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Merged
u8sand merged 1 commit into from
May 19, 2026
Merged

Add "the kinase library" and update plotly display #939

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24 changes: 15 additions & 9 deletions appyters/KEA3_Appyter/KEA3-Appyter.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -53,7 +53,8 @@
"from IPython.display import HTML, display, Image, FileLink, Markdown\n",
"import plotly.graph_objects as go\n",
"import kaleido\n",
"import os "
"import os \n",
"import html"
]
},
{
Expand Down Expand Up @@ -197,19 +198,19 @@
" k_libs_palette = {'BioGRID': 'rgb(196, 8, 8)', 'ChengKSIN': 'rgb(244, 109, 67)', 'ChengPPI': 'rgb(242, 172, 68)',\n",
" 'HIPPIE': 'rgb(236, 252, 68)', 'mentha': 'rgb(165, 242, 162)', 'MINT': 'rgb(92, 217, 78)',\n",
" 'PhosDAll': 'rgb(0, 138, 64)', 'prePPI': 'rgb(96, 191, 235)', 'PTMsigDB': 'rgb(14, 130, 201)',\n",
" 'STRING': 'rgb(58, 50, 168)', 'STRING.bind': 'rgb(158, 50, 168)'}\n",
" 'STRING': 'rgb(58, 50, 168)', 'STRING.bind': 'rgb(158, 50, 168)', 'The_Kinase_Library': 'rgb(235, 0, 235)'}\n",
" \n",
" k_libs_means = {'STRING.bind': [0] * 10, 'ChengPPI': [0] * 10, 'PhosDAll': [0] * 10, 'BioGRID': [0] * 10,\n",
" 'HIPPIE': [0] * 10, 'ChengKSIN': [0] * 10,\n",
" 'STRING': [0] * 10, 'MINT': [0] * 10, 'mentha': [0] * 10, 'prePPI': [0] * 10,\n",
" 'PTMsigDB': [0] * 10}\n",
" 'PTMsigDB': [0] * 10, 'The_Kinase_Library': [0] * 10}\n",
"\n",
" libs_sorted = ['BioGRID', 'ChengKSIN', 'ChengPPI', 'HIPPIE', 'mentha', 'MINT', 'PhosDAll', 'prePPI', 'PTMsigDB', 'STRING', 'STRING.bind', 'The_Kinase_Library']\n",
"\n",
" libs_sorted = ['BioGRID', 'ChengKSIN', 'ChengPPI', 'HIPPIE', 'mentha', 'MINT', 'PhosDAll', 'prePPI', 'PTMsigDB', 'STRING', 'STRING.bind']\n",
" \n",
" results_mr_t = [r for r in results['Integrated--meanRank'] if len(r['Library'].split(';')) >= threshold][:num_kinases]\n",
" # results_mr_t.sort(key=lambda kin: sum([int(k.split(',')[1]) for k in kin['Library'].split(';')]))\n",
" results_mr_t = results_mr_t[::-1]\n",
" sorted_kinases = [k['TF'] for k in results_mr_t[:num_kinases]]\n",
" sorted_kinases = [k['TF'] for k in results_mr_t[:num_kinases]] \n",
"\n",
" for i, kin in enumerate(results_mr_t[:num_kinases]):\n",
" scores = kin['Library'].split(';')\n",
Expand Down Expand Up @@ -237,12 +238,17 @@
" )\n",
" )\n",
"\n",
" html_str = fig.to_html(include_plotlyjs='cdn')\n",
" escaped_html = html.escape(html_str)\n",
" iframe = f\"\"\"\n",
" <iframe srcdoc=\"{escaped_html}\" width=\"100%\" height=\"400\" frameborder=\"0\" scrolling=\"no\" style=\"overflow:hidden\"></iframe>\n",
" \"\"\"\n",
" display(HTML(iframe))\n",
" display(HTML(\n",
" '<h2>This interactive bar chart summarizes the ranks of the top kinases from the different libraries.</h2>'))\n",
" display(HTML(\n",
" f'<i>Kinases are sorted by MeanRank. Only kinases with at least {threshold} contributed libraries are shown. ' +\n",
" 'To download the file as a PNG, click the camera button in the upper right corner of the chart.</i>'))\n",
" fig.show()"
" 'To download the file as a PNG, click the camera button in the upper right corner of the chart.</i>'))"
]
},
{
Expand Down Expand Up @@ -271,7 +277,7 @@
"\n",
" display(HTML('<h2>The following tables display the rankings of the top kinases from each library.</h2>'))\n",
"\n",
" display_tables(['ChengKSIN', 'PTMsigDB', 'PhosDAll'], 'Kinase-substrate interaction')\n",
" display_tables(['ChengKSIN', 'PTMsigDB', 'PhosDAll', 'The_Kinase_Library'], 'Kinase-substrate interaction')\n",
" display_tables(['prePPI', 'BioGRID', 'mentha', 'MINT','HIPPIE', 'STRING.bind', 'ChengPPI'], 'Protein-protein interaction')\n",
" display_tables(['STRING'], 'All associations')"
]
Expand Down
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