fig->query_attributes('$object > ? AND $key = ? ORDER BY $object LIMIT 10000',
1679                                                           ["ZINC:$zinc_id", "zinc_name"]);
1680                Trace(scalar(@attributeData) . " attribute rows returned.") if T(3);
1681                if (! @attributeData) {
1682                    # Here there are no attributes left, so we quit the loop.
1683                    $done = 1;
1684                } else {
1685                    # Process the attribute data we've received.
1686                    for my $zinc_data (@attributeData) {
1687                        # The ZINC ID is found in the first return column, prefixed with the word ZINC.
1688                        if ($zinc_data->[0] =~ /^ZINC:(\d+)$/) {
1689                            $zinc_id = $1;
1690                            # Check for a duplicate.
1691                            if ($zinc_id eq $last_zinc_id) {
1692                                $loadLigand->Add("duplicate");
1693                            } else {
1694                                # Here it's safe to output the ligand. The ligand name is the attribute value
1695                                # (third column in the row).
1696                                $loadLigand->Put($zinc_id, $zinc_data->[2]);
1697                                # Insure we don't try to add this ID again.
1698                                $last_zinc_id = $zinc_id;
1699                            }
1700                        } else {
1701                            Trace("Invalid zinc ID \"$zinc_data->[0]\" in attribute table.") if T(0);
1702                            $loadLigand->Add("errors");
1703                        }
1704                    }
1705                }
1706            }
1707            Trace("Ligands loaded.") if T(2);
1708        }
1709        # Finish the load.
1710        my $retVal = $self->_FinishAll();
1711        return $retVal;
1712    }
1713    
1714    
1715  =head2 Internal Utility Methods  =head2 Internal Utility Methods
1716    
1717    =head3 SpecialAttribute
1718    
1719    C<< my $count = SproutLoad::SpecialAttribute($id, \@attributes, $idxMatch, \@idxValues, $pattern, $loader); >>
1720    
1721    Look for special attributes of a given type. A special attribute is found by comparing one of
1722    the columns of the incoming attribute list to a search pattern. If a match is found, then
1723    a set of columns is put into an output table connected to the specified ID.
1724    
1725    For example, when processing features, the attribute list we look at has three columns: attribute
1726    name, attribute value, and attribute value HTML. The IEDB attribute exists if the attribute name
1727    begins with C<iedb_>. The call signature is therefore
1728    
1729        my $found = SpecialAttribute($fid, \@attributeList, 0, [0,2], '^iedb_', $loadFeatureIEDB);
1730    
1731    The pattern is matched against column 0, and if we have a match, then column 2's value is put
1732    to the output along with the specified feature ID.
1733    
1734    =over 4
1735    
1736    =item id
1737    
1738    ID of the object whose special attributes are being loaded. This forms the first column of the
1739    output.
1740    
1741    =item attributes
1742    
1743    Reference to a list of tuples.
1744    
1745    =item idxMatch
1746    
1747    Index in each tuple of the column to be matched against the pattern. If the match is
1748    successful, an output record will be generated.
1749    
1750    =item idxValues
1751    
1752    Reference to a list containing the indexes in each tuple of the columns to be put as
1753    the second column of the output.
1754    
1755    =item pattern
1756    
1757    Pattern to be matched against the specified column. The match will be case-insensitive.
1758    
1759    =item loader
1760    
1761    An object to which each output record will be put. Usually this is an B<ERDBLoad> object,
1762    but technically it could be anything with a C<Put> method.
1763    
1764    =item RETURN
1765    
1766    Returns a count of the matches found.
1767    
1768    =item
1769    
1770    =back
1771    
1772    =cut
1773    
1774    sub SpecialAttribute {
1775        # Get the parameters.
1776        my ($id, $attributes, $idxMatch, $idxValues, $pattern, $loader) = @_;
1777        # Declare the return variable.
1778        my $retVal = 0;
1779        # Loop through the attribute rows.
1780        for my $row (@{$attributes}) {
1781            # Check for a match.
1782            if ($row->[$idxMatch] =~ m/$pattern/i) {
1783                # We have a match, so output a row. This is a bit tricky, since we may
1784                # be putting out multiple columns of data from the input.
1785                my $value = join(" ", map { $row->[$_] } @{$idxValues});
1786                $loader->Put($id, $value);
1787                $retVal++;
1788            }
1789        }
1790        Trace("$retVal special attributes found for $id and loader " . $loader->RelName() . ".") if T(4) && $retVal;
1791        # Return the number of matches.
1792        return $retVal;
1793    }
1794    
1795  =head3 TableLoader  =head3 TableLoader
1796    
1797  Create an ERDBLoad object for the specified table. The object is also added to  Create an ERDBLoad object for the specified table. The object is also added to
# Line 1581  Line 1806 
1806    
1807  Name of the table (relation) being loaded.  Name of the table (relation) being loaded.
1808    
 =item ignore  
   
 TRUE if the table should be ignored entirely, else FALSE.  
   
1809  =item RETURN  =item RETURN
1810    
1811  Returns an ERDBLoad object for loading the specified table.  Returns an ERDBLoad object for loading the specified table.
# Line 1595  Line 1816 
1816    
1817  sub _TableLoader {  sub _TableLoader {
1818      # Get the parameters.      # Get the parameters.
1819      my ($self, $tableName, $ignore) = @_;      my ($self, $tableName) = @_;
1820      # Create the load object.      # Create the load object.
1821      my $retVal = ERDBLoad->new($self->{erdb}, $tableName, $self->{loadDirectory}, $self->LoadOnly,      my $retVal = ERDBLoad->new($self->{erdb}, $tableName, $self->{loadDirectory}, $self->LoadOnly);
                                $ignore);  
1822      # Cache it in the loader list.      # Cache it in the loader list.
1823      push @{$self->{loaders}}, $retVal;      push @{$self->{loaders}}, $retVal;
1824      # Return it to the caller.      # Return it to the caller.
# Line 1670  Line 1890 
1890      return $retVal;      return $retVal;
1891  }  }
1892    
1893    =head3 GetGenomeAttributes
1894    
1895    C<< my $aHashRef = GetGenomeAttributes($fig, $genomeID, \@fids, \@propKeys); >>
1896    
1897    Return a hash of attributes keyed on feature ID. This method gets all the NMPDR-related
1898    attributes for all the features of a genome in a single call, then organizes them into
1899    a hash.
1900    
1901    =over 4
1902    
1903    =item fig
1904    
1905    FIG-like object for accessing attributes.
1906    
1907    =item genomeID
1908    
1909    ID of the genome who's attributes are desired.
1910    
1911    =item fids
1912    
1913    Reference to a list of the feature IDs whose attributes are to be kept.
1914    
1915    =item propKeys
1916    
1917    A list of the keys to retrieve.
1918    
1919    =item RETURN
1920    
1921    Returns a reference to a hash. The key of the hash is the feature ID. The value is the
1922    reference to a list of the feature's attribute tuples. Each tuple contains the feature ID,
1923    the attribute key, and one or more attribute values.
1924    
1925    =back
1926    
1927    =cut
1928    
1929    sub GetGenomeAttributes {
1930        # Get the parameters.
1931        my ($fig, $genomeID, $fids, $propKeys) = @_;
1932        # Declare the return variable.
1933        my $retVal = {};
1934        # Initialize the hash. This not only enables us to easily determine which FIDs to
1935        # keep, it insures that the caller sees a list reference for every known fid,
1936        # simplifying the logic.
1937        for my $fid (@{$fids}) {
1938            $retVal->{$fid} = [];
1939        }
1940        # Get the attributes. If ev_code_cron is running, we may get a timeout error, so
1941        # an eval is used.
1942        my @aList = ();
1943        eval {
1944            @aList = $fig->get_attributes("fig|$genomeID%", $propKeys);
1945            Trace(scalar(@aList) . " attributes returned for genome $genomeID.") if T(3);
1946        };
1947        # Check for a problem.
1948        if ($@) {
1949            Trace("Retrying attributes for $genomeID due to error: $@") if T(1);
1950            # Our fallback plan is to process the attributes in blocks of 100. This is much slower,
1951            # but allows us to continue processing.
1952            my $nFids = scalar @{$fids};
1953            for (my $i = 0; $i < $nFids; $i += 100) {
1954                # Determine the index of the last feature ID we'll be specifying on this pass.
1955                # Normally it's $i + 99, but if we're close to the end it may be less.
1956                my $end = ($i + 100 > $nFids ? $nFids - 1 : $i + 99);
1957                # Get a slice of the fid list.
1958                my @slice = @{$fids}[$i .. $end];
1959                # Get the relevant attributes.
1960                Trace("Retrieving attributes for fids $i to $end.") if T(3);
1961                my @aShort = $fig->get_attributes(\@slice, $propKeys);
1962                Trace(scalar(@aShort) . " attributes returned for fids $i to $end.") if T(3);
1963                push @aList, @aShort;
1964            }
1965        }
1966        # Now we should have all the interesting attributes in @aList. Populate the hash with
1967        # them.
1968        for my $aListEntry (@aList) {
1969            my $fid = $aListEntry->[0];
1970            if (exists $retVal->{$fid}) {
1971                push @{$retVal->{$fid}}, $aListEntry;
1972            }
1973        }
1974        # Return the result.
1975        return $retVal;
1976    }
1977    
1978    
1979  1;  1;

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