Fix mixup between strict and marginal thresholds of significance. Als…

…o fixes pink color on dChart

eForge/ePlot.pm

@@ -71,7 +71,7 @@ This is the original code using standard R plot to generate a static pdf.
 
 sub Chart{
     print "Making static chart.\n";
-    my ($filename, $lab, $resultsdir, $tissues, $cells, $label, $t1, $t2, $data) = @_;
+    my ($filename, $lab, $resultsdir, $tissues, $cells, $label, $t_marginal, $t_strict, $data) = @_;
     my $Rdir = $resultsdir;
     my $chart = "$lab.chart.pdf";
     my $rfile = "$Rdir/$lab.chart.R";
@@ -80,17 +80,17 @@ sub Chart{
 
 
     open my $rfh, ">", $rfile;
-#results\$Class<-cut(results\$Pvalue, breaks =c(min(results\$Pvalue), $t1, $t2, max(results\$Pvalue)), labels=FALSE, include.lowest=TRUE) # 99 and 95% CIs 1, 2, 3
-$t1 = sprintf("%.2f", $t1);
-$t2 = sprintf("%.2f", $t2);
+#results\$Class<-cut(results\$Pvalue, breaks =c(min(results\$Pvalue), $t_marginal, $t_strict, max(results\$Pvalue)), labels=FALSE, include.lowest=TRUE) # 99 and 95% CIs 1, 2, 3
+$t_marginal = sprintf("%.2f", $t_marginal);
+$t_strict = sprintf("%.2f", $t_strict);
     print $rfh "setwd('$Rdir')
 results<-read.table('$filename', header=TRUE,sep='\\t')
 
-# Class splits the data into non-significant, marginally significant and significant according to $t1 and $t2 (in -log10 scale)
-results\$Class <- cut(results\$Pvalue, breaks =c(0, $t2, $t1, 1)/length(unique(results[,'Tissue'])), labels=FALSE, include.lowest=TRUE)
+# Class splits the data into non-significant, marginally significant and significant according to $t_marginal and $t_strict (in -log10 scale)
+results\$Class <- cut(results\$Pvalue, breaks =c(0, $t_strict, $t_marginal, 1)/length(unique(results[,'Tissue'])), labels=FALSE, include.lowest=TRUE)
 
 # Class splits the data into non-significant, marginally significant and significant according to q-value (B-Y FDR adjusted)
-results\$Class2 <- cut(results\$Qvalue, breaks =c(0, $t2, $t1, 1), labels=FALSE, include.lowest=TRUE)
+results\$Class2 <- cut(results\$Qvalue, breaks =c(0, $t_strict, $t_marginal, 1), labels=FALSE, include.lowest=TRUE)
 
 # Re-order the entries according to tissue first and then cell type/line
 tissue.cell.order <- unique(results[, c('Tissue', 'Cell')])
@@ -131,11 +131,11 @@ mtext(2, text='-log10 binomial p-value', line=2, cex=1.4)
 
 # Add legend (internal color first)
 palette(c('white', '$msig', '$sig'))
-legend('topleft', pch=19, legend=c('q < $t2', 'q < $t1', 'non-sig'), col = 3:1, cex=0.8, inset=c(0.001, 0.005), box.col='white', title='FDR q-value', text.col='white', bg='white')
+legend('topleft', pch=19, legend=c('q < $t_strict', 'q < $t_marginal', 'non-sig'), col = 3:1, cex=0.8, inset=c(0.001, 0.005), box.col='white', title='FDR q-value', text.col='white', bg='white')
 
 # Add contour to the points in the legend
 palette(c('$ns', '$msig', 'black'))
-legend('topleft', pch=1, legend=c('q < $t2', 'q < $t1', 'non-sig'), col = 3:1, cex=0.8, inset=c(0.001, 0.005), box.col='darkgrey', title='FDR q-value')
+legend('topleft', pch=1, legend=c('q < $t_strict', 'q < $t_marginal', 'non-sig'), col = 3:1, cex=0.8, inset=c(0.001, 0.005), box.col='darkgrey', title='FDR q-value')
 
 palette('default')
 dev.off()
@@ -153,7 +153,7 @@ Make dimple interactive chart.
 =cut
 
 sub dChart{
-    my ($filename, $lab, $resultsdir, $data, $label, $t1, $t2, $web) = @_;
+    my ($filename, $lab, $resultsdir, $data, $label, $t_marginal, $t_strict, $web) = @_;
 
     print "Making dChart.\n";
     my $chart = "$lab.dchart.html";
@@ -163,19 +163,22 @@ sub dChart{
     print $rcfh "setwd(\"$Rdir\")
 results<-read.table(\"$filename\", header = TRUE, sep=\"\\t\")
 
-# Class splits the data into non-significant, marginally significant and significant according to $t1 and $t2 (in -log10 scale)
-results\$Class <- cut(results\$Pvalue, breaks =c(0, $t2, $t1, 1)/length(unique(results[,'Tissue'])), labels=FALSE, include.lowest=TRUE)
+# Class splits the data into non-significant, marginally significant and significant according to $t_marginal and $t_strict (in -log10 scale)
+results\$Class <- cut(results\$Pvalue, breaks =c(0, $t_strict, $t_marginal, 1)/length(unique(results[,'Tissue'])), labels=FALSE, include.lowest=TRUE)
 
 # Class splits the data into non-significant, marginally significant and significant according to q-value (B-Y FDR adjusted)
-results\$Class2 <- cut(results\$Qvalue, breaks =c(0, $t2, $t1, 1), labels=FALSE, include.lowest=TRUE)
+results\$Class2 <- cut(results\$Qvalue, breaks =c(0, $t_strict, $t_marginal, 1), labels=FALSE, include.lowest=TRUE)
 color.axis.palette = c();
 if (length(which(results\$Class2 == 1)) > 0 ) {
     color.axis.palette = c('red');
 }
 if (length(which(results\$Class2 == 2)) > 0 ) {
-    color.axis.palette = c(color.axis.palette, 'pink');
+    color.axis.palette = c(color.axis.palette, '#FF82ab');
+}
+color.axis.palette = c(color.axis.palette, 'lightblue');
+if (length(color.axis.palette) < 2) {
+    color.axis.palette = c(color.axis.palette, 'lightblue'); # Add it twice to force the color if only non-significant values
 }
-color.axis.palette = c(color.axis.palette, 'lightblue', 'lightblue'); # Add it twice to force the color if only non-significant values
 
 results\$log10pvalue <- -log10(results\$Pvalue)
 

eforge.pl

@@ -338,15 +338,18 @@ =head1 ACKNOWLEDGEMENTS
 
 
 # Define the thresholds to use.
-my ($t1, $t2);
+my ($t_marginal, $t_strict);
 if (defined $thresh) {
-    ($t1, $t2) = split(",", $thresh);
-    unless (looks_like_number($t1) && looks_like_number($t2)){
-        die "You must specify numerical p value thresholds in a comma separated list";
+    ($t_marginal, $t_strict) = split(",", $thresh);
+    unless (looks_like_number($t_marginal) && looks_like_number($t_strict)){
+        die "You must specify numerical p value thresholds in a comma separated list\n";
+    }
+    unless ((1 >= $t_marginal) && ($t_marginal >= $t_strict) && ($t_strict >= 0)) {
+        die "The p-value thresholds should be 1 >= T.marginal >= T.strict >= 0\n";
     }
 } else {
-    $t1 = 0.05; # set binomial p values, bonferroni is applied later based on number of samples (cells)
-    $t2 = 0.01;
+    $t_marginal = 0.05; # set binomial p values, bonferroni is applied later based on number of samples (cells)
+    $t_strict = 0.01;
 }
 
 # mvps need to come either from a file or a list
@@ -576,8 +579,8 @@ =head1 ACKNOWLEDGEMENTS
 warn "[".scalar(localtime())."] Generating plots...\n";
 unless (defined $noplot){
     #Plotting and table routines
-    Chart($filename, $lab, $out_dir, $tissues, $cells, $label, $t1, $t2, $data); # basic pdf plot
-    dChart($filename, $lab, $out_dir, $data, $label, $t1, $t2, $web); # rCharts Dimple chart
+    Chart($filename, $lab, $out_dir, $tissues, $cells, $label, $t_marginal, $t_strict, $data); # basic pdf plot
+    dChart($filename, $lab, $out_dir, $data, $label, $t_marginal, $t_strict, $web); # rCharts Dimple chart
     table($filename, $lab, $out_dir, $web); # Datatables chart
   }
 

webserver/cgi-bin/index.pl

@@ -277,10 +277,10 @@ sub print_form {
                 textfield('reps', '1000', 10)]),
             td(["Significance threshold:",
                 ""]),
-            td(["      Min:",
-                textfield('thresh1', '0.01', 10)]),
-            td(["      Max:",
-                textfield('thresh2', '0.05', 10)]),
+            td(["      Strict:",
+                textfield('thresh_strict', '0.01', 10)]),
+            td(["      Marginal:",
+                textfield('thresh_marginal', '0.05', 10)]),
 
             th({-colspan=>2}, ["<hr>"]),
 
@@ -393,27 +393,26 @@ sub validate_form {
     }
     push(@$validated_args, "--reps", $reps);
 
-    my $thresh1 = param("thresh1");
-    if (!$thresh1 or $thresh1 !~ /^\d+(\.\d*)?$/) {
-        push(@error_messages, "Min. significance threshold must be a positive number.");
-    } elsif ($thresh1 >= 1) {
-        push(@error_messages, "Min. significance threshold must be less than 1.");
+    my $thresh_strict = param("thresh_strict");
+    if (!$thresh_strict or $thresh_strict !~ /^\d+(\.\d*)?$/) {
+        push(@error_messages, "Strict significance threshold must be a positive number.");
+    } elsif ($thresh_strict >= 1) {
+        push(@error_messages, "Strict significance threshold must be less than 1.");
     }
 
-    my $thresh2 = param("thresh2");
-    if (!$thresh2 or $thresh2 !~ /^\d+(\.\d*)?$/) {
-        push(@error_messages, "Max. significance threshold must be a positive number.");
-    } elsif ($thresh2 >= 1) {
-        push(@error_messages, "Max. significance threshold must be less than 1.");
+    my $thresh_marginal = param("thresh_marginal");
+    if (!$thresh_marginal or $thresh_marginal !~ /^\d+(\.\d*)?$/) {
+        push(@error_messages, "Marginal significance threshold must be a positive number.");
+    } elsif ($thresh_marginal >= 1) {
+        push(@error_messages, "Marginal significance threshold must be less than 1.");
     }
 
-    if ($thresh1 > $thresh2) {
+    if ($thresh_strict > $thresh_marginal) {
         print $q->header;
-        push(@error_messages, "Min. significance threshold must be less than max. significance".
-            " threshold.");
+        push(@error_messages, "Strict significance threshold must be less than marginal one.");
         return 0;
     }
-    push(@$validated_args, "--thresh", "$thresh1,$thresh2");
+    push(@$validated_args, "--thresh", "$thresh_marginal,$thresh_strict");
 
     if (@error_messages) {
         print $q->header;
@@ -915,7 +914,7 @@ sub print_help_page {
            <br \>",
 
        "<strong>Significance threshold</strong><br \><br \>
-           Alter the default binomial p value thresholds. (0 < Min < Max < 1)
+           Alter the default binomial p value thresholds. (0 < Strict < Marginal < 1)
            <br \>",
     );