SpatialTranscriptomicsResearch · jfnavarro · Nov 1, 2016 · Nov 1, 2016 · Nov 1, 2016 · Nov 1, 2016
diff --git a/scripts/differential_analysis.py b/scripts/differential_analysis.py
@@ -123,8 +123,9 @@ def main(input_data, data_classes, conditions_tuples, outdir):
         dea_results.to_csv(os.path.join(outdir, "dea_results_{}.tsv".format(cond)), sep="\t")
         # Volcano plot
         print "Generating plots..."
+        # TODO add colors according to differently expressed or not
         scatter_plot(dea_results["log2FoldChange"], -np.log10(dea_results["pvalue"]),
-                     xlabel="Log2FoldChange", ylabel="-log10(pvalue)", 
+                     xlabel="Log2FoldChange", ylabel="-log10(pvalue)", colors=None,
                      title="Volcano plot", output=os.path.join(outdir, "volcano_{}.png".format(cond)))
 
 if __name__ == '__main__':

diff --git a/scripts/unsupervised.py b/scripts/unsupervised.py
@@ -164,9 +164,9 @@ def main(counts_table_files,
     y_min = min(reduced_data[:,1])
     x_p = reduced_data[:,0]
     y_p = reduced_data[:,1]
-    z_p = y_p
+    z_p = None
     if num_dimensions == 3:
-        z_p = reduced_data[:,3]
+        z_p = reduced_data[:,2]
         z_max = max(reduced_data[:,2])
         z_min = min(reduced_data[:,2])
     for x,y,z in zip(x_p,y_p,z_p):

diff --git a/setup.py b/setup.py
@@ -16,7 +16,7 @@
 
 setup(
   name = 'stanalysis',
-  version = "0.2.0",
+  version = "0.2.1",
   description = __doc__.split("\n", 1)[0],
   long_description = long_description,
   keywords = 'rna-seq analysis spatial transcriptomics toolkit',

diff --git a/stanalysis/visualization.py b/stanalysis/visualization.py
@@ -48,8 +48,8 @@ def histogram(x_points, output, title="Histogram", xlabel="X",
     fig.set_size_inches(16, 16)
     fig.savefig(output, dpi=300)
 
-def scatter_plot3d(x_points, y_points, z_points, colors, 
-                   output, cmap=None, title='Scatter', xlabel='X', 
+def scatter_plot3d(x_points, y_points, z_points, output,
+                   colors=None, cmap=None, title='Scatter', xlabel='X', 
                    ylabel='Y', zlabel="Z", alpha=1.0, size=50):
     """ 
     This function makes a scatter 3d plot of a set of points (x,y,z).
@@ -58,13 +58,14 @@ def scatter_plot3d(x_points, y_points, z_points, colors,
     :param x_points: a list of x coordinates
     :param y_points: a list of y coordinates
     :param z_points: a list of z coordinates (optional)
-    :param colors: a color label for each point
+    :param output: the name/path of the output file
+    :param colors: a color label for each point (can be None)
+    :param alignment: an alignment 3x3 matrix (pass identity to not align)
     :param cmap: Matplotlib color mapping object (optional)
     :param title: the title for the plot
     :param xlabel: the name of the X label
     :param ylabel: the name of the Y label
-    :param zlabel: the name of the Z label
-    :param output: the name/path of the output file
+    :param image: the path to the image file
     :param alpha: the alpha transparency level for the dots
     :param size: the size of the dots
     :raises: RuntimeError
@@ -77,7 +78,7 @@ def scatter_plot3d(x_points, y_points, z_points, colors,
         color_list = set(colors)
         color_values = [color_map[i] for i in color_list]
         cmap = ListedColormap(color_values)
-    else:
+    elif colors is None:
         colors = "blue"
     a.scatter(x_points, 
               y_points,
@@ -98,7 +99,7 @@ def scatter_plot3d(x_points, y_points, z_points, colors,
     fig.set_size_inches(16, 16)
     fig.savefig(output, dpi=300)
 
-def scatter_plot(x_points, y_points, colors, output, 
+def scatter_plot(x_points, y_points, output, colors=None,
                  alignment=None, cmap=None, title='Scatter', xlabel='X', 
                  ylabel='Y', image=None, alpha=1.0, size=50):
     """ 
@@ -110,14 +111,73 @@ def scatter_plot(x_points, y_points, colors, output,
     The plot will be written to a file.
     :param x_points: a list of x coordinates
     :param y_points: a list of y coordinates
-    :param colors: a color label for each point
+    :param output: the name/path of the output file
+    :param colors: a color label for each point (can be None)
+    :param alignment: an alignment 3x3 matrix (pass identity to not align)
     :param cmap: Matplotlib color mapping object (optional)
     :param title: the title for the plot
     :param xlabel: the name of the X label
     :param ylabel: the name of the Y label
     :param image: the path to the image file
+    :param alpha: the alpha transparency level for the dots
+    :param size: the size of the dots
+    :raises: RuntimeError
+    """
+    # Plot spots with the color class in the tissue image
+    fig = plt.figure(figsize=(16,16))
+    a = fig.add_subplot(111, aspect='equal')
+    base_trans = a.transData
+    extent_size = (1,33,35,1)
+    # If alignment is None we re-size the image to chip size (1,1,33,35)
+    if alignment is not None:
+        base_trans = transforms.Affine2D(matrix = alignment) + base_trans
+        extent_size = None
+    color_values = None
+    if cmap is None and colors is not None:
+        color_list = set(colors)
+        color_values = [color_map[i] for i in color_list]
+        cmap = ListedColormap(color_values)
+    elif colors is None:
+        colors = "blue"
+    a.scatter(x_points, 
+              y_points,  
+              c=colors, 
+              cmap=cmap, 
+              edgecolor="none", 
+              s=size, 
+              transform=base_trans,
+              alpha=alpha)
+    if image is not None and os.path.isfile(image):
+        img = plt.imread(image)
+        # TODO imgshow() will not work if I pass extent_size as variable
+        a.imshow(img, extent=(1,33,35,1))
+    a.set_xlabel(xlabel)
+    a.set_ylabel(ylabel)
+    if color_values is not None:
+        a.legend([plt.Line2D((0,1),(0,0), color=x) for x in color_values], 
+                 color_list, loc="upper right", markerscale=1.0, 
+                 ncol=1, scatterpoints=1, fontsize=10)
+    a.set_title(title, size=20)
+    fig.set_size_inches(16, 16)
+    fig.savefig(output, dpi=300)
+
+def volcano_plot(x_points, y_points, output,
+                 title='Volcano', xlabel='X', ylabel='Y'):
+    """ 
+    This function makes a Volcano plot with the given
+    log2foldChange values (X) and -log10(pvalues) (Y).
+    It will color the most differently expressed
+    values (using the p-value threshold) as 
+    :param x_points: a list of x coordinates
+    :param y_points: a list of y coordinates
     :param output: the name/path of the output file
+    :param colors: a color label for each point (can be None)
     :param alignment: an alignment 3x3 matrix (pass identity to not align)
+    :param cmap: Matplotlib color mapping object (optional)
+    :param title: the title for the plot
+    :param xlabel: the name of the X label
+    :param ylabel: the name of the Y label
+    :param image: the path to the image file
     :param alpha: the alpha transparency level for the dots
     :param size: the size of the dots
     :raises: RuntimeError
@@ -136,7 +196,7 @@ def scatter_plot(x_points, y_points, colors, output,
         color_list = set(colors)
         color_values = [color_map[i] for i in color_list]
         cmap = ListedColormap(color_values)
-    else:
+    elif colors is None:
         colors = "blue"
     a.scatter(x_points, 
               y_points,