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revision 1.3, Fri Sep 29 15:10:05 2006 UTC revision 1.14, Thu Apr 19 00:07:02 2007 UTC
# Line 8  Line 8 
8      use CGI;      use CGI;
9      use HTML;      use HTML;
10      use Sprout;      use Sprout;
11        use Time::HiRes;
12        use FIGRules;
13    
14      our @ISA = qw(SearchHelper);      our @ISA = qw(SearchHelper);
15    
# Line 55  Line 57 
57    
58  Maximum match difference for a BBH hit to be considered valid. The default is C<1e-10>.  Maximum match difference for a BBH hit to be considered valid. The default is C<1e-10>.
59    
60    =item showMatch
61    
62    If TRUE, then all the genes in the target set that match the ones in the reference genome
63    will be shown in an extra column.
64    
65  =back  =back
66    
67  =head2 Virtual Methods  =head2 Virtual Methods
68    
69  =head3 Form  =head3 Form
70    
71  C<< my $html = $shelp->Include(); >>  C<< my $html = $shelp->Form(); >>
72    
73  Generate the HTML for a form to request a new search.  Generate the HTML for a form to request a new search.
74    
# Line 80  Line 87 
87      # there is the selector for the given genome, the commonality and cutoff values,      # there is the selector for the given genome, the commonality and cutoff values,
88      # and the submit button. Our first task, then, is to get the genome selection      # and the submit button. Our first task, then, is to get the genome selection
89      # menus.      # menus.
90      my $givenMenu   = $self->NmpdrGenomeMenu('given', 0, [$cgi->param('genome')]);      my $givenMenu   = $self->NmpdrGenomeMenu('given', 0, [$cgi->param('given')]);
91      my $targetMenu  = $self->NmpdrGenomeMenu('target', 'multiple', [$cgi->param('target')]);      my $targetMenu  = $self->NmpdrGenomeMenu('target', 'multiple', [$cgi->param('target')], 10, 'exclusion');
92      my $excludeMenu = $self->NmpdrGenomeMenu('exclusion', 'multiple', [$cgi->param('exclusion')]);      my $excludeMenu = $self->NmpdrGenomeMenu('exclusion', 'multiple', [$cgi->param('exclusion')], 10, 'target');
93      # Get the default values to use for the commonality and cutoff controls.      # Get the default values to use for the commonality and cutoff controls.
94      my $commonality = $cgi->param('commonality') || "0.8";      my $commonality = $cgi->param('commonality') || "0.8";
95      my $cutoff = $cgi->param('cutoff') || "1e-10";      my $cutoff = $cgi->param('cutoff') || "1e-10";
96      # Now we build the table rows. The top contains the two numeric parameters and      my $statistical = $cgi->param('statistical') || 1;
97      # the submit button.      my $showMatch = $cgi->param('showMatch') || 0;
98        my $useSims = $cgi->param('useSims') || 0;
99        my $pegsOnly = $cgi->param('pegsOnly') || 1;
100        # Now we build the table rows.
101      my @rows = ();      my @rows = ();
102        # First we have the given genome.
103        push @rows, $cgi->Tr($cgi->td({valign => "top"}, "Reference Genome"),
104                             $cgi->td({colspan => 2}, $givenMenu));
105        # Now show the target and exclusion menus.
106        push @rows, $cgi->Tr($cgi->td({valign => "top"}, "Inclusion Genomes (Set 1)"),
107                             $cgi->td({colspan => 2}, $targetMenu));
108        push @rows, $cgi->Tr($cgi->td({valign => "top"}, "Exclusion Genomes (Set 2)"),
109                             $cgi->td({colspan => 2}, $excludeMenu));
110        # Next, the tuning parameters.
111      push @rows, $cgi->Tr($cgi->td("Commonality"),      push @rows, $cgi->Tr($cgi->td("Commonality"),
112                           $cgi->td($cgi->textfield(-name => 'commonality',                           $cgi->td($cgi->textfield(-name => 'commonality',
113                                                    -value => $commonality,                                                    -value => $commonality,
114                                                    -size => 5)));                                                    -size => 5))),
115      push @rows, $cgi->Tr($cgi->td("Cutoff"),                  $cgi->Tr($cgi->td(), $cgi->td(join(" ",
116                                      $cgi->checkbox(-name => 'statistical',
117                                                     -checked => $statistical,
118                                                     -value => 1,
119                                                     -label => 'Use Statistical Algorithm'),
120                                      $cgi->checkbox(-name => 'useSims',
121                                                     -checked => $useSims,
122                                                     -value => 1,
123                                                     -label => 'Use Similarities')))),
124                    $cgi->Tr($cgi->td(), $cgi->td(join(" ",
125                                      $cgi->checkbox(-name => 'showMatch',
126                                                     -checked => $showMatch,
127                                                     -value => 1,
128                                                     -label => 'Show Matching Genes'),
129    #                                  $cgi->checkbox(-name => 'pegsOnly',
130    #                                                 -checked => $pegsOnly,
131    #                                                 -value => 1,
132    #                                                 -label => 'PEGs Only')
133                                      ))),
134                    $cgi->Tr($cgi->td("Cutoff"),
135                           $cgi->td($cgi->textfield(-name => 'cutoff',                           $cgi->td($cgi->textfield(-name => 'cutoff',
136                                                    -value => $cutoff,                                                    -value => $cutoff,
137                                                    -size => 5)));                                                    -size => 5)));
138      push @rows, $self->SubmitRow();      # Next, the feature filter rows.
     # The next rows have the given genome and a feature filter.  
     push @rows, $cgi->Tr($cgi->td({valign => "top"}, "Given Genome"),  
                          $cgi->td({colspan => 2}, $givenMenu));  
139      push @rows, $self->FeatureFilterRows();      push @rows, $self->FeatureFilterRows();
140      # Now show the target and exclusion menus.      # Finally, the submit button.
141      push @rows, $cgi->Tr($cgi->td({valign => "top"}, "Target Genomes (Set 1)"),      push @rows, $self->SubmitRow();
                          $cgi->td({colspan => 2}, $targetMenu));  
     push @rows, $cgi->Tr($cgi->td({valign => "top"}, "Exclusion Genomes (Set 2)"),  
                          $cgi->td({colspan => 2}, $excludeMenu));  
142      # Create the table.      # Create the table.
143      $retVal .= $self->MakeTable(\@rows);      $retVal .= $self->MakeTable(\@rows);
144      # Close the form.      # Close the form.
# Line 135  Line 167 
167      # Declare the return variable. If it remains undefined, the caller will      # Declare the return variable. If it remains undefined, the caller will
168      # assume there was an error.      # assume there was an error.
169      my $retVal;      my $retVal;
170        # Denote the extra columns go at the end.
171        $self->SetExtraPos('score');
172        # Create the timers.
173        my ($saveTime, $loopCounter, $bbhTimer, $putTimer, $queryTimer) = (0, 0, 0, 0, 0);
174      # Validate the numeric parameters.      # Validate the numeric parameters.
175      my $commonality = $cgi->param('commonality');      my $commonality = $cgi->param('commonality');
176      my $cutoff = $cgi->param('cutoff');      my $cutoff = $cgi->param('cutoff');
177        my $pegsOnly = $cgi->param('pegsOnly') || 1;
178      if ($commonality !~ /^\s*\d(\.\d+)?\s*$/) {      if ($commonality !~ /^\s*\d(\.\d+)?\s*$/) {
179          $self->SetMessage("Commonality value appears invalid, too big, negative, or not a number.");          $self->SetMessage("Commonality value appears invalid, too big, negative, or not a number.");
180      } elsif ($commonality <= 0 || $commonality > 1) {      } elsif ($commonality <= 0 || $commonality > 1) {
# Line 148  Line 185 
185          $self->SetMessage("Cutoff cannot be greater than 1.");          $self->SetMessage("Cutoff cannot be greater than 1.");
186      } else {      } else {
187          # Now we need to gather and validate the genome sets.          # Now we need to gather and validate the genome sets.
188            $self->PrintLine("Gathering the target genomes.  ");
189          my ($givenGenomeID) = $self->GetGenomes('given');          my ($givenGenomeID) = $self->GetGenomes('given');
190          my %targetGenomes = map { $_ => 1 } $self->GetGenomes('target');          my %targetGenomes = map { $_ => 1 } $self->GetGenomes('target');
191            $self->PrintLine("Gathering the exclusion genomes.  ");
192          my %exclusionGenomes = map { $_ => 1 } $self->GetGenomes('exclusion');          my %exclusionGenomes = map { $_ => 1 } $self->GetGenomes('exclusion');
193            $self->PrintLine("Validating the genome sets.<br />");
194          # Insure the given genome is not in the exclusion set.          # Insure the given genome is not in the exclusion set.
195          if ($exclusionGenomes{$givenGenomeID}) {          if ($exclusionGenomes{$givenGenomeID}) {
196              $self->SetMessage("The given genome ($givenGenomeID) cannot be in the exclusion set.");              $self->SetMessage("The given genome ($givenGenomeID) cannot be in the exclusion set.");
# Line 158  Line 198 
198              # Insure the given genome is in the target set.              # Insure the given genome is in the target set.
199              $targetGenomes{$givenGenomeID} = 1              $targetGenomes{$givenGenomeID} = 1
200          }          }
201            # Find out if we want to use a statistical analysis.
202            my $statistical = $cgi->param('statistical') || 1;
203            # Find out if we need to show matching genes.
204            my $showMatch = $cgi->param('showMatch') || 0;
205          # Denote we have not yet found any genomes.          # Denote we have not yet found any genomes.
206          $retVal = 0;          $retVal = 0;
207          #TODO: find stuff          # Compute the list of genomes of interest.
208            my @allGenomes = (keys %exclusionGenomes, keys %targetGenomes);
209            # Set the parameter that indicates whether or not we're in PEGs-only mode.
210            my $pegMode = ($pegsOnly ? 'peg' : undef);
211            # Get the peg matrix.
212            Trace("Requesting matrix.") if T(3);
213            $saveTime = time();
214            my %bbhMatrix;
215            if (! $cgi->param('useSims')) {
216                # Here we are using BBHs, which are fast enough to do in one gulp.
217                $self->PrintLine("Requesting bidirectional best hits.  ");
218                %bbhMatrix = $sprout->BBHMatrix($givenGenomeID, $cutoff, @allGenomes);
219            } else {
220                # Here we are using similarities, which is much more complicated.
221                $self->PrintLine("Requesting similarities.<br />");
222                # Create a filtering matrix for the results. We only want to keep PEGs in the
223                # specified target and exclusion genomes.
224                my %keepGenomes = map { $_ => 1 } @allGenomes;
225                # Loop through the given genome's features.
226                my @features = $sprout->FeaturesOf($givenGenomeID, $pegMode);
227                for my $fid (@features) {
228                    $self->PrintLine("Retrieving similarities for $fid.  ");
229                    # Get this feature's similarities.
230                    my $simList = $sprout->Sims($fid, 1000, $cutoff, 'fig');
231                    my $simCount = scalar @{$simList};
232                    $self->PrintLine("Raw similarity count: $simCount.  ");
233                    # Create the matrix hash for this feature.
234                    $bbhMatrix{$fid} = {};
235                    # Now we need to filter out the similarities that don't land on the target genome.
236                    $simCount = 0;
237                    for my $sim (@{$simList}) {
238                        # Insure this similarity lands on a target genome.
239                        my ($genomeID2) = FIGRules::ParseFeatureID($sim->id2);
240                        if ($keepGenomes{$genomeID2}) {
241                            # Here we're keeping the similarity, so we put it in this feature's hash.
242                            $bbhMatrix{$fid}->{$sim->id2} = $sim->psc;
243                            $simCount++;
244                        }
245                    }
246                    $self->PrintLine("Similarities retained: $simCount.<br />");
247                }
248            }
249            $bbhTimer += time() - $saveTime;
250            $self->PrintLine("Time to build matrix: $bbhTimer seconds.<br />");
251            Trace("Matrix built.") if T(3);
252            # Create a feature query object to loop through the chosen features of the given
253            # genome.
254            Trace("Creating feature query.") if T(3);
255            $saveTime = time();
256            my $fquery = FeatureQuery->new($self, $givenGenomeID);
257            $queryTimer += time() - $saveTime;
258            # Get the sizes of the two sets. This information is useful in computing commonality.
259            my $targetSetSize = scalar keys %targetGenomes;
260            my $exclusionSetSize = scalar keys %exclusionGenomes;
261            # Loop through the features.
262            my $done = 0;
263            while (! $done) {
264                # Get the next feature.
265                $saveTime = time();
266                my $record = $fquery->Fetch();
267                $queryTimer += time() - $saveTime;
268                if (! $record) {
269                    $done = 1;
270                } else {
271                    # Get the feature's ID.
272                    my $fid = $fquery->FID();
273                    # Insure we want to look at this feature.
274                    if ($fid =~ /\.peg\./ || ! $pegsOnly) {
275                        Trace("Checking feature $fid.") if T(4);
276                        $self->PrintLine("Checking feature $fid.<br />");
277                        # Get its list of BBHs. The list is actually a hash mapping each BBH to its
278                        # score. All we care about, however, are the BBHs themselves.
279                        my $bbhList = $bbhMatrix{$fid};
280                        # We next wish to loop through the BBH IDs, counting how many are in each of the
281                        # sets. If a genome occurs twice, we only want to count the first occurrence, so
282                        # we have a hash of genomes we've already seen. The hash will map each gene ID
283                        # to 0, 1, or 2, depending on whether it was found in the reference genome,
284                        # a target genome, or an exclusion genome.
285                        my %alreadySeen = ();
286                        # Save the matching genes in here.
287                        my %genesMatching = ();
288                        # Clear the exclusion count.
289                        my $exclusionCount = 0;
290                        # Denote that we're in our own genome.
291                        $alreadySeen{$givenGenomeID} = 0;
292                        my $targetCount = 1;
293                        # Loop through the BBHs/Sims.
294                        for my $bbhPeg (keys %{$bbhList}) {
295                            # Get the genome ID. We want to find out if this genome is new.
296                            my ($genomeID) = FIGRules::ParseFeatureID($bbhPeg);
297                            if (! exists $alreadySeen{$genomeID}) {
298                                # It's new, so we check to see which set it's in.
299                                if ($targetGenomes{$genomeID}) {
300                                    # It's in the target set.
301                                    $targetCount++;
302                                    $alreadySeen{$genomeID} = 1;
303                                } elsif ($exclusionGenomes{$genomeID}) {
304                                    # It's in the exclusion set.
305                                    $exclusionCount++;
306                                    $alreadySeen{$genomeID} = 2;
307                                }
308                                # Note that $alreadySeen{$genomeID} exists in the hash by this
309                                # point. If it's 1, we need to save the current PEG.
310                                if ($alreadySeen{$genomeID} == 1) {
311                                    $genesMatching{$bbhPeg} = 1;
312                                }
313                            }
314                        }
315                        # Create a variable to indicate whether or not we want to keep this feature and
316                        # another for the score.
317                        my ($okFlag, $score);
318                        # We need to see if we're using statistics or not. This only matters
319                        # for a two-set situation.
320                        if ($statistical && $exclusionSetSize > 0) {
321                            # This is the magic formula for choosing the differentiating genes. It looks like
322                            # it has something to do with variance computations, but I'm not sure.
323                            my $targetNotCount = $targetSetSize - $targetCount;
324                            my $targetSquare = $targetCount * $targetCount + $targetNotCount * $targetNotCount;
325                            my $exclusionNotCount = $exclusionSetSize - $exclusionCount;
326                            my $exclusionSquare = $exclusionCount * $exclusionCount + $exclusionNotCount * $exclusionNotCount;
327                            my $mixed = $targetCount * $exclusionCount + $targetNotCount * $exclusionNotCount;
328                            my $inD = 1 - (($exclusionSetSize * $mixed) / ($targetSetSize * $exclusionSquare));
329                            my $outD = 1 - (($targetSetSize * $mixed) / ($exclusionSetSize * $targetSquare));
330                            # If the two differentials are greater than one, we keep this feature.
331                            $score = $inD + $outD;
332                            $okFlag = ($score > 1);
333                            # Subtract 1 from the score so it looks like the commonality score.
334                            $score -= 1.0;
335                        } else {
336                            # Check to see if we're common in set 1 and not in set 2.
337                            my $score1 = IsCommon($targetCount, $targetSetSize, $commonality);
338                            my $score2 = IsCommon($exclusionCount, $exclusionSetSize, $commonality);
339                            if ($score1 && ! $score2) {
340                                # We satisfy the criterion, so we put this feature to the output. The
341                                # score is essentially $score1, since $score2 is zero.
342                                $score = $score1;
343                                $okFlag = 1;
344                            }
345                        }
346                        if ($okFlag) {
347                            # Put this feature to the output. We have one or two extra columns.
348                            # First we store the score.
349                            $fquery->AddExtraColumns(score => sprintf("%.3f",$score));
350                            # Next we add the list of matching genes, but only if "showMatch" is specified.
351                            if ($showMatch) {
352                                # The matching genes are in the hash "genesMatching".
353                                my @genes = sort { FIGRules::FIGCompare($a,$b) } keys %genesMatching;
354                                # We need to linkify them.
355                                my $genesHTML = join(", ", map { HTML::fid_link($cgi, $_) } @genes);
356                                # Now add them as an extra column.
357                                $fquery->AddExtraColumns(matches => $genesHTML);
358                            }
359                            $saveTime = time();
360                            $self->PutFeature($fquery);
361                            $putTimer += time() - $saveTime;
362                            # Increase the result count.
363                            $retVal++;
364                        }
365                        # Check for a timer trace. We trace every 500 features.
366                        $loopCounter++;
367                        if (T(3) && $loopCounter % 500 == 0) {
368                            Trace("Time spent for $loopCounter features: Put = $putTimer, Query = $queryTimer, BBH = $bbhTimer.");
369                        }
370      }      }
371                }
372            }
373            # Close the session file.
374            $saveTime = time();
375            $self->CloseSession();
376            $putTimer += time() - $saveTime;
377        }
378        # Trace the timers.
379        Trace("Time spent: Put = $putTimer, Query = $queryTimer, BBH = $bbhTimer.") if T(3);
380      # Return the result count.      # Return the result count.
381      return $retVal;      return $retVal;
382  }  }
# Line 180  Line 395 
395      # Get the parameters.      # Get the parameters.
396      my ($self) = @_;      my ($self) = @_;
397      # Return the result.      # Return the result.
398      return "Search for features that are common to a group of organisms or that discriminate between two groups of organisms.";      return "Search for genes that are common to a group of organisms or that discriminate between two groups of organisms.";
399    }
400    
401    =head2 Internal Utilities
402    
403    =head3 IsCommon
404    
405    C<< my $score = SHSigGenes::IsCommon($count, $size, $commonality); >>
406    
407    Return the match score if a specified count indicates a gene is common in a specified set
408    and 0 otherwise. Commonality is computed by dividing the count by the size of the set and
409    comparing the result to the minimum commonality ratio. The one exception is
410    if the set size is 0. In that case, this method always returns 0.
411    
412    =over 4
413    
414    =item count
415    
416    Number of elements of the set that have the relevant characteristic.
417    
418    =item size
419    
420    Total number of elements in the set.
421    
422    =item commonality
423    
424    Minimum count/size ratio for the characteristic to be considered common.
425    
426    =item RETURN
427    
428    Returns TRUE if the characteristic is common, else FALSE.
429    
430    =back
431    
432    =cut
433    
434    sub IsCommon {
435        # Get the parameters.
436        my ($count, $size, $commonality) = @_;
437        # Declare the return variable.
438        my $retVal = 0;
439        # Only procced if the size is positive.
440        if ($size > 0) {
441            # Compute the commonality.
442            $retVal = $count/$size;
443            # If it's too small, clear it.
444            if ($retVal < $commonality) {
445                $retVal = 0;
446            }
447        }
448        # Return the result.
449        return $retVal;
450  }  }
451    
452  1;  1;

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