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revision 1.61, Sun Jul 30 01:41:34 2006 UTC revision 1.95, Sat Sep 20 14:33:28 2008 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;
14      use HTML;      use HTML;
15        use AliasAnalysis;
16        use BioWords;
17    
18  =head1 Sprout Load Methods  =head1 Sprout Load Methods
19    
# Line 50  Line 53 
53    
54  =head3 new  =head3 new
55    
56  C<< my $spl = SproutLoad->new($sprout, $fig, $genomeFile, $subsysFile, $options); >>      my $spl = SproutLoad->new($sprout, $fig, $genomeFile, $subsysFile, $options);
57    
58  Construct a new Sprout Loader object, specifying the two participating databases and  Construct a new Sprout Loader object, specifying the two participating databases and
59  the name of the files containing the list of genomes and subsystems to use.  the name of the files containing the list of genomes and subsystems to use.
# Line 80  Line 83 
83  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
84  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
85  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>
86  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.
87    
88  =item options  =item options
89    
# Line 101  Line 104 
104              # Here we want all the complete genomes and an access code of 1.              # Here we want all the complete genomes and an access code of 1.
105              my @genomeList = $fig->genomes(1);              my @genomeList = $fig->genomes(1);
106              %genomes = map { $_ => 1 } @genomeList;              %genomes = map { $_ => 1 } @genomeList;
107                Trace(scalar(keys %genomes) . " genomes found.") if T(3);
108          } else {          } else {
109              my $type = ref $genomeFile;              my $type = ref $genomeFile;
110              Trace("Genome file parameter type is \"$type\".") if T(3);              Trace("Genome file parameter type is \"$type\".") if T(3);
# Line 120  Line 124 
124                      # an omitted access code can be defaulted to 1.                      # an omitted access code can be defaulted to 1.
125                      for my $genomeLine (@genomeList) {                      for my $genomeLine (@genomeList) {
126                          my ($genomeID, $accessCode) = split("\t", $genomeLine);                          my ($genomeID, $accessCode) = split("\t", $genomeLine);
127                          if (undef $accessCode) {                          if (! defined($accessCode)) {
128                              $accessCode = 1;                              $accessCode = 1;
129                          }                          }
130                          $genomes{$genomeID} = $accessCode;                          $genomes{$genomeID} = $accessCode;
# Line 138  Line 142 
142          if (! defined $subsysFile || $subsysFile eq '') {          if (! defined $subsysFile || $subsysFile eq '') {
143              # 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.
144              my @subs = $fig->all_subsystems();              my @subs = $fig->all_subsystems();
145              # Loop through, checking for usability.              # Loop through, checking for the NMPDR file.
146              for my $sub (@subs) {              for my $sub (@subs) {
147                  if ($fig->usable_subsystem($sub)) {                  if ($fig->nmpdr_subsystem($sub)) {
148                      $subsystems{$sub} = 1;                      $subsystems{$sub} = 1;
149                  }                  }
150              }              }
# Line 163  Line 167 
167                  Confess("Invalid subsystem parameter in SproutLoad constructor.");                  Confess("Invalid subsystem parameter in SproutLoad constructor.");
168              }              }
169          }          }
170            # Go through the subsys hash again, creating the keyword list for each subsystem.
171            for my $subsystem (keys %subsystems) {
172                my $name = $subsystem;
173                $name =~ s/_/ /g;
174                $subsystems{$subsystem} = $name;
175      }      }
176        }
177        # Get the list of NMPDR-oriented attribute keys.
178        my @propKeys = $fig->get_group_keys("NMPDR");
179      # Get the data directory from the Sprout object.      # Get the data directory from the Sprout object.
180      my ($directory) = $sprout->LoadInfo();      my ($directory) = $sprout->LoadInfo();
181      # Create the Sprout load object.      # Create the Sprout load object.
# Line 175  Line 187 
187                    loadDirectory => $directory,                    loadDirectory => $directory,
188                    erdb => $sprout,                    erdb => $sprout,
189                    loaders => [],                    loaders => [],
190                    options => $options                    options => $options,
191                      propKeys => \@propKeys,
192                   };                   };
193      # Bless and return it.      # Bless and return it.
194      bless $retVal, $class;      bless $retVal, $class;
# Line 184  Line 197 
197    
198  =head3 LoadOnly  =head3 LoadOnly
199    
200  C<< my $flag = $spl->LoadOnly; >>      my $flag = $spl->LoadOnly;
201    
202  Return TRUE if we are in load-only mode, else FALSE.  Return TRUE if we are in load-only mode, else FALSE.
203    
# Line 195  Line 208 
208      return $self->{options}->{loadOnly};      return $self->{options}->{loadOnly};
209  }  }
210    
 =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};  
 }  
211    
212  =head3 LoadGenomeData  =head3 LoadGenomeData
213    
214  C<< my $stats = $spl->LoadGenomeData(); >>      my $stats = $spl->LoadGenomeData();
215    
216  Load the Genome, Contig, and Sequence data from FIG into Sprout.  Load the Genome, Contig, and Sequence data from FIG into Sprout.
217    
# Line 247  Line 248 
248      my $genomeCount = (keys %{$genomeHash});      my $genomeCount = (keys %{$genomeHash});
249      # Create load objects for each of the tables we're loading.      # Create load objects for each of the tables we're loading.
250      my $loadGenome = $self->_TableLoader('Genome');      my $loadGenome = $self->_TableLoader('Genome');
251      my $loadHasContig = $self->_TableLoader('HasContig', $self->PrimaryOnly);      my $loadHasContig = $self->_TableLoader('HasContig');
252      my $loadContig = $self->_TableLoader('Contig', $self->PrimaryOnly);      my $loadContig = $self->_TableLoader('Contig');
253      my $loadIsMadeUpOf = $self->_TableLoader('IsMadeUpOf', $self->PrimaryOnly);      my $loadIsMadeUpOf = $self->_TableLoader('IsMadeUpOf');
254      my $loadSequence = $self->_TableLoader('Sequence', $self->PrimaryOnly);      my $loadSequence = $self->_TableLoader('Sequence');
255      if ($self->{options}->{loadOnly}) {      if ($self->{options}->{loadOnly}) {
256          Trace("Loading from existing files.") if T(2);          Trace("Loading from existing files.") if T(2);
257      } else {      } else {
258          Trace("Generating genome data.") if T(2);          Trace("Generating genome data.") if T(2);
259            # Get the full info for the FIG genomes.
260            my %genomeInfo = map { $_->[0] => { gname => $_->[1], szdna => $_->[2], maindomain => $_->[3],
261                                                pegs => $_->[4], rnas => $_->[5], complete => $_->[6] } } @{$fig->genome_info()};
262          # Now we loop through the genomes, generating the data for each one.          # Now we loop through the genomes, generating the data for each one.
263          for my $genomeID (sort keys %{$genomeHash}) {          for my $genomeID (sort keys %{$genomeHash}) {
264              Trace("Generating data for genome $genomeID.") if T(3);              Trace("Generating data for genome $genomeID.") if T(3);
# Line 266  Line 270 
270              my $extra = join " ", @extraData;              my $extra = join " ", @extraData;
271              # Get the full taxonomy.              # Get the full taxonomy.
272              my $taxonomy = $fig->taxonomy_of($genomeID);              my $taxonomy = $fig->taxonomy_of($genomeID);
273                # Get the version. If no version is specified, we default to the genome ID by itself.
274                my $version = $fig->genome_version($genomeID);
275                if (! defined($version)) {
276                    $version = $genomeID;
277                }
278                # Get the DNA size.
279                my $dnaSize = $fig->genome_szdna($genomeID);
280                # Open the NMPDR group file for this genome.
281                my $group;
282                if (open(TMP, "<$FIG_Config::organisms/$genomeID/NMPDR") &&
283                    defined($group = <TMP>)) {
284                    # Clean the line ending.
285                    chomp $group;
286                } else {
287                    # No group, so use the default.
288                    $group = $FIG_Config::otherGroup;
289                }
290                close TMP;
291                # Get the contigs.
292                my @contigs = $fig->all_contigs($genomeID);
293                # Get this genome's info array.
294                my $info = $genomeInfo{$genomeID};
295              # Output the genome record.              # Output the genome record.
296              $loadGenome->Put($genomeID, $accessCode, $fig->is_complete($genomeID), $genus,              $loadGenome->Put($genomeID, $accessCode, $info->{complete}, scalar(@contigs),
297                               $species, $extra, $taxonomy);                               $dnaSize, $genus, $info->{pegs}, $group, $info->{rnas}, $species, $extra, $version, $taxonomy);
298              # Now we loop through each of the genome's contigs.              # Now we loop through each of the genome's contigs.
             my @contigs = $fig->all_contigs($genomeID);  
299              for my $contigID (@contigs) {              for my $contigID (@contigs) {
300                  Trace("Processing contig $contigID for $genomeID.") if T(4);                  Trace("Processing contig $contigID for $genomeID.") if T(4);
301                  $loadContig->Add("contigIn");                  $loadContig->Add("contigIn");
# Line 306  Line 331 
331      return $retVal;      return $retVal;
332  }  }
333    
 =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;  
 }  
   
334  =head3 LoadFeatureData  =head3 LoadFeatureData
335    
336  C<< my $stats = $spl->LoadFeatureData(); >>      my $stats = $spl->LoadFeatureData();
337    
338  Load the feature data from FIG into Sprout.  Load the feature data from FIG into Sprout.
339    
# Line 444  Line 343 
343    
344      Feature      Feature
345      FeatureAlias      FeatureAlias
346        IsAliasOf
347      FeatureLink      FeatureLink
348      FeatureTranslation      FeatureTranslation
349      FeatureUpstream      FeatureUpstream
350      IsLocatedIn      IsLocatedIn
351      HasFeature      HasFeature
352        HasRoleInSubsystem
353        FeatureEssential
354        FeatureVirulent
355        FeatureIEDB
356        CDD
357        IsPresentOnProteinOf
358        CellLocation
359        IsPossiblePlaceFor
360        ExternalDatabase
361        IsAlsoFoundIn
362        Keyword
363    
364  =over 4  =over 4
365    
# Line 463  Line 374 
374  sub LoadFeatureData {  sub LoadFeatureData {
375      # Get this object instance.      # Get this object instance.
376      my ($self) = @_;      my ($self) = @_;
377      # Get the FIG object.      # Get the FIG and Sprout objects.
378      my $fig = $self->{fig};      my $fig = $self->{fig};
379        my $sprout = $self->{sprout};
380      # Get the table of genome IDs.      # Get the table of genome IDs.
381      my $genomeHash = $self->{genomes};      my $genomeHash = $self->{genomes};
382      # Create load objects for each of the tables we're loading.      # Create load objects for each of the tables we're loading.
383      my $loadFeature = $self->_TableLoader('Feature');      my $loadFeature = $self->_TableLoader('Feature');
384      my $loadIsLocatedIn = $self->_TableLoader('IsLocatedIn', $self->PrimaryOnly);      my $loadIsLocatedIn = $self->_TableLoader('IsLocatedIn');
385      my $loadFeatureAlias = $self->_TableLoader('FeatureAlias');      my $loadFeatureAlias = $self->_TableLoader('FeatureAlias');
386        my $loadIsAliasOf = $self->_TableLoader('IsAliasOf');
387      my $loadFeatureLink = $self->_TableLoader('FeatureLink');      my $loadFeatureLink = $self->_TableLoader('FeatureLink');
388      my $loadFeatureTranslation = $self->_TableLoader('FeatureTranslation');      my $loadFeatureTranslation = $self->_TableLoader('FeatureTranslation');
389      my $loadFeatureUpstream = $self->_TableLoader('FeatureUpstream');      my $loadFeatureUpstream = $self->_TableLoader('FeatureUpstream');
390      my $loadHasFeature = $self->_TableLoader('HasFeature');      my $loadHasFeature = $self->_TableLoader('HasFeature');
391        my $loadHasRoleInSubsystem = $self->_TableLoader('HasRoleInSubsystem');
392        my $loadFeatureEssential = $self->_TableLoader('FeatureEssential');
393        my $loadFeatureVirulent = $self->_TableLoader('FeatureVirulent');
394        my $loadFeatureIEDB = $self->_TableLoader('FeatureIEDB');
395        my $loadCDD = $self->_TableLoader('CDD');
396        my $loadIsPresentOnProteinOf = $self->_TableLoader('IsPresentOnProteinOf');
397        my $loadCellLocation = $self->_TableLoader('CellLocation');
398        my $loadIsPossiblePlaceFor = $self->_TableLoader('IsPossiblePlaceFor');
399        my $loadIsAlsoFoundIn = $self->_TableLoader('IsAlsoFoundIn');
400        my $loadExternalDatabase = $self->_TableLoader('ExternalDatabase');
401        my $loadKeyword = $self->_TableLoader('Keyword');
402        # Get the subsystem hash.
403        my $subHash = $self->{subsystems};
404        # Get the property keys.
405        my $propKeys = $self->{propKeys};
406        # Create a hashes to hold CDD, Cell Location (PSORT), External Database, and alias values.
407        my %CDD = ();
408        my %alias = ();
409        my %cellLocation = ();
410        my %xdb = ();
411        # Create the bio-words object.
412        my $biowords = BioWords->new(exceptions => "$FIG_Config::sproutData/Exceptions.txt",
413                                     stops => "$FIG_Config::sproutData/StopWords.txt",
414                                     cache => 0);
415        # One of the things we have to do here is build the keyword table, and the keyword
416        # table needs to contain the originating text and feature count for each stem. Unfortunately,
417        # the number of distinct keywords is so large it causes PERL to hang if we try to
418        # keep them in memory. As a result, we need to track them using disk files.
419        # Our approach will be to use two sequential files. One will contain stems and phonexes.
420        # Each time a stem occurs in a feature, a record will be written to that file. The stem
421        # file can then be sorted and collated to determine the number of features for each
422        # stem. A separate file will contain keywords and stems. This last file
423        # will be subjected to a sort unique on stem/keyword. The file is then merged
424        # with the stem file to create the keyword table relation (keyword, stem, phonex, count).
425        my $stemFileName = "$FIG_Config::temp/stems$$.tbl";
426        my $keyFileName = "$FIG_Config::temp/keys$$.tbl";
427        my $stemh = Open(undef, "| sort -T\"$FIG_Config::temp\" -t\"\t\" -k1,1 >$stemFileName");
428        my $keyh = Open(undef, "| sort -T\"$FIG_Config::temp\" -t\"\t\" -u -k1,1 -k2,2 >$keyFileName");
429      # 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
430      # locations.      # locations.
431      my $chunkSize = $self->{sprout}->MaxSegment();      my $chunkSize = $self->{sprout}->MaxSegment();
# Line 483  Line 434 
434      } else {      } else {
435          Trace("Generating feature data.") if T(2);          Trace("Generating feature data.") if T(2);
436          # Now we loop through the genomes, generating the data for each one.          # Now we loop through the genomes, generating the data for each one.
437          for my $genomeID (sort keys %{$genomeHash}) {          my @allGenomes = sort keys %{$genomeHash};
438            Trace(scalar(@allGenomes) . " genomes found in list.") if T(3);
439            for my $genomeID (@allGenomes) {
440              Trace("Loading features for genome $genomeID.") if T(3);              Trace("Loading features for genome $genomeID.") if T(3);
441              $loadFeature->Add("genomeIn");              $loadFeature->Add("genomeIn");
442              # Get the feature list for this genome.              # Get the feature list for this genome.
443              my $features = $fig->all_features_detailed($genomeID);              my $features = $fig->all_features_detailed_fast($genomeID);
444              # Sort and count the list.              # Sort and count the list.
445              my @featureTuples = sort { $a->[0] cmp $b->[0] } @{$features};              my @featureTuples = sort { $a->[0] cmp $b->[0] } @{$features};
446              my $count = scalar @featureTuples;              my $count = scalar @featureTuples;
447                my @fids = map { $_->[0] } @featureTuples;
448              Trace("$count features found for genome $genomeID.") if T(3);              Trace("$count features found for genome $genomeID.") if T(3);
449                # Get the attributes for this genome and put them in a hash by feature ID.
450                my $attributes = GetGenomeAttributes($fig, $genomeID, \@fids, $propKeys);
451                Trace("Looping through features for $genomeID.") if T(3);
452              # Set up for our duplicate-feature check.              # Set up for our duplicate-feature check.
453              my $oldFeatureID = "";              my $oldFeatureID = "";
454              # Loop through the features.              # Loop through the features.
455              for my $featureTuple (@featureTuples) {              for my $featureTuple (@featureTuples) {
456                  # Split the tuple.                  # Split the tuple.
457                  my ($featureID, $locations, undef, $type) = @{$featureTuple};                  my ($featureID, $locations, undef, $type, $minloc, $maxloc, $assignment, $user, $quality) = @{$featureTuple};
458                  # Check for duplicates.                  # Check for duplicates.
459                  if ($featureID eq $oldFeatureID) {                  if ($featureID eq $oldFeatureID) {
460                      Trace("Duplicate feature $featureID found.") if T(1);                      Trace("Duplicate feature $featureID found.") if T(1);
# Line 505  Line 462 
462                      $oldFeatureID = $featureID;                      $oldFeatureID = $featureID;
463                      # Count this feature.                      # Count this feature.
464                      $loadFeature->Add("featureIn");                      $loadFeature->Add("featureIn");
465                      # Create the feature record.                      # Fix the quality. It is almost always a space, but some odd stuff might sneak through, and the
466                      $loadFeature->Put($featureID, 1, $type);                      # Sprout database requires a single character.
467                      # Link it to the parent genome.                      if (! defined($quality) || $quality eq "") {
468                      $loadHasFeature->Put($genomeID, $featureID, $type);                          $quality = " ";
469                        }
470                        # Begin building the keywords. We start with the genome ID, the
471                        # feature ID, the taxonomy, and the organism name.
472                        my @keywords = ($genomeID, $featureID, $fig->genus_species($genomeID),
473                                        $fig->taxonomy_of($genomeID));
474                      # Create the aliases.                      # Create the aliases.
475                      for my $alias ($fig->feature_aliases($featureID)) {                      for my $alias ($fig->feature_aliases($featureID)) {
476                          $loadFeatureAlias->Put($featureID, $alias);                          #Connect this alias to this feature.
477                            $loadIsAliasOf->Put($alias, $featureID);
478                            push @keywords, $alias;
479                            # If this is a locus tag, also add its natural form as a keyword.
480                            my $naturalName = AliasAnalysis::Type(LocusTag => $alias);
481                            if ($naturalName) {
482                                push @keywords, $naturalName;
483                            }
484                            # If this is the first time for the specified alias, create its
485                            # alias record.
486                            if (! exists $alias{$alias}) {
487                                $loadFeatureAlias->Put($alias);
488                                $alias{$alias} = 1;
489                            }
490                        }
491                        # Add the corresponding IDs. We ask for 2-tuples of the form (id, database).
492                        my @corresponders = $fig->get_corresponding_ids($featureID, 1);
493                        for my $tuple (@corresponders) {
494                            my ($id, $xdb) = @{$tuple};
495                            # Ignore SEED: that's us.
496                            if ($xdb ne 'SEED') {
497                                # Connect this ID to the feature.
498                                $loadIsAlsoFoundIn->Put($featureID, $xdb, $id);
499                                # Add it as a keyword.
500                                push @keywords, $id;
501                                # If this is a new database, create a record for it.
502                                if (! exists $xdb{$xdb}) {
503                                    $xdb{$xdb} = 1;
504                                    $loadExternalDatabase->Put($xdb);
505                      }                      }
506                            }
507                        }
508                        Trace("Assignment for $featureID is: $assignment") if T(4);
509                        # Break the assignment into words and shove it onto the
510                        # keyword list.
511                        push @keywords, split(/\s+/, $assignment);
512                        # Link this feature to the parent genome.
513                        $loadHasFeature->Put($genomeID, $featureID, $type);
514                      # Get the links.                      # Get the links.
515                      my @links = $fig->fid_links($featureID);                      my @links = $fig->fid_links($featureID);
516                      for my $link (@links) {                      for my $link (@links) {
# Line 531  Line 529 
529                              $loadFeatureUpstream->Put($featureID, $upstream);                              $loadFeatureUpstream->Put($featureID, $upstream);
530                          }                          }
531                      }                      }
532                        # Now we need to find the subsystems this feature participates in.
533                        # We also add the subsystems to the keyword list. Before we do that,
534                        # we must convert underscores to spaces.
535                        my @subsystems = $fig->peg_to_subsystems($featureID);
536                        for my $subsystem (@subsystems) {
537                            # Only proceed if we like this subsystem.
538                            if (exists $subHash->{$subsystem}) {
539                                # Store the has-role link.
540                                $loadHasRoleInSubsystem->Put($featureID, $subsystem, $genomeID, $type);
541                                # Save the subsystem's keyword data.
542                                my $subKeywords = $subHash->{$subsystem};
543                                push @keywords, split /\s+/, $subKeywords;
544                                # Now we need to get this feature's role in the subsystem.
545                                my $subObject = $fig->get_subsystem($subsystem);
546                                my @roleColumns = $subObject->get_peg_roles($featureID);
547                                my @allRoles = $subObject->get_roles();
548                                for my $col (@roleColumns) {
549                                    my $role = $allRoles[$col];
550                                    push @keywords, split /\s+/, $role;
551                                    push @keywords, $subObject->get_role_abbr($col);
552                                }
553                            }
554                        }
555                        # There are three special attributes computed from property
556                        # data that we build next. If the special attribute is non-empty,
557                        # its name will be added to the keyword list. First, we get all
558                        # the attributes for this feature. They will come back as
559                        # 4-tuples: [peg, name, value, URL]. We use a 3-tuple instead:
560                        # [name, value, value with URL]. (We don't need the PEG, since
561                        # we already know it.)
562                        my @attributes = map { [$_->[1], $_->[2], Tracer::CombineURL($_->[2], $_->[3])] }
563                                             @{$attributes->{$featureID}};
564                        # Now we process each of the special attributes.
565                        if (SpecialAttribute($featureID, \@attributes,
566                                             1, [0,2], '^(essential|potential_essential)$',
567                                             $loadFeatureEssential)) {
568                            push @keywords, 'essential';
569                            $loadFeature->Add('essential');
570                        }
571                        if (SpecialAttribute($featureID, \@attributes,
572                                             0, [2], '^virulen',
573                                             $loadFeatureVirulent)) {
574                            push @keywords, 'virulent';
575                            $loadFeature->Add('virulent');
576                        }
577                        if (SpecialAttribute($featureID, \@attributes,
578                                             0, [0,2], '^iedb_',
579                                             $loadFeatureIEDB)) {
580                            push @keywords, 'iedb';
581                            $loadFeature->Add('iedb');
582                        }
583                        # Now we have some other attributes we need to process. To get
584                        # through them, we convert the attribute list for this feature
585                        # into a two-layer hash: key => subkey => value.
586                        my %attributeHash = ();
587                        for my $attrRow (@{$attributes->{$featureID}}) {
588                            my (undef, $key, @values) = @{$attrRow};
589                            my ($realKey, $subKey);
590                            if ($key =~ /^([^:]+)::(.+)/) {
591                                ($realKey, $subKey) = ($1, $2);
592                            } else {
593                                ($realKey, $subKey) = ($key, "");
594                            }
595                            if (exists $attributeHash{$1}) {
596                                $attributeHash{$1}->{$2} = \@values;
597                            } else {
598                                $attributeHash{$1} = {$2 => \@values};
599                            }
600                        }
601                        # First we handle CDD. This is a bit complicated, because
602                        # there are multiple CDDs per protein.
603                        if (exists $attributeHash{CDD}) {
604                            # Get the hash of CDD IDs to scores for this feature. We
605                            # already know it exists because of the above IF.
606                            my $cddHash = $attributeHash{CDD};
607                            my @cddData = sort keys %{$cddHash};
608                            for my $cdd (@cddData) {
609                                # Extract the score for this CDD and decode it.
610                                my ($codeScore) = split(/\s*[,;]\s*/, $cddHash->{$cdd}->[0]);
611                                my $realScore = FIGRules::DecodeScore($codeScore);
612                                # We can't afford to crash because of a bad attribute
613                                # value, hence the IF below.
614                                if (! defined($realScore)) {
615                                    # Bad score, so count it.
616                                    $loadFeature->Add('badCDDscore');
617                                    Trace("CDD score \"$codeScore\" for feature $featureID invalid.") if T(3);
618                                } else {
619                                    # Create the connection.
620                                    $loadIsPresentOnProteinOf->Put($cdd, $featureID, $realScore);
621                                    # If this CDD does not yet exist, create its record.
622                                    if (! exists $CDD{$cdd}) {
623                                        $CDD{$cdd} = 1;
624                                        $loadCDD->Put($cdd);
625                                    }
626                                }
627                            }
628                        }
629                        # Next we do PSORT cell locations. here the confidence value
630                        # could have the value "unknown", which we translate to -1.
631                        if (exists $attributeHash{PSORT}) {
632                            # This will be a hash of cell locations to confidence
633                            # factors.
634                            my $psortHash = $attributeHash{PSORT};
635                            for my $psort (keys %{$psortHash}) {
636                                # Get the confidence, and convert it to a number if necessary.
637                                my $confidence = $psortHash->{$psort};
638                                if ($confidence eq 'unknown') {
639                                    $confidence = -1;
640                                }
641                                $loadIsPossiblePlaceFor->Put($psort, $featureID, $confidence);
642                                # If this cell location does not yet exist, create its record.
643                                if (! exists $cellLocation{$psort}) {
644                                    $cellLocation{$psort} = 1;
645                                    $loadCellLocation->Put($psort);
646                                }
647                                # If this is a significant location, add it as a keyword.
648                                if ($confidence > 2.5) {
649                                    push @keywords, $psort;
650                                }
651                            }
652                        }
653                        # Phobius data is next. This consists of the signal peptide location and
654                        # the transmembrane locations.
655                        my $signalList = "";
656                        my $transList = "";
657                        if (exists $attributeHash{Phobius}) {
658                            # This will be a hash of two keys (transmembrane and signal) to
659                            # location strings. If there's no value, we stuff in an empty string.
660                            $signalList = GetCommaList($attributeHash{Phobius}->{signal});
661                            $transList = GetCommaList($attributeHash{Phobius}->{transmembrane});
662                        }
663                        # Here are some more numbers: isoelectric point, molecular weight, and
664                        # the similar-to-human flag.
665                        my $isoelectric = 0;
666                        if (exists $attributeHash{isoelectric_point}) {
667                            $isoelectric = $attributeHash{isoelectric_point}->{""};
668                        }
669                        my $similarToHuman = 0;
670                        if (exists $attributeHash{similar_to_human} && $attributeHash{similar_to_human}->{""} eq 'yes') {
671                            $similarToHuman = 1;
672                        }
673                        my $molecularWeight = 0;
674                        if (exists $attributeHash{molecular_weight}) {
675                            $molecularWeight = $attributeHash{molecular_weight}->{""};
676                        }
677                        # Create the keyword string.
678                        my $keywordString = join(" ", @keywords);
679                        Trace("Real keyword string for $featureID: $keywordString.") if T(4);
680                        # Get rid of annoying punctuation.
681                        $keywordString =~ s/[();@#\/]/ /g;
682                        # Get the list of keywords in the keyword string.
683                        my @realKeywords = grep { $biowords->IsWord($_) } $biowords->Split($keywordString);
684                        # We need to do two things here: create the keyword string for the feature table
685                        # and write records to the keyword and stem files. The stuff we write to
686                        # the files will be taken from the following two hashes. The stuff used
687                        # to create the keyword string will be taken from the list.
688                        my (%keys, %stems, @realStems);
689                        for my $keyword (@realKeywords) {
690                            # Compute the stem and phonex for this keyword.
691                            my ($stem, $phonex) = $biowords->StemLookup($keyword);
692                            # Only proceed if a stem comes back. If no stem came back, it's a
693                            # stop word and we throw it away.
694                            if ($stem) {
695                                $keys{$keyword} = $stem;
696                                $stems{$stem} = $phonex;
697                                push @realStems, $stem;
698                            }
699                        }
700                        # Now create the keyword string.
701                        my $cleanWords = join(" ", @realStems);
702                        Trace("Keyword string for $featureID: $cleanWords") if T(4);
703                        # Write the stem and keyword records.
704                        for my $stem (keys %stems) {
705                            Tracer::PutLine($stemh, [$stem, $stems{$stem}]);
706                        }
707                        for my $key (keys %keys) {
708                            # The stem goes first in this file, because we want to sort
709                            # by stem and then keyword.
710                            Tracer::PutLine($keyh, [$keys{$key}, $key]);
711                        }
712                        # Now we need to process the feature's locations. First, we split them up.
713                        my @locationList = split /\s*,\s*/, $locations;
714                        # Next, we convert them to Sprout location objects.
715                        my @locObjectList = map { BasicLocation->new("$genomeID:$_") } @locationList;
716                        # Assemble them into a sprout location string for later.
717                        my $locationString = join(", ", map { $_->String } @locObjectList);
718                        # We'll store the sequence length in here.
719                        my $sequenceLength = 0;
720                      # 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
721                      # 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
722                      # the maximum segment size. This simplifies the genes_in_region processing                      # the maximum segment size. This simplifies the genes_in_region processing
723                      # for Sprout.                      # for Sprout. To start, we create the location position indicator.
                     my @locationList = split /\s*,\s*/, $locations;  
                     # Create the location position indicator.  
724                      my $i = 1;                      my $i = 1;
725                      # Loop through the locations.                      # Loop through the locations.
726                      for my $location (@locationList) {                      for my $locObject (@locObjectList) {
727                          # Parse the location.                          # Record the length.
728                          my $locObject = BasicLocation->new("$genomeID:$location");                          $sequenceLength += $locObject->Length;
729                          # Split it into a list of chunks.                          # Split this location into a list of chunks.
730                          my @locOList = ();                          my @locOList = ();
731                          while (my $peeling = $locObject->Peel($chunkSize)) {                          while (my $peeling = $locObject->Peel($chunkSize)) {
732                              $loadIsLocatedIn->Add("peeling");                              $loadIsLocatedIn->Add("peeling");
# Line 557  Line 741 
741                              $i++;                              $i++;
742                          }                          }
743                      }                      }
744                        # Now we get some ancillary flags.
745                        my $locked = $fig->is_locked_fid($featureID);
746                        my $in_genbank = $fig->peg_in_gendb($featureID);
747                        # Create the feature record.
748                        $loadFeature->Put($featureID, 1, $user, $quality, $type, $in_genbank, $isoelectric, $locked, $molecularWeight,
749                                          $sequenceLength, $signalList, $similarToHuman, $assignment, $cleanWords, $locationString,
750                                          $transList);
751                    }
752                }
753                Trace("Genome $genomeID processed.") if T(3);
754            }
755        }
756        Trace("Sorting keywords.") if T(2);
757        # Now we need to load the keyword table from the key and stem files.
758        close $keyh;
759        close $stemh;
760        Trace("Loading keywords.") if T(2);
761        $keyh = Open(undef, "<$keyFileName");
762        $stemh = Open(undef, "<$stemFileName");
763        # We'll count the keywords in here, for tracing purposes.
764        my $count = 0;
765        # These variables track the current stem's data. When an incoming
766        # keyword's stem changes, these will be recomputed.
767        my ($currentStem, $currentPhonex, $currentCount);
768        # Prime the loop by reading the first stem in the stem file.
769        my ($nextStem, $nextPhonex) = Tracer::GetLine($stemh);
770        # Loop through the keyword file.
771        while (! eof $keyh) {
772            # Read this keyword.
773            my ($thisStem, $thisKey) = Tracer::GetLine($keyh);
774            # Check to see if it's the new stem yet.
775            if ($thisStem ne $currentStem) {
776                # Yes. It's a terrible error if it's not also the next stem.
777                if ($thisStem ne $nextStem) {
778                    Confess("Error in stem file. Expected \"$nextStem\", but found \"$thisStem\".");
779                } else {
780                    # Here we're okay.
781                    ($currentStem, $currentPhonex) = ($nextStem, $nextPhonex);
782                    # Count the number of features for this stem.
783                    $currentCount = 0;
784                    while ($nextStem eq $thisStem) {
785                        ($nextStem, $nextPhonex) = Tracer::GetLine($stemh);
786                        $currentCount++;
787                  }                  }
788              }              }
789          }          }
790      }          # Now $currentStem is the same as $thisStem, and the other $current-vars
791      # Finish the loads.          # contain the stem's data (phonex and count).
792      my $retVal = $self->_FinishAll();          $loadKeyword->Put($thisKey, $currentCount, $currentPhonex, $currentStem);
793      return $retVal;          if (++$count % 1000 == 0 && T(3)) {
794  }              Trace("$count keywords loaded.");
   
 =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,  
                                                            $score);  
                     }  
                 }  
             }  
795          }          }
796      }      }
797        Trace("$count keywords loaded into keyword table.") if T(2);
798      # Finish the loads.      # Finish the loads.
799      my $retVal = $self->_FinishAll();      my $retVal = $self->_FinishAll();
800      return $retVal;      return $retVal;
# Line 636  Line 802 
802    
803  =head3 LoadSubsystemData  =head3 LoadSubsystemData
804    
805  C<< my $stats = $spl->LoadSubsystemData(); >>      my $stats = $spl->LoadSubsystemData();
806    
807  Load the subsystem data from FIG into Sprout.  Load the subsystem data from FIG into Sprout.
808    
# Line 652  Line 818 
818      SubsystemClass      SubsystemClass
819      Role      Role
820      RoleEC      RoleEC
821        IsIdentifiedByEC
822      SSCell      SSCell
823      ContainsFeature      ContainsFeature
824      IsGenomeOf      IsGenomeOf
# Line 665  Line 832 
832      ConsistsOfGenomes      ConsistsOfGenomes
833      GenomeSubset      GenomeSubset
834      HasGenomeSubset      HasGenomeSubset
     Catalyzes  
835      Diagram      Diagram
836      RoleOccursIn      RoleOccursIn
837        SubsystemHopeNotes
838    
839  =over 4  =over 4
840    
# Line 693  Line 860 
860      # Get the map list.      # Get the map list.
861      my @maps = $fig->all_maps;      my @maps = $fig->all_maps;
862      # Create load objects for each of the tables we're loading.      # Create load objects for each of the tables we're loading.
863      my $loadDiagram = $self->_TableLoader('Diagram', $self->PrimaryOnly);      my $loadDiagram = $self->_TableLoader('Diagram');
864      my $loadRoleOccursIn = $self->_TableLoader('RoleOccursIn', $self->PrimaryOnly);      my $loadRoleOccursIn = $self->_TableLoader('RoleOccursIn');
865      my $loadSubsystem = $self->_TableLoader('Subsystem');      my $loadSubsystem = $self->_TableLoader('Subsystem');
866      my $loadRole = $self->_TableLoader('Role', $self->PrimaryOnly);      my $loadRole = $self->_TableLoader('Role');
867      my $loadRoleEC = $self->_TableLoader('RoleEC', $self->PrimaryOnly);      my $loadRoleEC = $self->_TableLoader('RoleEC');
868      my $loadCatalyzes = $self->_TableLoader('Catalyzes', $self->PrimaryOnly);      my $loadIsIdentifiedByEC = $self->_TableLoader('IsIdentifiedByEC');
869      my $loadSSCell = $self->_TableLoader('SSCell', $self->PrimaryOnly);      my $loadCatalyzes = $self->_TableLoader('Catalyzes');
870      my $loadContainsFeature = $self->_TableLoader('ContainsFeature', $self->PrimaryOnly);      my $loadSSCell = $self->_TableLoader('SSCell');
871      my $loadIsGenomeOf = $self->_TableLoader('IsGenomeOf', $self->PrimaryOnly);      my $loadContainsFeature = $self->_TableLoader('ContainsFeature');
872      my $loadIsRoleOf = $self->_TableLoader('IsRoleOf', $self->PrimaryOnly);      my $loadIsGenomeOf = $self->_TableLoader('IsGenomeOf');
873      my $loadOccursInSubsystem = $self->_TableLoader('OccursInSubsystem', $self->PrimaryOnly);      my $loadIsRoleOf = $self->_TableLoader('IsRoleOf');
874      my $loadParticipatesIn = $self->_TableLoader('ParticipatesIn', $self->PrimaryOnly);      my $loadOccursInSubsystem = $self->_TableLoader('OccursInSubsystem');
875      my $loadHasSSCell = $self->_TableLoader('HasSSCell', $self->PrimaryOnly);      my $loadParticipatesIn = $self->_TableLoader('ParticipatesIn');
876      my $loadRoleSubset = $self->_TableLoader('RoleSubset', $self->PrimaryOnly);      my $loadHasSSCell = $self->_TableLoader('HasSSCell');
877      my $loadGenomeSubset = $self->_TableLoader('GenomeSubset', $self->PrimaryOnly);      my $loadRoleSubset = $self->_TableLoader('RoleSubset');
878      my $loadConsistsOfRoles = $self->_TableLoader('ConsistsOfRoles', $self->PrimaryOnly);      my $loadGenomeSubset = $self->_TableLoader('GenomeSubset');
879      my $loadConsistsOfGenomes = $self->_TableLoader('ConsistsOfGenomes', $self->PrimaryOnly);      my $loadConsistsOfRoles = $self->_TableLoader('ConsistsOfRoles');
880      my $loadHasRoleSubset = $self->_TableLoader('HasRoleSubset', $self->PrimaryOnly);      my $loadConsistsOfGenomes = $self->_TableLoader('ConsistsOfGenomes');
881      my $loadHasGenomeSubset = $self->_TableLoader('HasGenomeSubset', $self->PrimaryOnly);      my $loadHasRoleSubset = $self->_TableLoader('HasRoleSubset');
882      my $loadSubsystemClass = $self->_TableLoader('SubsystemClass', $self->PrimaryOnly);      my $loadHasGenomeSubset = $self->_TableLoader('HasGenomeSubset');
883        my $loadSubsystemClass = $self->_TableLoader('SubsystemClass');
884        my $loadSubsystemHopeNotes = $self->_TableLoader('SubsystemHopeNotes');
885      if ($self->{options}->{loadOnly}) {      if ($self->{options}->{loadOnly}) {
886          Trace("Loading from existing files.") if T(2);          Trace("Loading from existing files.") if T(2);
887      } else {      } else {
888          Trace("Generating subsystem data.") if T(2);          Trace("Generating subsystem data.") if T(2);
889          # 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
890          # information will be used to generate the Catalyzes table.          # information will be used to generate the Catalyzes table.
891          my %ecToRoles = ();          my %ecToRoles = ();
892          # 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 900 
900              # Get the subsystem object.              # Get the subsystem object.
901              my $sub = $fig->get_subsystem($subsysID);              my $sub = $fig->get_subsystem($subsysID);
902              # Only proceed if the subsystem has a spreadsheet.              # Only proceed if the subsystem has a spreadsheet.
903              if (! $sub->{empty_ss}) {              if (defined($sub) && ! $sub->{empty_ss}) {
904                  Trace("Creating subsystem $subsysID.") if T(3);                  Trace("Creating subsystem $subsysID.") if T(3);
905                  $loadSubsystem->Add("subsystemIn");                  $loadSubsystem->Add("subsystemIn");
906                  # Create the subsystem record.                  # Create the subsystem record.
907                  my $curator = $sub->get_curator();                  my $curator = $sub->get_curator();
908                  my $notes = $sub->get_notes();                  my $notes = $sub->get_notes();
909                  $loadSubsystem->Put($subsysID, $curator, $notes);                  my $version = $sub->get_version();
910                  my $class = $fig->subsystem_classification($subsysID);                  my $description = $sub->get_description();
911                  if ($class) {                  $loadSubsystem->Put($subsysID, $curator, $version, $description, $notes);
912                      $loadSubsystemClass->Put($subsysID, $class);                  # Add the hope notes.
913                  }                  my $hopeNotes = $sub->get_hope_curation_notes();
914                    if ($hopeNotes) {
915                        $loadSubsystemHopeNotes->Put($sub, $hopeNotes);
916                    }
917                    # Now for the classification string. This comes back as a list
918                    # reference and we convert it to a space-delimited string.
919                    my $classList = $fig->subsystem_classification($subsysID);
920                    my $classString = join($FIG_Config::splitter, grep { $_ } @$classList);
921                    $loadSubsystemClass->Put($subsysID, $classString);
922                  # 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.
923                  for (my $col = 0; defined($roleID = $sub->get_role($col)); $col++) {                  for (my $col = 0; defined($roleID = $sub->get_role($col)); $col++) {
924                        # Get the role's abbreviation.
925                        my $abbr = $sub->get_role_abbr($col);
926                        # Get its essentiality.
927                        my $aux = $fig->is_aux_role_in_subsystem($subsysID, $roleID);
928                        # Get its reaction note.
929                        my $hope_note = $sub->get_hope_reaction_notes($roleID) || "";
930                      # Connect to this role.                      # Connect to this role.
931                      $loadOccursInSubsystem->Add("roleIn");                      $loadOccursInSubsystem->Add("roleIn");
932                      $loadOccursInSubsystem->Put($roleID, $subsysID, $col);                      $loadOccursInSubsystem->Put($roleID, $subsysID, $abbr, $aux, $col, $hope_note);
933                      # If it's a new role, add it to the role table.                      # If it's a new role, add it to the role table.
934                      if (! exists $roleData{$roleID}) {                      if (! exists $roleData{$roleID}) {
935                          # Get the role's abbreviation.                          # Get the role's abbreviation.
                         my $abbr = $sub->get_role_abbr($col);  
936                          # Add the role.                          # Add the role.
937                          $loadRole->Put($roleID, $abbr);                          $loadRole->Put($roleID);
938                          $roleData{$roleID} = 1;                          $roleData{$roleID} = 1;
939                          # Check for an EC number.                          # Check for an EC number.
940                          if ($roleID =~ /\(EC ([^.]+\.[^.]+\.[^.]+\.[^)]+)\)\s*$/) {                          if ($roleID =~ /\(EC (\d+\.\d+\.\d+\.\d+)\s*\)\s*$/) {
941                              my $ec = $1;                              my $ec = $1;
942                              $loadRoleEC->Put($roleID, $ec);                              $loadIsIdentifiedByEC->Put($roleID, $ec);
943                              $ecToRoles{$ec} = $roleID;                              # Check to see if this is our first encounter with this EC.
944                                if (exists $ecToRoles{$ec}) {
945                                    # No, so just add this role to the EC list.
946                                    push @{$ecToRoles{$ec}}, $roleID;
947                                } else {
948                                    # Output this EC.
949                                    $loadRoleEC->Put($ec);
950                                    # Create its role list.
951                                    $ecToRoles{$ec} = [$roleID];
952                                }
953                          }                          }
954                      }                      }
955                  }                  }
# Line 871  Line 1062 
1062              # Now we need to link all the map's roles to it.              # Now we need to link all the map's roles to it.
1063              # A hash is used to prevent duplicates.              # A hash is used to prevent duplicates.
1064              my %roleHash = ();              my %roleHash = ();
1065              for my $role ($fig->map_to_ecs($map)) {              for my $ec ($fig->map_to_ecs($map)) {
1066                  if (exists $ecToRoles{$role} && ! $roleHash{$role}) {                  if (exists $ecToRoles{$ec}) {
1067                      $loadRoleOccursIn->Put($ecToRoles{$role}, $map);                      for my $role (@{$ecToRoles{$ec}}) {
1068                            if (! $roleHash{$role}) {
1069                                $loadRoleOccursIn->Put($role, $map);
1070                      $roleHash{$role} = 1;                      $roleHash{$role} = 1;
1071                  }                  }
1072              }              }
1073          }          }
         # Before we leave, we must create the Catalyzes table. We start with the reactions,  
         # then use the "ecToRoles" table to convert EC numbers to role IDs.  
         my @reactions = $fig->all_reactions();  
         for my $reactionID (@reactions) {  
             # Get this reaction's list of roles. The results will be EC numbers.  
             my @roles = $fig->catalyzed_by($reactionID);  
             # Loop through the roles, creating catalyzation records.  
             for my $thisRole (@roles) {  
                 if (exists $ecToRoles{$thisRole}) {  
                     $loadCatalyzes->Put($ecToRoles{$thisRole}, $reactionID);  
                 }  
1074              }              }
1075          }          }
1076      }      }
# Line 899  Line 1081 
1081    
1082  =head3 LoadPropertyData  =head3 LoadPropertyData
1083    
1084  C<< my $stats = $spl->LoadPropertyData(); >>      my $stats = $spl->LoadPropertyData();
1085    
1086  Load the attribute data from FIG into Sprout.  Load the attribute data from FIG into Sprout.
1087    
# Line 935  Line 1117 
1117      my $genomeHash = $self->{genomes};      my $genomeHash = $self->{genomes};
1118      # Create load objects for each of the tables we're loading.      # Create load objects for each of the tables we're loading.
1119      my $loadProperty = $self->_TableLoader('Property');      my $loadProperty = $self->_TableLoader('Property');
1120      my $loadHasProperty = $self->_TableLoader('HasProperty', $self->PrimaryOnly);      my $loadHasProperty = $self->_TableLoader('HasProperty');
1121      if ($self->{options}->{loadOnly}) {      if ($self->{options}->{loadOnly}) {
1122          Trace("Loading from existing files.") if T(2);          Trace("Loading from existing files.") if T(2);
1123      } else {      } else {
# Line 943  Line 1125 
1125          # Create a hash for storing property IDs.          # Create a hash for storing property IDs.
1126          my %propertyKeys = ();          my %propertyKeys = ();
1127          my $nextID = 1;          my $nextID = 1;
1128            # Get the attributes we intend to store in the property table.
1129            my $propKeys = $self->{propKeys};
1130          # Loop through the genomes.          # Loop through the genomes.
1131          for my $genomeID (keys %{$genomeHash}) {          for my $genomeID (sort keys %{$genomeHash}) {
1132              $loadProperty->Add("genomeIn");              $loadProperty->Add("genomeIn");
1133              Trace("Generating properties for $genomeID.") if T(3);              Trace("Generating properties for $genomeID.") if T(3);
1134              # 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;  
1135              my $propertyCount = 0;              my $propertyCount = 0;
1136              # Loop through the features, creating HasProperty records.              # Get the properties for this genome's features.
1137              for my $fid (@features) {              my @attributes = $fig->get_attributes("fig|$genomeID%", $propKeys);
1138                  # Get all attributes for this feature. We do this one feature at a time              Trace("Property list built for $genomeID.") if T(3);
1139                  # to insure we do not get any genome attributes.              # Loop through the results, creating HasProperty records.
1140                  my @attributeList = $fig->get_attributes($fid, '', '', '');              for my $attributeData (@attributes) {
1141                  if (scalar @attributeList) {                  # Pull apart the attribute tuple.
1142                      $featureCount++;                  my ($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};  
1143                      # Concatenate the key and value and check the "propertyKeys" hash to                      # Concatenate the key and value and check the "propertyKeys" hash to
1144                      # 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
1145                      # character.                      # character.
# Line 984  Line 1157 
1157                      # Create the HasProperty entry for this feature/property association.                      # Create the HasProperty entry for this feature/property association.
1158                      $loadHasProperty->Put($fid, $propertyID, $url);                      $loadHasProperty->Put($fid, $propertyID, $url);
1159                  }                  }
             }  
1160              # Update the statistics.              # Update the statistics.
1161              Trace("$propertyCount attributes processed for $featureCount features.") if T(3);              Trace("$propertyCount attributes processed.") if T(3);
             $loadHasProperty->Add("featuresIn", $featureCount);  
1162              $loadHasProperty->Add("propertiesIn", $propertyCount);              $loadHasProperty->Add("propertiesIn", $propertyCount);
1163          }          }
1164      }      }
# Line 998  Line 1169 
1169    
1170  =head3 LoadAnnotationData  =head3 LoadAnnotationData
1171    
1172  C<< my $stats = $spl->LoadAnnotationData(); >>      my $stats = $spl->LoadAnnotationData();
1173    
1174  Load the annotation data from FIG into Sprout.  Load the annotation data from FIG into Sprout.
1175    
# Line 1032  Line 1203 
1203      my $genomeHash = $self->{genomes};      my $genomeHash = $self->{genomes};
1204      # Create load objects for each of the tables we're loading.      # Create load objects for each of the tables we're loading.
1205      my $loadAnnotation = $self->_TableLoader('Annotation');      my $loadAnnotation = $self->_TableLoader('Annotation');
1206      my $loadIsTargetOfAnnotation = $self->_TableLoader('IsTargetOfAnnotation', $self->PrimaryOnly);      my $loadIsTargetOfAnnotation = $self->_TableLoader('IsTargetOfAnnotation');
1207      my $loadSproutUser = $self->_TableLoader('SproutUser', $self->PrimaryOnly);      my $loadSproutUser = $self->_TableLoader('SproutUser');
1208      my $loadUserAccess = $self->_TableLoader('UserAccess', $self->PrimaryOnly);      my $loadUserAccess = $self->_TableLoader('UserAccess');
1209      my $loadMadeAnnotation = $self->_TableLoader('MadeAnnotation', $self->PrimaryOnly);      my $loadMadeAnnotation = $self->_TableLoader('MadeAnnotation');
1210      if ($self->{options}->{loadOnly}) {      if ($self->{options}->{loadOnly}) {
1211          Trace("Loading from existing files.") if T(2);          Trace("Loading from existing files.") if T(2);
1212      } else {      } else {
# Line 1105  Line 1276 
1276    
1277  =head3 LoadSourceData  =head3 LoadSourceData
1278    
1279  C<< my $stats = $spl->LoadSourceData(); >>      my $stats = $spl->LoadSourceData();
1280    
1281  Load the source data from FIG into Sprout.  Load the source data from FIG into Sprout.
1282    
# Line 1139  Line 1310 
1310      # Get the genome hash.      # Get the genome hash.
1311      my $genomeHash = $self->{genomes};      my $genomeHash = $self->{genomes};
1312      # Create load objects for each of the tables we're loading.      # Create load objects for each of the tables we're loading.
1313      my $loadComesFrom = $self->_TableLoader('ComesFrom', $self->PrimaryOnly);      my $loadComesFrom = $self->_TableLoader('ComesFrom');
1314      my $loadSource = $self->_TableLoader('Source');      my $loadSource = $self->_TableLoader('Source');
1315      my $loadSourceURL = $self->_TableLoader('SourceURL');      my $loadSourceURL = $self->_TableLoader('SourceURL');
1316      if ($self->{options}->{loadOnly}) {      if ($self->{options}->{loadOnly}) {
# Line 1183  Line 1354 
1354    
1355  =head3 LoadExternalData  =head3 LoadExternalData
1356    
1357  C<< my $stats = $spl->LoadExternalData(); >>      my $stats = $spl->LoadExternalData();
1358    
1359  Load the external data from FIG into Sprout.  Load the external data from FIG into Sprout.
1360    
# Line 1263  Line 1434 
1434    
1435  =head3 LoadReactionData  =head3 LoadReactionData
1436    
1437  C<< my $stats = $spl->LoadReactionData(); >>      my $stats = $spl->LoadReactionData();
1438    
1439  Load the reaction data from FIG into Sprout.  Load the reaction data from FIG into Sprout.
1440    
# Line 1276  Line 1447 
1447      Compound      Compound
1448      CompoundName      CompoundName
1449      CompoundCAS      CompoundCAS
1450        IsIdentifiedByCAS
1451        HasCompoundName
1452      IsAComponentOf      IsAComponentOf
1453        Scenario
1454        Catalyzes
1455        HasScenario
1456        IsInputFor
1457        IsOutputOf
1458        ExcludesReaction
1459        IncludesReaction
1460        IsOnDiagram
1461        IncludesReaction
1462    
1463  This method proceeds reaction by reaction rather than genome by genome.  This method proceeds reaction by reaction rather than genome by genome.
1464    
# Line 1297  Line 1479 
1479      my $fig = $self->{fig};      my $fig = $self->{fig};
1480      # Create load objects for each of the tables we're loading.      # Create load objects for each of the tables we're loading.
1481      my $loadReaction = $self->_TableLoader('Reaction');      my $loadReaction = $self->_TableLoader('Reaction');
1482      my $loadReactionURL = $self->_TableLoader('ReactionURL', $self->PrimaryOnly);      my $loadReactionURL = $self->_TableLoader('ReactionURL');
1483      my $loadCompound = $self->_TableLoader('Compound', $self->PrimaryOnly);      my $loadCompound = $self->_TableLoader('Compound');
1484      my $loadCompoundName = $self->_TableLoader('CompoundName', $self->PrimaryOnly);      my $loadCompoundName = $self->_TableLoader('CompoundName');
1485      my $loadCompoundCAS = $self->_TableLoader('CompoundCAS', $self->PrimaryOnly);      my $loadCompoundCAS = $self->_TableLoader('CompoundCAS');
1486      my $loadIsAComponentOf = $self->_TableLoader('IsAComponentOf', $self->PrimaryOnly);      my $loadIsAComponentOf = $self->_TableLoader('IsAComponentOf');
1487        my $loadIsIdentifiedByCAS = $self->_TableLoader('IsIdentifiedByCAS');
1488        my $loadHasCompoundName = $self->_TableLoader('HasCompoundName');
1489        my $loadScenario = $self->_TableLoader('Scenario');
1490        my $loadHasScenario = $self->_TableLoader('HasScenario');
1491        my $loadIsInputFor = $self->_TableLoader('IsInputFor');
1492        my $loadIsOutputOf = $self->_TableLoader('IsOutputOf');
1493        my $loadIsOnDiagram = $self->_TableLoader('IsOnDiagram');
1494        my $loadIncludesReaction = $self->_TableLoader('IncludesReaction');
1495        my $loadExcludesReaction = $self->_TableLoader('ExcludesReaction');
1496        my $loadCatalyzes = $self->_TableLoader('Catalyzes');
1497      if ($self->{options}->{loadOnly}) {      if ($self->{options}->{loadOnly}) {
1498          Trace("Loading from existing files.") if T(2);          Trace("Loading from existing files.") if T(2);
1499      } else {      } else {
1500          Trace("Generating annotation data.") if T(2);          Trace("Generating reaction data.") if T(2);
1501            # We need some hashes to prevent duplicates.
1502            my %compoundNames = ();
1503            my %compoundCASes = ();
1504          # First we create the compounds.          # First we create the compounds.
1505          my @compounds = $fig->all_compounds();          my %compounds = map { $_ => 1 } $fig->all_compounds();
1506          for my $cid (@compounds) {          for my $cid (keys %compounds) {
1507              # Check for names.              # Check for names.
1508              my @names = $fig->names_of_compound($cid);              my @names = $fig->names_of_compound($cid);
1509              # Each name will be given a priority number, starting with 1.              # Each name will be given a priority number, starting with 1.
1510              my $prio = 1;              my $prio = 1;
1511              for my $name (@names) {              for my $name (@names) {
1512                  $loadCompoundName->Put($cid, $name, $prio++);                  if (! exists $compoundNames{$name}) {
1513                        $loadCompoundName->Put($name);
1514                        $compoundNames{$name} = 1;
1515                    }
1516                    $loadHasCompoundName->Put($cid, $name, $prio++);
1517              }              }
1518              # Create the main compound record. Note that the first name              # Create the main compound record. Note that the first name
1519              # becomes the label.              # becomes the label.
# Line 1323  Line 1522 
1522              # Check for a CAS ID.              # Check for a CAS ID.
1523              my $cas = $fig->cas($cid);              my $cas = $fig->cas($cid);
1524              if ($cas) {              if ($cas) {
1525                  $loadCompoundCAS->Put($cid, $cas);                  $loadIsIdentifiedByCAS->Put($cid, $cas);
1526                    if (! exists $compoundCASes{$cas}) {
1527                        $loadCompoundCAS->Put($cas);
1528                        $compoundCASes{$cas} = 1;
1529                    }
1530              }              }
1531          }          }
1532          # 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,
1533          # we initialize the discriminator index. This is a single integer used to insure          # we initialize the discriminator index. This is a single integer used to insure
1534          # duplicate elements in a reaction are not accidentally collapsed.          # duplicate elements in a reaction are not accidentally collapsed.
1535          my $discrim = 0;          my $discrim = 0;
1536          my @reactions = $fig->all_reactions();          my %reactions = map { $_ => 1 } $fig->all_reactions();
1537          for my $reactionID (@reactions) {          for my $reactionID (keys %reactions) {
1538              # Create the reaction record.              # Create the reaction record.
1539              $loadReaction->Put($reactionID, $fig->reversible($reactionID));              $loadReaction->Put($reactionID, $fig->reversible($reactionID));
1540              # Compute the reaction's URL.              # Compute the reaction's URL.
# Line 1354  Line 1557 
1557                  }                  }
1558              }              }
1559          }          }
1560            # Now we run through the subsystems and roles, generating the scenarios
1561            # and connecting the reactions. We'll need some hashes to prevent
1562            # duplicates and a counter for compound group keys.
1563            my %roles = ();
1564            my %scenarios = ();
1565            my @subsystems = $fig->all_subsystems();
1566            for my $subName (@subsystems) {
1567                my $sub = $fig->get_subsystem($subName);
1568                Trace("Processing $subName reactions.") if T(3);
1569                # Get the subsystem's reactions.
1570                my %reactions = $sub->get_hope_reactions();
1571                # Loop through the roles, connecting them to the reactions.
1572                for my $role (keys %reactions) {
1573                    # Only process this role if it is new.
1574                    if (! $roles{$role}) {
1575                        $roles{$role} = 1;
1576                        my @reactions = @{$reactions{$role}};
1577                        for my $reaction (@reactions) {
1578                            $loadCatalyzes->Put($role, $reaction);
1579                        }
1580                    }
1581                }
1582                Trace("Processing $subName scenarios.") if T(3);
1583                # Get the subsystem's scenarios.
1584                my @scenarioNames = $sub->get_hope_scenario_names();
1585                # Loop through the scenarios, creating scenario data.
1586                for my $scenarioName (@scenarioNames) {
1587                    # Link this scenario to this subsystem.
1588                    $loadHasScenario->Put($subName, $scenarioName);
1589                    # If this scenario is new, we need to create it.
1590                    if (! $scenarios{$scenarioName}) {
1591                        Trace("Creating scenario $scenarioName.") if T(3);
1592                        $scenarios{$scenarioName} = 1;
1593                        # Create the scenario itself.
1594                        $loadScenario->Put($scenarioName);
1595                        # Attach the input compounds.
1596                        for my $input ($sub->get_hope_input_compounds($scenarioName)) {
1597                            $loadIsInputFor->Put($input, $scenarioName);
1598                        }
1599                        # Now we need to set up the output compounds. They come in two
1600                        # groups, which we mark 0 and 1.
1601                        my $outputGroup = 0;
1602                        # Set up the output compounds.
1603                        for my $outputGroup ($sub->get_hope_output_compounds($scenarioName)) {
1604                            # Attach the compounds.
1605                            for my $compound (@$outputGroup) {
1606                                $loadIsOutputOf->Put($scenarioName, $compound, $outputGroup);
1607                            }
1608                        }
1609                        # Create the reaction lists.
1610                        my @addReactions = $sub->get_hope_additional_reactions($scenarioName);
1611                        for my $reaction (@addReactions) {
1612                            $loadIncludesReaction->Put($scenarioName, $reaction);
1613                        }
1614                        my @notReactions = $sub->get_hope_ignore_reactions($scenarioName);
1615                        for my $reaction (@notReactions) {
1616                            $loadExcludesReaction->Put($scenarioName, $reaction);
1617                        }
1618                        # Link the maps.
1619                        my @maps = $sub->get_hope_map_ids($scenarioName);
1620                        for my $map (@maps) {
1621                            $loadIsOnDiagram->Put($scenarioName, "map$map");
1622      }      }
     # Finish the load.  
     my $retVal = $self->_FinishAll();  
     return $retVal;  
1623  }  }
   
 =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);  
1624              }              }
             close TMP;  
1625          }          }
1626      }      }
1627      # Finish the load.      # Finish the load.
# Line 1419  Line 1631 
1631    
1632  =head3 LoadSynonymData  =head3 LoadSynonymData
1633    
1634  C<< my $stats = $spl->LoadSynonymData(); >>      my $stats = $spl->LoadSynonymData();
1635    
1636  Load the synonym groups into Sprout.  Load the synonym groups into Sprout.
1637    
# Line 1458  Line 1670 
1670          Trace("Generating synonym group data.") if T(2);          Trace("Generating synonym group data.") if T(2);
1671          # Get the database handle.          # Get the database handle.
1672          my $dbh = $fig->db_handle();          my $dbh = $fig->db_handle();
1673          # 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.
1674          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");
1675          my $result = $sth->execute();          my $result = $sth->execute();
1676          if (! defined($result)) {          if (! defined($result)) {
1677              Confess("Database error in Synonym load: " . $sth->errstr());              Confess("Database error in Synonym load: " . $sth->errstr());
1678          } else {          } else {
1679                Trace("Processing synonym results.") if T(2);
1680              # Remember the current synonym.              # Remember the current synonym.
1681              my $current_syn = "";              my $current_syn = "";
1682              # Count the features.              # Count the features.
1683              my $featureCount = 0;              my $featureCount = 0;
1684                my $entryCount = 0;
1685              # Loop through the synonym/peg pairs.              # Loop through the synonym/peg pairs.
1686              while (my @row = $sth->fetchrow()) {              while (my @row = $sth->fetchrow()) {
1687                  # Get the synonym ID and feature ID.                  # Get the synonym group ID and feature ID.
1688                  my ($syn_id, $peg) = @row;                  my ($syn_id, $peg) = @row;
1689                    # Count this row.
1690                    $entryCount++;
1691                    if ($entryCount % 1000 == 0) {
1692                        Trace("$entryCount rows processed.") if T(3);
1693                    }
1694                  # Insure it's for one of our genomes.                  # Insure it's for one of our genomes.
1695                  my $genomeID = FIG::genome_of($peg);                  my $genomeID = FIG::genome_of($peg);
1696                  if (exists $genomeHash->{$genomeID}) {                  if (exists $genomeHash->{$genomeID}) {
# Line 1490  Line 1709 
1709                      }                      }
1710                  }                  }
1711              }              }
1712                Trace("$entryCount rows produced $featureCount features.") if T(2);
1713          }          }
1714      }      }
1715      # Finish the load.      # Finish the load.
# Line 1499  Line 1719 
1719    
1720  =head3 LoadFamilyData  =head3 LoadFamilyData
1721    
1722  C<< my $stats = $spl->LoadFamilyData(); >>      my $stats = $spl->LoadFamilyData();
1723    
1724  Load the protein families into Sprout.  Load the protein families into Sprout.
1725    
1726  The following relations are loaded by this method.  The following relations are loaded by this method.
1727    
1728      Family      Family
1729      ContainsFeature      IsFamilyForFeature
1730    
1731  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>,
1732  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 1750 
1750      my $genomeHash = $self->{genomes};      my $genomeHash = $self->{genomes};
1751      # Create load objects for the tables we're loading.      # Create load objects for the tables we're loading.
1752      my $loadFamily = $self->_TableLoader('Family');      my $loadFamily = $self->_TableLoader('Family');
1753      my $loadContainsFeature = $self->_TableLoader('ContainsFeature');      my $loadIsFamilyForFeature = $self->_TableLoader('IsFamilyForFeature');
1754      if ($self->{options}->{loadOnly}) {      if ($self->{options}->{loadOnly}) {
1755          Trace("Loading from existing files.") if T(2);          Trace("Loading from existing files.") if T(2);
1756      } else {      } else {
# Line 1542  Line 1762 
1762              Trace("Processing features for $genomeID.") if T(2);              Trace("Processing features for $genomeID.") if T(2);
1763              # Loop through this genome's PEGs.              # Loop through this genome's PEGs.
1764              for my $fid ($fig->all_features($genomeID, "peg")) {              for my $fid ($fig->all_features($genomeID, "peg")) {
1765                  $loadContainsFeature->Add("features", 1);                  $loadIsFamilyForFeature->Add("features", 1);
1766                  # Get this feature's families.                  # Get this feature's families.
1767                  my @families = $fig->families_for_protein($fid);                  my @families = $fig->families_for_protein($fid);
1768                  # Loop through the families, connecting them to the feature.                  # Loop through the families, connecting them to the feature.
1769                  for my $family (@families) {                  for my $family (@families) {
1770                      $loadContainsFeature->Put($family, $fid);                      $loadIsFamilyForFeature->Put($family, $fid);
1771                      # If this is a new family, create a record for it.                      # If this is a new family, create a record for it.
1772                      if (! exists $familyHash{$family}) {                      if (! exists $familyHash{$family}) {
1773                            $familyHash{$family} = 1;
1774                          $loadFamily->Add("families", 1);                          $loadFamily->Add("families", 1);
1775                          my $size = $fig->sz_family($family);                          my $size = $fig->sz_family($family);
1776                          my $func = $fig->family_function($family);                          my $func = $fig->family_function($family);
# Line 1564  Line 1785 
1785      return $retVal;      return $retVal;
1786  }  }
1787    
1788    =head3 LoadDrugData
1789    
1790        my $stats = $spl->LoadDrugData();
1791    
1792    Load the drug target data into Sprout.
1793    
1794    The following relations are loaded by this method.
1795    
1796        PDB
1797        DocksWith
1798        IsProteinForFeature
1799        Ligand
1800    
1801    The source information for these relations is taken from attributes. The
1802    C<PDB> attribute links a PDB to a feature, and is used to build B<IsProteinForFeature>.
1803    The C<zinc_name> attribute describes the ligands. The C<docking_results>
1804    attribute contains the information for the B<DocksWith> relationship. It is
1805    expected that additional attributes and tables will be added in the future.
1806    
1807    =over 4
1808    
1809    =item RETURNS
1810    
1811    Returns a statistics object for the loads.
1812    
1813    =back
1814    
1815    =cut
1816    #: Return Type $%;
1817    sub LoadDrugData {
1818        # Get this object instance.
1819        my ($self) = @_;
1820        # Get the FIG object.
1821        my $fig = $self->{fig};
1822        # Get the genome hash.
1823        my $genomeHash = $self->{genomes};
1824        # Create load objects for the tables we're loading.
1825        my $loadPDB = $self->_TableLoader('PDB');
1826        my $loadLigand = $self->_TableLoader('Ligand');
1827        my $loadIsProteinForFeature = $self->_TableLoader('IsProteinForFeature');
1828        my $loadDocksWith = $self->_TableLoader('DocksWith');
1829        if ($self->{options}->{loadOnly}) {
1830            Trace("Loading from existing files.") if T(2);
1831        } else {
1832            Trace("Generating drug target data.") if T(2);
1833            # First comes the "DocksWith" relationship. This will give us a list of PDBs.
1834            # We can also encounter PDBs when we process "IsProteinForFeature". To manage
1835            # this process, PDB information is collected in a hash table and then
1836            # unspooled after both relationships are created.
1837            my %pdbHash = ();
1838            Trace("Generating docking data.") if T(2);
1839            # Get all the docking data. This may cause problems if there are too many PDBs,
1840            # at which point we'll need another algorithm. The indicator that this is
1841            # happening will be a timeout error in the next statement.
1842            my @dockData = $fig->query_attributes('$key = ? AND $value < ?',
1843                                                  ['docking_results', $FIG_Config::dockLimit]);
1844            Trace(scalar(@dockData) . " rows of docking data found.") if T(3);
1845            for my $dockData (@dockData) {
1846                # Get the docking data components.
1847                my ($pdbID, $docking_key, @valueData) = @{$dockData};
1848                # Fix the PDB ID. It's supposed to be lower-case, but this does not always happen.
1849                $pdbID = lc $pdbID;
1850                # Strip off the object type.
1851                $pdbID =~ s/pdb://;
1852                # Extract the ZINC ID from the docking key. Note that there are two possible
1853                # formats.
1854                my (undef, $zinc_id) = $docking_key =~ /^docking_results::(ZINC)?(\d+)$/;
1855                if (! $zinc_id) {
1856                    Trace("Invalid docking result key $docking_key for $pdbID.") if T(0);
1857                    $loadDocksWith->Add("errors");
1858                } else {
1859                    # Get the pieces of the value and parse the energy.
1860                    # Note that we don't care about the rank, since
1861                    # we can sort on the energy level itself in our database.
1862                    my ($energy, $tool, $type) = @valueData;
1863                    my ($rank, $total, $vanderwaals, $electrostatic) = split /\s*;\s*/, $energy;
1864                    # Ignore predicted results.
1865                    if ($type ne "Predicted") {
1866                        # Count this docking result.
1867                        if (! exists $pdbHash{$pdbID}) {
1868                            $pdbHash{$pdbID} = 1;
1869                        } else {
1870                            $pdbHash{$pdbID}++;
1871                        }
1872                        # Write the result to the output.
1873                        $loadDocksWith->Put($pdbID, $zinc_id, $electrostatic, $type, $tool,
1874                                            $total, $vanderwaals);
1875                    }
1876                }
1877            }
1878            Trace("Connecting features.") if T(2);
1879            # Loop through the genomes.
1880            for my $genome (sort keys %{$genomeHash}) {
1881                Trace("Generating PDBs for $genome.") if T(3);
1882                # Get all of the PDBs that BLAST against this genome's features.
1883                my @attributeData = $fig->get_attributes("fig|$genome%", 'PDB::%');
1884                for my $pdbData (@attributeData) {
1885                    # The PDB ID is coded as a subkey.
1886                    if ($pdbData->[1] !~ /PDB::(.+)/i) {
1887                        Trace("Invalid PDB ID \"$pdbData->[1]\" in attribute table.") if T(0);
1888                        $loadPDB->Add("errors");
1889                    } else {
1890                        my $pdbID = $1;
1891                        # Insure the PDB is in the hash.
1892                        if (! exists $pdbHash{$pdbID}) {
1893                            $pdbHash{$pdbID} = 0;
1894                        }
1895                        # The score and locations are coded in the attribute value.
1896                        if ($pdbData->[2] !~ /^([^;]+)(.*)$/) {
1897                            Trace("Invalid PDB data for $pdbID and feature $pdbData->[0].") if T(0);
1898                            $loadIsProteinForFeature->Add("errors");
1899                        } else {
1900                            my ($score, $locData) = ($1,$2);
1901                            # The location data may not be present, so we have to start with some
1902                            # defaults and then check.
1903                            my ($start, $end) = (1, 0);
1904                            if ($locData) {
1905                                $locData =~ /(\d+)-(\d+)/;
1906                                $start = $1;
1907                                $end = $2;
1908                            }
1909                            # If we still don't have the end location, compute it from
1910                            # the feature length.
1911                            if (! $end) {
1912                                # Most features have one location, but we do a list iteration
1913                                # just in case.
1914                                my @locations = $fig->feature_location($pdbData->[0]);
1915                                $end = 0;
1916                                for my $loc (@locations) {
1917                                    my $locObject = BasicLocation->new($loc);
1918                                    $end += $locObject->Length;
1919                                }
1920                            }
1921                            # Decode the score.
1922                            my $realScore = FIGRules::DecodeScore($score);
1923                            # Connect the PDB to the feature.
1924                            $loadIsProteinForFeature->Put($pdbID, $pdbData->[0], $start, $realScore, $end);
1925                        }
1926                    }
1927                }
1928            }
1929            # We've got all our PDBs now, so we unspool them from the hash.
1930            Trace("Generating PDBs. " . scalar(keys %pdbHash) . " found.") if T(2);
1931            my $count = 0;
1932            for my $pdbID (sort keys %pdbHash) {
1933                $loadPDB->Put($pdbID, $pdbHash{$pdbID});
1934                $count++;
1935                Trace("$count PDBs processed.") if T(3) && ($count % 500 == 0);
1936            }
1937            # Finally we create the ligand table. This information can be found in the
1938            # zinc_name attribute.
1939            Trace("Loading ligands.") if T(2);
1940            # The ligand list is huge, so we have to get it in pieces. We also have to check for duplicates.
1941            my $last_zinc_id = "";
1942            my $zinc_id = "";
1943            my $done = 0;
1944            while (! $done) {
1945                # Get the next 10000 ligands. We insist that the object ID is greater than
1946                # the last ID we processed.
1947                Trace("Loading batch starting with ZINC:$zinc_id.") if T(3);
1948                my @attributeData = $fig->query_attributes('$object > ? AND $key = ? ORDER BY $object LIMIT 10000',
1949                                                           ["ZINC:$zinc_id", "zinc_name"]);
1950                Trace(scalar(@attributeData) . " attribute rows returned.") if T(3);
1951                if (! @attributeData) {
1952                    # Here there are no attributes left, so we quit the loop.
1953                    $done = 1;
1954                } else {
1955                    # Process the attribute data we've received.
1956                    for my $zinc_data (@attributeData) {
1957                        # The ZINC ID is found in the first return column, prefixed with the word ZINC.
1958                        if ($zinc_data->[0] =~ /^ZINC:(\d+)$/) {
1959                            $zinc_id = $1;
1960                            # Check for a duplicate.
1961                            if ($zinc_id eq $last_zinc_id) {
1962                                $loadLigand->Add("duplicate");
1963                            } else {
1964                                # Here it's safe to output the ligand. The ligand name is the attribute value
1965                                # (third column in the row).
1966                                $loadLigand->Put($zinc_id, $zinc_data->[2]);
1967                                # Insure we don't try to add this ID again.
1968                                $last_zinc_id = $zinc_id;
1969                            }
1970                        } else {
1971                            Trace("Invalid zinc ID \"$zinc_data->[0]\" in attribute table.") if T(0);
1972                            $loadLigand->Add("errors");
1973                        }
1974                    }
1975                }
1976            }
1977            Trace("Ligands loaded.") if T(2);
1978        }
1979        # Finish the load.
1980        my $retVal = $self->_FinishAll();
1981        return $retVal;
1982    }
1983    
1984    
1985  =head2 Internal Utility Methods  =head2 Internal Utility Methods
1986    
1987    =head3 SpecialAttribute
1988    
1989        my $count = SproutLoad::SpecialAttribute($id, \@attributes, $idxMatch, \@idxValues, $pattern, $loader);
1990    
1991    Look for special attributes of a given type. A special attribute is found by comparing one of
1992    the columns of the incoming attribute list to a search pattern. If a match is found, then
1993    a set of columns is put into an output table connected to the specified ID.
1994    
1995    For example, when processing features, the attribute list we look at has three columns: attribute
1996    name, attribute value, and attribute value HTML. The IEDB attribute exists if the attribute name
1997    begins with C<iedb_>. The call signature is therefore
1998    
1999        my $found = SpecialAttribute($fid, \@attributeList, 0, [0,2], '^iedb_', $loadFeatureIEDB);
2000    
2001    The pattern is matched against column 0, and if we have a match, then column 2's value is put
2002    to the output along with the specified feature ID.
2003    
2004    =over 4
2005    
2006    =item id
2007    
2008    ID of the object whose special attributes are being loaded. This forms the first column of the
2009    output.
2010    
2011    =item attributes
2012    
2013    Reference to a list of tuples.
2014    
2015    =item idxMatch
2016    
2017    Index in each tuple of the column to be matched against the pattern. If the match is
2018    successful, an output record will be generated.
2019    
2020    =item idxValues
2021    
2022    Reference to a list containing the indexes in each tuple of the columns to be put as
2023    the second column of the output.
2024    
2025    =item pattern
2026    
2027    Pattern to be matched against the specified column. The match will be case-insensitive.
2028    
2029    =item loader
2030    
2031    An object to which each output record will be put. Usually this is an B<ERDBLoad> object,
2032    but technically it could be anything with a C<Put> method.
2033    
2034    =item RETURN
2035    
2036    Returns a count of the matches found.
2037    
2038    =item
2039    
2040    =back
2041    
2042    =cut
2043    
2044    sub SpecialAttribute {
2045        # Get the parameters.
2046        my ($id, $attributes, $idxMatch, $idxValues, $pattern, $loader) = @_;
2047        # Declare the return variable.
2048        my $retVal = 0;
2049        # Loop through the attribute rows.
2050        for my $row (@{$attributes}) {
2051            # Check for a match.
2052            if ($row->[$idxMatch] =~ m/$pattern/i) {
2053                # We have a match, so output a row. This is a bit tricky, since we may
2054                # be putting out multiple columns of data from the input.
2055                my $value = join(" ", map { $row->[$_] } @{$idxValues});
2056                $loader->Put($id, $value);
2057                $retVal++;
2058            }
2059        }
2060        Trace("$retVal special attributes found for $id and loader " . $loader->RelName() . ".") if T(4) && $retVal;
2061        # Return the number of matches.
2062        return $retVal;
2063    }
2064    
2065  =head3 TableLoader  =head3 TableLoader
2066    
2067  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 1580  Line 2076 
2076    
2077  Name of the table (relation) being loaded.  Name of the table (relation) being loaded.
2078    
 =item ignore  
   
 TRUE if the table should be ignored entirely, else FALSE.  
   
2079  =item RETURN  =item RETURN
2080    
2081  Returns an ERDBLoad object for loading the specified table.  Returns an ERDBLoad object for loading the specified table.
# Line 1594  Line 2086 
2086    
2087  sub _TableLoader {  sub _TableLoader {
2088      # Get the parameters.      # Get the parameters.
2089      my ($self, $tableName, $ignore) = @_;      my ($self, $tableName) = @_;
2090      # Create the load object.      # Create the load object.
2091      my $retVal = ERDBLoad->new($self->{erdb}, $tableName, $self->{loadDirectory}, $self->LoadOnly,      my $retVal = ERDBLoad->new($self->{erdb}, $tableName, $self->{loadDirectory}, $self->LoadOnly);
                                $ignore);  
2092      # Cache it in the loader list.      # Cache it in the loader list.
2093      push @{$self->{loaders}}, $retVal;      push @{$self->{loaders}}, $retVal;
2094      # Return it to the caller.      # Return it to the caller.
# Line 1669  Line 2160 
2160      return $retVal;      return $retVal;
2161  }  }
2162    
2163    =head3 GetGenomeAttributes
2164    
2165        my $aHashRef = GetGenomeAttributes($fig, $genomeID, \@fids, \@propKeys);
2166    
2167    Return a hash of attributes keyed on feature ID. This method gets all the NMPDR-related
2168    attributes for all the features of a genome in a single call, then organizes them into
2169    a hash.
2170    
2171    =over 4
2172    
2173    =item fig
2174    
2175    FIG-like object for accessing attributes.
2176    
2177    =item genomeID
2178    
2179    ID of the genome who's attributes are desired.
2180    
2181    =item fids
2182    
2183    Reference to a list of the feature IDs whose attributes are to be kept.
2184    
2185    =item propKeys
2186    
2187    A list of the keys to retrieve.
2188    
2189    =item RETURN
2190    
2191    Returns a reference to a hash. The key of the hash is the feature ID. The value is the
2192    reference to a list of the feature's attribute tuples. Each tuple contains the feature ID,
2193    the attribute key, and one or more attribute values.
2194    
2195    =back
2196    
2197    =cut
2198    
2199    sub GetGenomeAttributes {
2200        # Get the parameters.
2201        my ($fig, $genomeID, $fids, $propKeys) = @_;
2202        # Declare the return variable.
2203        my $retVal = {};
2204        # Initialize the hash. This not only enables us to easily determine which FIDs to
2205        # keep, it insures that the caller sees a list reference for every known fid,
2206        # simplifying the logic.
2207        for my $fid (@{$fids}) {
2208            $retVal->{$fid} = [];
2209        }
2210        # Get the attributes. If ev_code_cron is running, we may get a timeout error, so
2211        # an eval is used.
2212        my @aList = ();
2213        eval {
2214            @aList = $fig->get_attributes("fig|$genomeID%", $propKeys);
2215            Trace(scalar(@aList) . " attributes returned for genome $genomeID.") if T(3);
2216        };
2217        # Check for a problem.
2218        if ($@) {
2219            Trace("Retrying attributes for $genomeID due to error: $@") if T(1);
2220            # Our fallback plan is to process the attributes in blocks of 100. This is much slower,
2221            # but allows us to continue processing.
2222            my $nFids = scalar @{$fids};
2223            for (my $i = 0; $i < $nFids; $i += 100) {
2224                # Determine the index of the last feature ID we'll be specifying on this pass.
2225                # Normally it's $i + 99, but if we're close to the end it may be less.
2226                my $end = ($i + 100 > $nFids ? $nFids - 1 : $i + 99);
2227                # Get a slice of the fid list.
2228                my @slice = @{$fids}[$i .. $end];
2229                # Get the relevant attributes.
2230                Trace("Retrieving attributes for fids $i to $end.") if T(3);
2231                my @aShort = $fig->get_attributes(\@slice, $propKeys);
2232                Trace(scalar(@aShort) . " attributes returned for fids $i to $end.") if T(3);
2233                push @aList, @aShort;
2234            }
2235        }
2236        # Now we should have all the interesting attributes in @aList. Populate the hash with
2237        # them.
2238        for my $aListEntry (@aList) {
2239            my $fid = $aListEntry->[0];
2240            if (exists $retVal->{$fid}) {
2241                push @{$retVal->{$fid}}, $aListEntry;
2242            }
2243        }
2244        # Return the result.
2245        return $retVal;
2246    }
2247    
2248    =head3 GetCommaList
2249    
2250        my $string = GetCommaList($value);
2251    
2252    Create a comma-separated list of the values in a list reference. If the
2253    list reference is a scalar, it will be returned unchanged. If it is
2254    undefined, an empty string will be returned. The idea is that we may be
2255    looking at a string, a list, or nothing, but whatever comes out will be a
2256    string.
2257    
2258    =over 4
2259    
2260    =item value
2261    
2262    Reference to a list of values to be assembled into the return string.
2263    
2264    =item RETURN
2265    
2266    Returns a scalar string containing the content of the input value.
2267    
2268    =back
2269    
2270    =cut
2271    
2272    sub GetCommaList {
2273        # Get the parameters.
2274        my ($value) = @_;
2275        # Declare the return variable.
2276        my $retVal = "";
2277        # Only proceed if we have an input value.
2278        if (defined $value) {
2279            # Analyze the input value.
2280            if (ref $value eq 'ARRAY') {
2281                # Here it's a list reference.
2282                $retVal = join(", ", @$value);
2283            } else {
2284                # Here it's not. Flatten it to a scalar.
2285                $retVal = "$value";
2286            }
2287        }
2288        # Return the result.
2289        return $retVal;
2290    }
2291    
2292    
2293  1;  1;

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