Update rankovic analysis

Author: constantinpape

scripts/figures/plot_fig6.py

@@ -83,7 +83,7 @@ def plot_legend_fig06e(save_path):
     label = list(color_dict.keys())
     color = [color_dict[key] for key in color_dict.keys()]
 
-    f = lambda m, c: plt.plot([], [], marker=m, color=c, ls="none")[0]
+    f = lambda m, c: plt.plot([], [], marker=m, color=c, ls="none")[0]  # noqa
     handles = [f(m, c) for (c, m) in zip(color, marker)]
     legend = plt.legend(handles, label, loc=3, ncol=2, framealpha=1, frameon=False)
     export_legend(legend, save_path)
@@ -169,6 +169,7 @@ def fig_06e_octave(otof_data, save_path, plot=False, use_alias=True, trendline_m
         marker_neg = len([1 for i in marker_labels if i == 2])
         expression_eff = marker_pos / (marker_pos + marker_neg)
         print(f"Cochlea {name}, average expression efficiency {expression_eff}")
+        print(f"Cochlea {name}, number of IHCs: {len(freq)}")
         octave_binned = frequency_mapping(
             freq, marker_labels, animal="mouse", transduction_efficiency=True,
             bin_edges=bin_edges, bin_labels=bin_labels

scripts/la-vision/otof/README.md

@@ -0,0 +1,19 @@
+# Analysis Reuslts OTOF La-Vision Data
+
+## From Rankovic et al.
+
+- OTOF-23R:
+    - N-IHCS: 340
+    - Expression Efficiency: 0.3058823529411765
+- OTOF-25R:
+    - N-IHCS: 346
+    - Expression Efficiency: 0.21676300578034682
+
+## Our Analysis
+
+- OTOF-23R:
+    - N-IHCS: 643
+    - Expression Efficiency: 0.38202247191011235
+- OTOF-25R:
+    - N-IHCS: 520
+    - Expression Efficiency: 0.37884615384615383

scripts/la-vision/otof/comparison_rankovic.py

@@ -0,0 +1,108 @@
+import sys
+
+import matplotlib.pyplot as plt
+
+sys.path.append("../../figures")
+
+
+def plot_tonotopy(bin_labels, values, names, expression_eff_list):
+    from util import prism_style, prism_cleanup_axes
+
+    color_dict = {"O1": "#9C5027", "O2": "#67279C"}
+
+    prism_style()
+    label_size = 20
+    tick_label_size = 14
+
+    # result = pd.DataFrame(result)
+    # bin_labels = pd.unique(result["octave_band"])
+    # band_to_x = {band: i for i, band in enumerate(bin_labels)}
+    # result["x_pos"] = result["octave_band"].map(band_to_x)
+
+    fig, ax = plt.subplots(figsize=(8, 4))
+
+    offset = 0.08
+    for num in range(len(names)):
+
+        name = names[num]
+        expr_vals = values[num]
+
+        x_positions = range(len(bin_labels))
+        x_positions = [x - len(bin_labels) // 2 * offset + offset * num for x in x_positions]
+
+        x_positions = [pos for i, pos in enumerate(x_positions) if expr_vals[i] is not None]
+        expr_vals = [val for val in expr_vals if val is not None]
+        assert len(x_positions) == len(expr_vals)
+
+        ax.scatter(x_positions, expr_vals, marker="o", label=name, s=80, alpha=1, color=color_dict[name])
+
+    xlim_left, xlim_right = ax.get_xlim()
+    y_offset = [0.01, -0.04]
+    x_offset = 0.5
+    plt.xlim(xlim_left, xlim_right)
+    for num, key in enumerate(color_dict.keys()):
+        color = color_dict[key]
+        expression_eff = expression_eff_list[num]
+
+        ax.text(xlim_left + x_offset, expression_eff + y_offset[num], "mean",
+                color=color, fontsize=tick_label_size, ha="center")
+        trend_r, = ax.plot(
+            [xlim_left, xlim_right],
+            [expression_eff, expression_eff],
+            linestyle="dashed",
+            color=color,
+            alpha=0.7,
+            zorder=0
+        )
+
+    ax.set_xticks(range(len(bin_labels)))
+    ax.set_xticklabels(bin_labels)
+    ax.set_xlabel("Octave band [kHz]", fontsize=label_size)
+
+    ax.set_ylabel("Expression efficiency")
+    plt.tight_layout()
+    prism_cleanup_axes(ax)
+
+    plt.show()
+
+
+def main():
+    frequencies = ["4-8", "8-12", "12-16", "16-24", "24-32"]
+
+    n_ihcs_23R = [51, 107, 77, 105, None]
+    n_pos_23R = [15, 36, 24, 29, None]
+    assert len(n_ihcs_23R) == len(n_pos_23R)
+    assert len(n_ihcs_23R) == len(frequencies)
+
+    n_ihcs_25R = [None, 103, 71, 102, 70]
+    n_pos_25R = [None, 24, 21, 28, 2]
+    assert len(n_ihcs_25R) == len(n_pos_25R)
+    assert len(n_ihcs_25R) == len(frequencies)
+
+    total_23R = sum(n for n in n_ihcs_23R if n is not None)
+    pos_23R = sum(n for n in n_pos_23R if n is not None)
+    eff_23R = float(pos_23R) / total_23R
+    print("N-IHCs 23R:", total_23R)
+    print("Expr. Eff.:", eff_23R)
+    print()
+
+    total_25R = sum(n for n in n_ihcs_25R if n is not None)
+    pos_25R = sum(n for n in n_pos_25R if n is not None)
+    eff_25R = float(pos_25R) / total_25R
+    print("N-IHCs 25R:", total_25R)
+    print("Expr. Eff.:", eff_25R)
+
+    expr_23R = [None if n is None else float(pos) / n
+                for pos, n in zip(n_pos_23R, n_ihcs_23R)]
+    expr_25R = [None if n is None else float(pos) / n
+                for pos, n in zip(n_pos_25R, n_ihcs_25R)]
+    plot_tonotopy(
+        frequencies,
+        values=[expr_23R, expr_25R],
+        names=["O1", "O2"],
+        expression_eff_list=[eff_23R, eff_25R]
+    )
+
+
+if __name__ == "__main__":
+    main()