Merge pull request #169 from Roestlab/patch/plot_by_qvalue

Patch/plot by qvalue

massdash/loaders/GenericChromatogramLoader.py

@@ -86,8 +86,12 @@ def plotChromatogram(self,
         # load the transitionGroup for plotting
         transitionGroup = list(self.loadTransitionGroups(seq, charge, runNames=runName).values())[0]
         if includeBoundaries:
-            transitionGroupFeatures = self.loadTransitionGroupFeaturesDf(seq, charge)
+            transitionGroupFeatures = self.loadTransitionGroupFeaturesDf(seq, charge, runNames=runName)
         else:
             transitionGroupFeatures = None
 
+        # set title automatically (as peptide and charge state) if not set by user
+        if not 'title' in kwargs.keys():
+            kwargs['title'] = f"{seq}_{charge}"
+
         return super().plotChromatogram(transitionGroup, transitionGroupFeatures, include_ms1=include_ms1, smooth=smooth, sgolay_polynomial_order=sgolay_polynomial_order, sgolay_frame_length=sgolay_frame_length, **kwargs)

massdash/loaders/GenericRawDataLoader.py

@@ -59,6 +59,7 @@ def plotChromatogram(self,
                         gaussian_window: int = 11,
                         gaussian_sigma: float = 2,
                         width=800,
+                        allFeatures=True,
                         **kwargs) -> 'bokeh.plotting.figure.Figure':
         '''
         Plots a chromatogram for a transitionGroup and transitionGroupFeatures given peptide sequence and charge state for a given run
@@ -71,6 +72,7 @@ def plotChromatogram(self,
             sgolay_polynomial_order (int, optional): Order of the polynomial to use for smoothing. Defaults to 3.
             sgolay_frame_length (int, optional): Frame length to use for smoothing. Defaults to 11.
             scale_intensity (bool, optional): Whether to scale the intensity of the chromatogram such that all chromatograms are individually normalized to 1. Defaults to False.
+            allFeatures (bool, optional): Whether to plot all features or just the top ranked feature. Defaults to True.
 
         Returns: 
             bokeh.plotting.figure.Figure: Bokeh figure object
@@ -89,12 +91,23 @@ def plotChromatogram(self,
         # format transitionGroupFeatures for plotting with pyopenms_viz
         if transitionGroupFeatures is not None:
             transitionGroupFeatures.rename(columns={'leftBoundary':'leftWidth', 'rightBoundary':'rightWidth', 'consensusApexIntensity':'apexIntensity'}, inplace=True)
+
+            # sort by qvalue
+            transitionGroupFeatures = transitionGroupFeatures.sort_values(by='qvalue')
 
             # Determine the labels for the legend, this is dependent on software tool
             # if multiple software tools used, label by software
+
             labelBySoftware = transitionGroupFeatures['software'].nunique() > 1
             if transitionGroupFeatures.software is not None and labelBySoftware:
                 transitionGroupFeatures.rename(columns={'software':'name'}, inplace=True)
+                transitionGroupFeatures['name'] = transitionGroupFeatures['name'] + transitionGroupFeatures['qvalue'].map(lambda x: f' (qvalue={x:.2e})')
+            else: # if only one software tool used, label by q value
+                transitionGroupFeatures['name'] = transitionGroupFeatures['sequence'] + transitionGroupFeatures['qvalue'].map(lambda x: f' (qvalue={x:.2e})')
+                transitionGroupFeatures.rename(columns={'annotation':'name'}, inplace=True)
+
+            if not allFeatures:
+                transitionGroupFeatures = transitionGroupFeatures.head(1)
 
         def apply_smoothing(group):
             if smooth == 'savgol':
@@ -107,7 +120,6 @@ def apply_smoothing(group):
 
             return group
 
-
         to_plot = to_plot.groupby('annotation').apply(apply_smoothing).reset_index(drop=True)
 
         fig = to_plot.plot(x='rt', y='intensity', kind='chromatogram', by='annotation', backend='ms_bokeh', annotation_data=transitionGroupFeatures, width=width, show_plot=False, **kwargs) 

massdash/loaders/GenericSpectrumLoader.py

@@ -139,4 +139,8 @@ def plotChromatogram(self,
         else:
             transitionGroupFeatures = None
 
+        # set title automatically (as peptide and charge state) if not set by user
+        if not 'title' in kwargs.keys():
+            kwargs['title'] = f"{seq}_{charge}"
+
         return super().plotChromatogram(transitionGroup, transitionGroupFeatures, include_ms1=include_ms1, smooth=smooth, sgolay_polynomial_order=sgolay_polynomial_order, sgolay_frame_length=sgolay_frame_length, **kwargs)