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revision 1.9, Sat Dec 2 09:46:01 2006 UTC revision 1.13, Tue Apr 10 15:34:07 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
# Line 87  Line 94 
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      my $statistical = $cgi->param('statistical') || 1;      my $statistical = $cgi->param('statistical') || 1;
97        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.      # Now we build the table rows.
101      my @rows = ();      my @rows = ();
102      # First we have the given genome.      # First we have the given genome.
# Line 97  Line 107 
107                           $cgi->td({colspan => 2}, $targetMenu));                           $cgi->td({colspan => 2}, $targetMenu));
108      push @rows, $cgi->Tr($cgi->td({valign => "top"}, "Exclusion Genomes (Set 2)"),      push @rows, $cgi->Tr($cgi->td({valign => "top"}, "Exclusion Genomes (Set 2)"),
109                           $cgi->td({colspan => 2}, $excludeMenu));                           $cgi->td({colspan => 2}, $excludeMenu));
110      # Next, the numeric parameters.      # 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                  $cgi->Tr($cgi->td(), $cgi->td(                  $cgi->Tr($cgi->td(), $cgi->td(join(" ",
116                                    $cgi->checkbox(-name => 'statistical',                                    $cgi->checkbox(-name => 'statistical',
117                                                   -checked => $statistical,                                                   -checked => $statistical,
118                                                   -value => 1,                                                   -value => 1,
119                                                   -label => 'Use Statistical Algorithm')));                                                   -label => 'Use Statistical Algorithm'),
120      push @rows, $cgi->Tr($cgi->td("Cutoff"),                                    $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)));
# Line 143  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        $self->SetExtraPos(1);
172        # Create the timers.
173        my ($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 156  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 167  Line 199 
199              $targetGenomes{$givenGenomeID} = 1              $targetGenomes{$givenGenomeID} = 1
200          }          }
201          # Find out if we want to use a statistical analysis.          # Find out if we want to use a statistical analysis.
202          my $statistical = $cgi->param('statistical') || 0;          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            # 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          # Create a feature query object to loop through the chosen features of the given
253          # genome.          # genome.
254            Trace("Creating feature query.") if T(3);
255            $saveTime = time();
256          my $fquery = FeatureQuery->new($self, $givenGenomeID);          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.          # Get the sizes of the two sets. This information is useful in computing commonality.
259          my $targetSetSize = scalar keys %targetGenomes;          my $targetSetSize = scalar keys %targetGenomes;
260          my $exclusionSetSize = scalar keys %exclusionGenomes;          my $exclusionSetSize = scalar keys %exclusionGenomes;
261          # Loop through the features.          # Loop through the features.
262          while (my $record = $fquery->Fetch()) {          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.              # Get the feature's ID.
272              my $fid = $fquery->FID();              my $fid = $fquery->FID();
273              # Request its list of BBHs. The list is actually a hash mapping each BBH to its                  # Insure we want to look at this feature.
274                    if ($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.              # score. All we care about, however, are the BBHs themselves.
279              my %bbhList = $sprout->LowBBHs($fid, $cutoff);                      my $bbhList = $bbhMatrix{$fid};
280              # We next wish to loop through the BBH IDs, counting how many are in each of the              # 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              # 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.                      # 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 = ();              my %alreadySeen = ();
286              # Clear the counts.                      # Save the matching genes in here.
287              my ($targetCount, $exclusionCount) = (0, 0);                      my %genesMatching = ();
288              # Loop through the BBHs.                      # Clear the exclusion count.
289              for my $bbhPeg (keys %bbhList) {                      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.                  # Get the genome ID. We want to find out if this genome is new.
296                  my ($genomeID) = FIGRules::ParseFeatureID($bbhPeg);                  my ($genomeID) = FIGRules::ParseFeatureID($bbhPeg);
297                  if (! $alreadySeen{$genomeID}) {                          if (! exists $alreadySeen{$genomeID}) {
298                      # It's new, so we check to see which set it's in.                      # It's new, so we check to see which set it's in.
299                      if ($targetGenomes{$genomeID}) {                      if ($targetGenomes{$genomeID}) {
300                                    # It's in the target set.
301                          $targetCount++;                          $targetCount++;
302                                    $alreadySeen{$genomeID} = 1;
303                      } elsif ($exclusionGenomes{$genomeID}) {                      } elsif ($exclusionGenomes{$genomeID}) {
304                                    # It's in the exclusion set.
305                          $exclusionCount++;                          $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                      }                      }
                     # Make sure we don't look at it again.  
                     $alreadySeen{$genomeID} = 1;  
313                  }                  }
314              }              }
315              # Create a variable to indicate whether or not we want to keep this feature.                      # Create a variable to indicate whether or not we want to keep this feature and
316              my $okFlag;                      # another for the score.
317                        my ($okFlag, $score);
318              # We need to see if we're using statistics or not. This only matters              # We need to see if we're using statistics or not. This only matters
319              # for a two-set situation.              # for a two-set situation.
320              if ($statistical && $exclusionSetSize > 0) {              if ($statistical && $exclusionSetSize > 0) {
321                  # This looks like it has something to do with variance computations,                          # This is the magic formula for choosing the differentiating genes. It looks like
322                  # but I'm not sure.                          # it has something to do with variance computations, but I'm not sure.
323                  my $targetNotCount = $targetSetSize - $targetCount;                  my $targetNotCount = $targetSetSize - $targetCount;
324                  my $targetSquare = $targetCount * $targetCount + $targetNotCount * $targetNotCount;                  my $targetSquare = $targetCount * $targetCount + $targetNotCount * $targetNotCount;
325                  my $exclusionNotCount = $exclusionSetSize - $exclusionCount;                  my $exclusionNotCount = $exclusionSetSize - $exclusionCount;
# Line 219  Line 328 
328                  my $inD = 1 - (($exclusionSetSize * $mixed) / ($targetSetSize * $exclusionSquare));                  my $inD = 1 - (($exclusionSetSize * $mixed) / ($targetSetSize * $exclusionSquare));
329                  my $outD = 1 - (($targetSetSize * $mixed) / ($exclusionSetSize * $targetSquare));                  my $outD = 1 - (($targetSetSize * $mixed) / ($exclusionSetSize * $targetSquare));
330                  # If the two differentials are greater than one, we keep this feature.                  # If the two differentials are greater than one, we keep this feature.
331                  $okFlag = ($inD + $outD > 1);                          $score = $inD + $outD;
332                            $okFlag = ($score > 1);
333                            # Subtract 1 from the score so it looks like the commonality score.
334                            $score -= 1.0;
335              } else {              } else {
336                  # Check to see if we're common in set 1 and not in set 2.                  # Check to see if we're common in set 1 and not in set 2.
337                  if (IsCommon($targetCount, $targetSetSize, $commonality) &&                          my $score1 = IsCommon($targetCount, $targetSetSize, $commonality);
338                      ! IsCommon($exclusionCount, $exclusionSetSize, $commonality)) {                          my $score2 = IsCommon($exclusionCount, $exclusionSetSize, $commonality);
339                      # We satisfy the criterion, so we put this feature to the output.                          if ($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;                      $okFlag = 1;
344                  }                  }
345              }              }
346              if ($okFlag) {              if ($okFlag) {
347                  # Put this feature to the output.                          # 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);                  $self->PutFeature($fquery);
361                            $putTimer += time() - $saveTime;
362                  # Increase the result count.                  # Increase the result count.
363                  $retVal++;                  $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.          # Close the session file.
374            $saveTime = time();
375          $self->CloseSession();          $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 263  Line 402 
402    
403  =head3 IsCommon  =head3 IsCommon
404    
405  C<< my $flag = SHSigGenes::IsCommon($count, $size, $commonality); >>  C<< my $score = SHSigGenes::IsCommon($count, $size, $commonality); >>
406    
407  Return TRUE if a specified count indicates a gene is common in a specified set.  Return the match score if a specified count indicates a gene is common in a specified set
408  Commonality is computed by dividing the count by the size of the set and  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  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 FALSE.  if the set size is 0. In that case, this method always returns 0.
411    
412  =over 4  =over 4
413    
# Line 299  Line 438 
438      my $retVal = 0;      my $retVal = 0;
439      # Only procced if the size is positive.      # Only procced if the size is positive.
440      if ($size > 0) {      if ($size > 0) {
441          $retVal = ($count/$size >= $commonality);          # 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.      # Return the result.
449      return $retVal;      return $retVal;

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