diff --git a/figure_plots/plots/SI/fig_S3/fig_S3A_RBC_GA_area.pdf b/figure_plots/plots/SI/fig_S3/fig_S3A_RBC_GA_area.pdf index a5cf93b146c82060995cf2249ae97888ce815b0c..aaef3bce7338c73f888cd559d0adb7651b9a3fa2 100644 Binary files a/figure_plots/plots/SI/fig_S3/fig_S3A_RBC_GA_area.pdf and b/figure_plots/plots/SI/fig_S3/fig_S3A_RBC_GA_area.pdf differ diff --git a/figure_plots/plots/SI/fig_S3/fig_S3A_RBC_GA_deform.pdf b/figure_plots/plots/SI/fig_S3/fig_S3A_RBC_GA_deform.pdf index cb50313ed159904275b33f79762e43dfb1de4e1b..994288289f81014989d3b82f4eaa2616cd6e0265 100644 Binary files a/figure_plots/plots/SI/fig_S3/fig_S3A_RBC_GA_deform.pdf and b/figure_plots/plots/SI/fig_S3/fig_S3A_RBC_GA_deform.pdf differ diff --git a/figure_plots/plots/SI/fig_S3/fig_S3B_RBC_diamide_area.pdf b/figure_plots/plots/SI/fig_S3/fig_S3B_RBC_diamide_area.pdf index e54aedc1bc4556d833cc22f4f16384047572cf09..63f5252fbd5694f57738d21b6c2b758df0e50174 100644 Binary files a/figure_plots/plots/SI/fig_S3/fig_S3B_RBC_diamide_area.pdf and b/figure_plots/plots/SI/fig_S3/fig_S3B_RBC_diamide_area.pdf differ diff --git a/figure_plots/plots/SI/fig_S3/fig_S3B_RBC_diamide_deform.pdf b/figure_plots/plots/SI/fig_S3/fig_S3B_RBC_diamide_deform.pdf index b7e4360c1f8cba55eaf38730a2b7a9d4ae2c4a5d..d792e492a1a92e5e5d5f3a5ae69b1c84bb7af2e3 100644 Binary files a/figure_plots/plots/SI/fig_S3/fig_S3B_RBC_diamide_deform.pdf and b/figure_plots/plots/SI/fig_S3/fig_S3B_RBC_diamide_deform.pdf differ diff --git a/figure_plots/plots_fig_S3.ipynb b/figure_plots/plots_fig_S3.ipynb index 548a0a7b91a2359c652ebc6465a86c1db8501226..dd815b15f2cbde729c66d8f9e332510d2972ed9b 100644 --- a/figure_plots/plots_fig_S3.ipynb +++ b/figure_plots/plots_fig_S3.ipynb @@ -14,7 +14,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 2, "metadata": { "collapsed": true }, @@ -33,7 +33,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 3, "outputs": [], "source": [ "savefolder = r\"plots\\SI\\fig_S3\"" @@ -47,7 +47,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 4, "outputs": [], "source": [ "def plot_violins(dataframe, x_axis, y_axis, pal='tab10', color=None, saturation=.9,\n", @@ -125,7 +125,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 5, "outputs": [], "source": [ "glutaraldehyde_file = \"data\\RTfDC\\RBC\\glutaraldehyde_20201214.tsv\"\n", @@ -140,13 +140,13 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 6, "outputs": [ { "data": { "text/plain": "Text(0, 0.5, 'Projected area [µm$^2$]')" }, - "execution_count": 16, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" }, @@ -191,7 +191,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 7, "outputs": [], "source": [ "save_name = \"fig_S3A_RBC_GA_area\"\n", @@ -208,7 +208,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 8, "outputs": [ { "name": "stdout", @@ -273,13 +273,13 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 9, "outputs": [ { "data": { "text/plain": "[Text(0, 0, 'CTRL'),\n Text(1, 0, '0.0001'),\n Text(2, 0, '0.0005'),\n Text(3, 0, '0.001'),\n Text(4, 0, '0.0025'),\n Text(5, 0, '0.005')]" }, - "execution_count": 24, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" }, @@ -333,12 +333,12 @@ "name": "#%%\n" } }, - "execution_count": 25, + "execution_count": 10, "outputs": [] }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 11, "outputs": [ { "name": "stdout", @@ -403,7 +403,7 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 12, "outputs": [], "source": [ "diamide_file = \"data\\RTfDC\\RBC\\diamide_20201214.tsv\"\n", @@ -430,13 +430,13 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 13, "outputs": [ { "data": { "text/plain": "Text(0, 0.5, 'Projected area [µm$^2$]')" }, - "execution_count": 29, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" }, @@ -483,7 +483,7 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 14, "outputs": [], "source": [ "save_name = \"fig_S3B_RBC_diamide_area\"\n", @@ -500,22 +500,22 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 15, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CTRL vs 0.1mM:\n", - "Student's t-Test: p-value = 3.9226713952246814e-48\n", + "Student's t-Test: p-value = 0.0\n", "Welch's t-Test: p-value = 2.1054588408456662e-47 \n", "\n", "CTRL vs 0.5mM:\n", - "Student's t-Test: p-value = 7.842650404242887e-152\n", + "Student's t-Test: p-value = 0.0\n", "Welch's t-Test: p-value = 3.862413764992832e-148 \n", "\n", "CTRL vs 1mM:\n", - "Student's t-Test: p-value = 1.5484391391412718e-214\n", + "Student's t-Test: p-value = 0.0\n", "Welch's t-Test: p-value = 1.3031072298036893e-209 \n", "\n", "CTRL vs 2mM:\n", @@ -539,7 +539,8 @@ "for concentration in plot_order[1:]:\n", " df_dia_concentration = df_diamide[df_diamide['diamide_concentration'] == concentration]\n", " t_statistic, p_value = ttest_ind(df_diamide_ctrl[y_para], df_dia_concentration[y_para],\n", - " equal_var=True # set false, if variance differs\n", + " equal_var=True, # set false, if variance differs\n", + " permutations = 10\n", " )\n", " t_statistic_welch, p_value_welch = ttest_ind(df_diamide_ctrl[y_para], df_dia_concentration[y_para],\n", " equal_var=False # set false, if variance differs\n", @@ -569,13 +570,13 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 16, "outputs": [ { "data": { "text/plain": "(0.095, 0.405)" }, - "execution_count": 32, + "execution_count": 16, "metadata": {}, "output_type": "execute_result" }, @@ -621,7 +622,7 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 17, "outputs": [], "source": [ "save_name = \"fig_S3B_RBC_diamide_deform\"\n", @@ -638,7 +639,7 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 21, "outputs": [ { "name": "stdout", @@ -677,7 +678,8 @@ "for concentration in plot_order[1:]:\n", " df_dia_concentration = df_diamide[df_diamide['diamide_concentration'] == concentration]\n", " t_statistic, p_value = ttest_ind(df_diamide_ctrl[y_para], df_dia_concentration[y_para],\n", - " equal_var=True # set false, if variance differs\n", + " equal_var=True, # set false, if variance differs\n", + " alternative='two-sided'\n", " )\n", " t_statistic_welch, p_value_welch = ttest_ind(df_diamide_ctrl[y_para], df_dia_concentration[y_para],\n", " equal_var=False # set false, if variance differs\n", @@ -695,7 +697,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 19, "outputs": [], "source": [], "metadata": {