add notebooks to do predictions and interpretations on custom sequences input as fasta files

Author: panushri25

chrombpnet/evaluation/custom_sequences/custom_sequence_interpret.ipynb

@@ -0,0 +1,4 @@
+>seq1
+AATCTCCAGGTTATTTAAAGTAGTTATAGGAGCAGAGAACAAGCACCTTTATCAAAATCTGGTCCTATGTGCCTTGCTTTACCAAATACCTGATTTTTCTGGAGGGTGTTCCTGTAATTCACAACTGTAGACACATGGGCAAAATTAGGATTTTTAAGAATAAATACATTTCTATTTTTTTGGTTGTTTCAACATTAGCTCTTCAAATTCATTAACAAAATTAAAATAGGTATATTACAAAAGCATAAACATTTGTGAACAGTACTTAAATAAATTGTGATACTATTGCTCCATCATTGAACTTTTTGAAACTTTAACAATTGTATAAAACTGTCAGTTTGTTGTTTCATTTGTAATTACAAAATAATTTAAAAACTTTTTAAAATAATTTGGATCCTGACTTTGTCTATATCTGTATTTCATTTGTTTAGAAAGATTCTTTTGGGTTTGATAATGTAATTTGTATATTTAAATTTTTTATGGACATAATTCAAAGGAATGTATAAATTGGTCTTTTGTTAAATGGCTTTTTAATTGATAAACTTCTCTTGTCATTTTTTGGTATCCAGCTATTACCTATTTAATAGATTTATTGAAATAGATTATTTTCATAAAGAACTCTATACAAATCTTTTTCTATATTTCCTTATTTTCCTATTTACCTGTGTCTATGACCTAACCTATGAATTAGTCTTCTCTCTTTATATATCAAAAATGAATTACTGATCTTTTTCTCTGGCTCTGTAGTATCTCTATCACTGTCACATGTGATCTTTCTTCCTTTTCTCTAGCCCATATTCTAGCATGAAATACTGGGTTGGCCAGGTGCAGTGGCTCATTCCTGTAATCCCAACACTTTAGGAAGCCAAGGCAGAAGAATCGCTTGAGCCCATGAATTTGAGGCCAGCCTGGGCAACATAGCCTTGTTTCTACAAAAAATCTTAAAAATAAAATTAGCCAATATGTGGGCATGCACCTGTGGGGCCAGCTACTCAGGAGGCTGAGGCAGAAGGATTGCTTGAGCCCAGCAATTTGATGCTGCAGTAAACCATGATGACACTACTGGACTCTAGCCTGAGTGACAGTGAGACTCTGTCTCAAAAAACAAACAAAACAAAAACTGAAACAACAAAAAAAGACTGGGTTTATTTAAGCTAGTTAGAATTTATCTTTCTATATGTTAATAACAGCCTAACAGATTTTTTGTTTTAAATATCTCTAGGCTAGCCTCAAGGTTAAGTAATTATAGAAGTTTGGTATGTATTTTCTTCATAATTTGAATATAATTGCTTCCATTGTGACTGTCAATTGAATGCATGGAGATCAATTGTGATAATATACAGGATTTTAGTCCTATCTCTACTGCTGAAGTAACCTTACACAAAATACTTTGTAAAAAAATCACTAAAGTGCCAGCATTTTTAAAGTGTATATTTTTCTTTGGCAACCTCTCATGAAAAGCACTAACTAAAAATATTTAATAATCTTTTTTGTATTACAGTGCTTCTTTTGTTGGAAATATATCACAATCCTCAAGTTCCACTGCTATGCAAAAGTATCTTAGAATCTGAATCTTATAGATAATACTACCTTTTTTTTTTTTTTTTTTTTTTTTTTGAGATGGTGTCTCGCTCTGTCACCTAGGCTGCAGTGGTGTGACCTCACTGCAACCTCTGCCTCCCAGGTTCAAGCAATTCTCCTGCCTCAGCCTCCCTAGTAACTGGGATTACAGGCCATGCCACCACGCCCAACTAATTTTTGTATTTTTAGTAGAGACAGGGTTTCACCATGTTGGCCAGGCTGGTCTCAAACTCCTGACCTCAGGTGATCCGCCTGCCTCGGCCTCCCAAAGTGCTGGGTTTACAGGCGTGAGCCGCTGCGCCCGGCCAATACTGCCTTTCAAAAGAGACTGATAGTGACCAGCATTAGTAATCATACTGGTGGGGTTTTTTGGGGTGTTTTTCTGTTTTGTTTTTTGTTTTTTGTTTTTGAGACAAGGTCTTCCTCCCGTTGCCTAGGCTGGAGTGCGGTGACACAATCTTGGCTCACTGCAGCCTTGATAGAGCAAGCTCAAGTGATCCTCCCAGGAGCCTCGGCCCCCAAGCAGCTGGGAA
+>seq2
+ATCACAATCCTCAAGTTCCACTGCTATGCAAAAGTATCTTAGAATCTGAATCTTATAGATAATACTACCTTTTTTTTTTTTTTTTTTTTTTTTTTGAGATGGTGTCTCGCTCTGTCACCTAGGCTGCAGTGGTGTGACCTCACTGCAACCTCTGCCTCCCAGGTTCAAGCAATTCTCCTGCCTCAGCCTCCCTAGTAACTGGGATTACAGGCCATGCCACCACGCCCAACTAATTTTTGTATTTTTAGTAGAGACAGGGTTTCACCATGTTGGCCAGGCTGGTCTCAAACTCCTGACCTCAGGTGATCCGCCTGCCTCGGCCTCCCAAAGTGCTGGGTTTACAGGCGTGAGCCGCTGCGCCCGGCCAATACTGCCTTTCAAAAGAGACTGATAGTGACCAGCATTAGTAATCATACTGGTGGGGTTTTTTGGGGTGTTTTTCTGTTTTGTTTTTTGTTTTTTGTTTTTGAGACAAGGTCTTCCTCCCGTTGCCTAGGCTGGAGTGCGGTGACACAATCTTGGCTCACTGCAGCCTTGATAGAGCAAGCTCAAGTGATCCTCCCAGGAGCCTCGGCCCCCAAGCAGCTGGGAATACAGGTGCGCGCCACCATGCCCAGCTGATTTTTGTATTTTTTTGTAGAGATGGGGTTTTGCCATGTTGCCCGGATTGGTCTCAAACTCCTGAGCTTCAGTGATCTGCCTGCCTTGGCCTCCCAAAGTGTTGGGATTACAGGCGTGAGCGACCACACCCAGCCCATATTGGTCTTTCTTACTGTTCTTAAAAAGAGAATTCCTTTAAGGCAGGACCGATTACATATACACTCTAGAAAAGAAAATAGCAAGGAAGAAATAAATTGCCTTCAATTACCAAAGATTTGAGCTTCTGCTATGGCTGAGAGTGTTTTGGTCATTGCAAATTCAGGGGTTTCCCAAGTTCACCCTCAGTTCTGGCTAGAAAGAGAAAACTTACTAAAAGCTATTATACTCACAGTCATATTTATTACAGAGAAAGGAAATACAAATTAAAACCAGCCAAAGGAAGTGACACATAAAACAGAGTCTAGGAGTGGTCCAAACTTGAGGCTTTCGGTGTCCTTTTCTTGTAGCGTCATGGAAGGTGTTATCTACTCCTGACCACAATGTTTGACAGTACACACATAGTATTGCCATTCAGGGAAGCTCACCTAAGCTTTGGTGTCCAGATTTTTATTGAGAGAGGCTCTATTAGTTGGCATGGTTGGTTGATTTTTTTGCCCATGTAGTTGTCCTCTCTTTCCAACATCTGCCCCTCCCTGGAGATCTGGTTGACATCAAGACTTCAGGGCCTCACCATAGGTTATCTCGTTAGCATAAACTGTCAAGTGTTGTCTAAGGAACCCACAATGAATAATAAAGACATTCCTATCAGTGAGAACTCCCAAAGACTTACACCAGAACTTTCTTTGGATGGGCCAAATTTCTTACTACACAAAGACCATTCATCTCTATACACTTCCTTCTGAATTGATGAGGATGATACAAGCAACGACAATTCTTCTTTTCAGAGACTTTTAATTTTTTTTTTTTTTTTTTTTTTGAGATGGAGTCTCGCTCTGTCACTCAGGCTGGAGTTCAGCGGCACGATCTCTGCTCACTGCAACCTCCGCCTCCTGGGTTTGAGCAATTCTCCTACCTCAGCCTCCCAAGTAGCTGGGATTACTGGTGCTCACCACCACGCCCAACTAATTTTTGTATTTTTGGTAGAGACGGGTTTTCACCATGTTGGCCAGGCTGGTCTCGAACTCCTGACCTCAGGTGATCTGCCGGCCTTGGCCTCCCAAAGTGCTGGGATTACAGGCATGAGCCATCACACCCAGCCCAGAGACTTTTAATTTATACATTGTCATTTTTAATTTTAGAATATCTGTCAAATGATTCTGAACATAACATGAATCTAGTGTGGAAAAATGTTTATAATCAGATATTGTGTTAAGAACATATATATATATATAGAGAGAGAGAGAGCATAGTATTGTCATTTAGTTTTCACTTCTTATGTTTAATGACAACTTTATAAATGCTGGACTATTTTAAACTACAAATTTAAAACATGGTTTATAAACCTTTTACCTGTA

chrombpnet/evaluation/custom_sequences/custom_sequence_pred.ipynb

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+import matplotlib
+import matplotlib.pyplot as plt
+import numpy as np
+
+
+def ic_scale(pwm,background):
+    odds_ratio = ((pwm+0.001)/(1.004))/(background[None,:])
+    ic = ((np.log((pwm+0.001)/(1.004))/np.log(2))*pwm -\
+            (np.log(background)*background/np.log(2))[None,:])
+    return pwm*(np.sum(ic,axis=1)[:,None])
+
+
+def plot_a(ax, base, left_edge, height, color):
+    a_polygon_coords = [
+        np.array([
+           [0.0, 0.0],
+           [0.5, 1.0],
+           [0.5, 0.8],
+           [0.2, 0.0],
+        ]),
+        np.array([
+           [1.0, 0.0],
+           [0.5, 1.0],
+           [0.5, 0.8],
+           [0.8, 0.0],
+        ]),
+        np.array([
+           [0.225, 0.45],
+           [0.775, 0.45],
+           [0.85, 0.3],
+           [0.15, 0.3],
+        ])
+    ]
+    for polygon_coords in a_polygon_coords:
+        ax.add_patch(matplotlib.patches.Polygon((np.array([1,height])[None,:]*polygon_coords
+                                                 + np.array([left_edge,base])[None,:]),
+                                                facecolor=color, edgecolor=color))
+
+
+def plot_c(ax, base, left_edge, height, color):
+    ax.add_patch(matplotlib.patches.Ellipse(xy=[left_edge+0.65, base+0.5*height], width=1.3, height=height,
+                                            facecolor=color, edgecolor=color))
+    ax.add_patch(matplotlib.patches.Ellipse(xy=[left_edge+0.65, base+0.5*height], width=0.7*1.3, height=0.7*height,
+                                            facecolor='white', edgecolor='white'))
+    ax.add_patch(matplotlib.patches.Rectangle(xy=[left_edge+1, base], width=1.0, height=height,
+                                            facecolor='white', edgecolor='white', fill=True))
+
+
+def plot_g(ax, base, left_edge, height, color):
+    ax.add_patch(matplotlib.patches.Ellipse(xy=[left_edge+0.65, base+0.5*height], width=1.3, height=height,
+                                            facecolor=color, edgecolor=color))
+    ax.add_patch(matplotlib.patches.Ellipse(xy=[left_edge+0.65, base+0.5*height], width=0.7*1.3, height=0.7*height,
+                                            facecolor='white', edgecolor='white'))
+    ax.add_patch(matplotlib.patches.Rectangle(xy=[left_edge+1, base], width=1.0, height=height,
+                                            facecolor='white', edgecolor='white', fill=True))
+    ax.add_patch(matplotlib.patches.Rectangle(xy=[left_edge+0.825, base+0.085*height], width=0.174, height=0.415*height,
+                                            facecolor=color, edgecolor=color, fill=True))
+    ax.add_patch(matplotlib.patches.Rectangle(xy=[left_edge+0.625, base+0.35*height], width=0.374, height=0.15*height,
+                                            facecolor=color, edgecolor=color, fill=True))
+
+
+def plot_t(ax, base, left_edge, height, color):
+    ax.add_patch(matplotlib.patches.Rectangle(xy=[left_edge+0.4, base],
+                  width=0.2, height=height, facecolor=color, edgecolor=color, fill=True))
+    ax.add_patch(matplotlib.patches.Rectangle(xy=[left_edge, base+0.8*height],
+                  width=1.0, height=0.2*height, facecolor=color, edgecolor=color, fill=True))
+
+default_colors = {0:'green', 1:'blue', 2:'orange', 3:'red'}
+default_plot_funcs = {0:plot_a, 1:plot_c, 2:plot_g, 3:plot_t}
+def plot_weights_given_ax(ax, array,
+                 height_padding_factor,
+                 length_padding,
+                 subticks_frequency,
+                 highlight,
+                 colors=default_colors,
+                 plot_funcs=default_plot_funcs,
+                 ylabel="",
+                 ylim=None):
+    if len(array.shape)==3:
+        array = np.squeeze(array)
+    assert len(array.shape)==2, array.shape
+    if (array.shape[0]==4 and array.shape[1] != 4):
+        array = array.transpose(1,0)
+    assert array.shape[1]==4
+    max_pos_height = 0.0
+    min_neg_height = 0.0
+    heights_at_positions = []
+    depths_at_positions = []
+    for i in range(array.shape[0]):
+        #sort from smallest to highest magnitude
+        acgt_vals = sorted(enumerate(array[i,:]), key=lambda x: abs(x[1]))
+        positive_height_so_far = 0.0
+        negative_height_so_far = 0.0
+        for letter in acgt_vals:
+            plot_func = plot_funcs[letter[0]]
+            color=colors[letter[0]]
+            if (letter[1] > 0):
+                height_so_far = positive_height_so_far
+                positive_height_so_far += letter[1]                
+            else:
+                height_so_far = negative_height_so_far
+                negative_height_so_far += letter[1]
+            plot_func(ax=ax, base=height_so_far, left_edge=i, height=letter[1], color=color)
+        max_pos_height = max(max_pos_height, positive_height_so_far)
+        min_neg_height = min(min_neg_height, negative_height_so_far)
+        heights_at_positions.append(positive_height_so_far)
+        depths_at_positions.append(negative_height_so_far)
+
+    #now highlight any desired positions; the key of
+    #the highlight dict should be the color
+    for color in highlight:
+        for start_pos, end_pos in highlight[color]:
+            assert start_pos >= 0.0 and end_pos <= array.shape[0]
+            min_depth = np.min(depths_at_positions[start_pos:end_pos])
+            max_height = np.max(heights_at_positions[start_pos:end_pos])
+            ax.add_patch(
+                matplotlib.patches.Rectangle(xy=[start_pos,min_depth],
+                    width=end_pos-start_pos,
+                    height=max_height-min_depth,
+                    edgecolor=color, fill=False))
+            
+    ax.set_xlim(-length_padding, array.shape[0]+length_padding)
+    ax.xaxis.set_ticks(np.arange(0.0, array.shape[0]+1, subticks_frequency))
+
+    if ylim is not None:
+        # Use user-specified y-axis limits
+        min_neg_height, max_pos_height = ylim
+        assert min_neg_height <= 0
+        assert max_pos_height >= 0
+
+    height_padding = max(abs(min_neg_height)*(height_padding_factor),
+                         abs(max_pos_height)*(height_padding_factor))
+    ax.set_ylim(min_neg_height-height_padding, max_pos_height+height_padding)
+    ax.set_ylabel(ylabel)
+    ax.yaxis.label.set_fontsize(15)
+
+
+def plot_weights(array,
+                 figsize=(20,2),
+                 height_padding_factor=0.2,
+                 length_padding=1.0,
+                 subticks_frequency=1.0,
+                 colors=default_colors,
+                 plot_funcs=default_plot_funcs,
+                 highlight={},
+                 ylabel="",
+                 ylim=None,
+                dpi=300):
+    fig = plt.figure(figsize=figsize, dpi=dpi)
+    ax = fig.add_subplot(111) 
+    plot_weights_given_ax(ax=ax, array=array,
+        height_padding_factor=height_padding_factor,
+        length_padding=length_padding,
+        subticks_frequency=subticks_frequency,
+        colors=colors,
+        plot_funcs=plot_funcs,
+        highlight=highlight,
+        ylabel=ylabel,
+        ylim=ylim)
+#     plt.show()