{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# 2.1 CCLE Gene Expression\n", "This notebook uses Clustergrammer2 to visualize the Cancer cell line Encyclopedia gene expression data (data obtained from the [Broad-Institute](https://portals.broadinstitute.org/ccle)). The CCLE project measured genetic data from over 1000 cancer cell lines and provides cell line annotations (e.g. tissue) that is used to generate cell type categories. " ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ ">> clustergrammer2 backend version 0.14.0\n" ] } ], "source": [ "from clustergrammer2 import Network, CGM2\n", "import warnings\n", "warnings.filterwarnings('ignore')\n", "df = {}" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", "df['ini'] = pd.read_csv('../data/CCLE/CCLE.txt.gz', compression='gzip', index_col=0)" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "from ast import literal_eval as make_tuple\n", "cols = df['ini'].columns.tolist()\n", "new_cols = [make_tuple(x) for x in cols]\n", "df['ini'].columns = new_cols" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "n1 = Network(CGM2)\n", "n2 = Network(CGM2)" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "from copy import deepcopy\n", "df['meta_col'] = n1.make_df_from_cols(df['ini'].columns.tolist())\n", "df['clean'] = deepcopy(df['ini'])\n", "df['clean'].columns = df['meta_col'].index.tolist()" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ " color\n", "Cat red\n", "Dog yellow\n", "Shark black\n", "Snake blue\n", "Lizard green" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df['meta_cat_col'] = pd.DataFrame()\n", "df['meta_cat_col'].loc['Cat', 'color'] = 'red'\n", "df['meta_cat_col'].loc['Dog', 'color'] = 'yellow'\n", "df['meta_cat_col'].loc['Shark', 'color'] = 'black'\n", "df['meta_cat_col'].loc['Snake', 'color'] = 'blue'\n", "df['meta_cat_col'].loc['Lizard', 'color'] = 'green'\n", "df['meta_cat_col']" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# CCLE Gene Expression Data" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "5900273abcd84c2a8785bc33b47087b5", "version_major": 2, "version_minor": 0 }, "text/plain": [ "CGM2(manual_cat='{\"col\": {\"col_cat_colors\": {\"tissue: autonomic_ganglia\": \"#393b79\", \"tissue: biliary_tract\": …" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "n1.load_df(df['clean'], meta_col=df['meta_col'])\n", "n1.set_global_cat_colors(df['meta_cat_col'])\n", "n1.filter_N_top(axis='row', N_top=500, rank_type='var')\n", "n1.normalize(axis='row', norm_type='zscore')\n", "n1.set_manual_category(col='tissue', preferred_cats=df['meta_cat_col'])\n", "n1.widget()" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Snake 388\n", "Something!!!!!! 324\n", "haematopoietic_and_lymphoid_tissue 174\n", "lung 66\n", "autonomic_ganglia 13\n", "liver 12\n", "bone 10\n", "ovary 9\n", "stomach 8\n", "soft_tissue 8\n", "pancreas 5\n", "endometrium 5\n", "Lizard 4\n", "central_nervous_system 3\n", "large_intestine 3\n", "breast 2\n", "small_intestine 1\n", "prostate 1\n", "thyroid 1\n", "Name: tissue, dtype: int64" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df['meta_col']['tissue'].value_counts()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Cluster Based on Subset of Genes" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": [ "keep_genes = [ 'KRT19', 'EPCAM', 'TACSTD2', 'MAL2', 'AGR2', 'C19orf33', 'S100P', 'DSP', 'MIR205HG', 'SPINT2', 'ANXA3', 'ESRP1', 'KRT7', 'TSPAN8', 'VAMP8', 'LCN2', 'RAB25', 'SERPINB5', 'CSTA', 'SFN', 'CEACAM6', 'GPX2', 'NMU', 'C10orf116', 'TSTD1', 'FOXQ1', 'GALNT3', 'GDA', 'FOXA1', 'DMKN', 'SLPI', 'DSG2', 'TOX3', 'ASS1', 'CLDN1', 'KRT17', 'S100A8', 'KRT6A', 'FGFBP1', 'PLBD1', 'CEACAM5', 'CHMP4C', 'SPINT1', 'UCA1', 'GJB2', 'MMP7', 'TSPAN1', 'EEF1A2', 'FXYD3', 'WFDC2', 'CDH1', 'CLDN4', 'AIM1', 'ERBB3', 'TPD52L1', 'CST6', 'GPR87', 'IL18', 'GSTO2', 'FAM110C', 'S100A14', 'CLIC3', 'KLF5', 'MYO5C', 'KRT14', 'F2RL1', 'SELENBP1', 'KRT5', 'IRX2', 'TFF1', 'SLCO1B3', 'ST14', 'SORL1', 'MANSC1', 'PPL', 'KRT80', 'CDH3', 'S100A9', 'CRABP2', 'KCNK1', 'ESRP2', 'KRT23', 'INHBB', 'HOOK1', 'CALB1', 'KRT13', 'ZBED2', 'GPR160', 'TMEM45B', 'PI3', 'ELOVL7', 'SLC27A2']" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "21e0a551cabb485d92492ceb53338e5b", "version_major": 2, "version_minor": 0 }, "text/plain": [ "CGM2(manual_cat='{\"col\": {\"col_cat_colors\": {\"tissue: Dog\": \"#393b79\", \"tissue: autonomic_ganglia\": \"#ff7f0e\",…" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "n2.load_df(df['clean'].loc[keep_genes], meta_col=df['meta_col'])\n", "n2.set_global_cat_colors(df['meta_cat_col'])\n", "n2.filter_N_top(axis='row', N_top=500, rank_type='var')\n", "n2.normalize(axis='row', norm_type='zscore')\n", "n2.set_manual_category(col='tissue', preferred_cats=df['meta_cat_col'])\n", "n2.widget(link_net=n1)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "df_export = net.export_df()\n", "df_export.shape" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "df_export.to_csv('../data/CCLE/CCLE_500x1037.csv')\n", "net.save_dict_to_json(net.viz, '../data/CCLE/CCLE_500x1037.json')" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# man_cat = net.get_manual_category('col', 'tissue')" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# man_cat['tissue'].value_counts()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# man_cat['new_colors']" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "net.load_df(df_export)\n", "net.set_manual_category(col='tissue')\n", "net.normalize(axis='row', norm_type='zscore')\n", "net.set_matrix_colors(pos='red', neg='blue')\n", "net.widget()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "man_cat = net.get_manual_category('col', 'tissue')\n", "man_cat['tissue'].value_counts()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "df_export = net.export_df()\n", "df_export.to_csv('../data/CCLE/CCLE_500x1037-z.csv')\n", "net.save_dict_to_json(net.viz, '../data/CCLE/CCLE_500x1037-z.json')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# CCLE Gene Expression Data, Z-score Genes" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "net.load_df(df)\n", "net.filter_N_top(axis='row', N_top=1000, rank_type='var')\n", "net.normalize(axis='row', norm_type='zscore')\n", "net.load_df(net.export_df().round(2))\n", "net.manual_category(col='tissue')\n", "net.widget()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "man_cat = net.get_manual_category('col', 'tissue')\n", "man_cat['tissue'].value_counts()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.5" }, "widgets": { "application/vnd.jupyter.widget-state+json": { "state": { "22af51137c944e4183e12a7130c38397": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": {} }, "3eafe1c2fb2c48f29a43e612503d1c58": { "model_module": "clustergrammer2", "model_module_version": "^0.5.1", "model_name": "ExampleModel", "state": { "_model_module_version": "^0.5.1", "_view_module_version": "^0.5.1", "layout": "IPY_MODEL_22af51137c944e4183e12a7130c38397", "mat_string": "ini_mat_string", "network": "{\"row_nodes\": [{\"name\": \"KRT19\", \"ini\": 1000, \"clust\": 967, \"rank\": 948, \"rankvar\": 689, \"group\": [954.0, 924.0, 747.0, 436.0, 144.0, 13.0, 1.0, 1.0, 1.0, 1.0, 1.0]}, {\"name\": \"EPCAM\", \"ini\": 999, \"clust\": 998, \"rank\": 148, \"rankvar\": 127, \"group\": [977.0, 939.0, 747.0, 436.0, 144.0, 13.0, 1.0, 1.0, 1.0, 1.0, 1.0]}, {\"name\": \"TACSTD2\", \"ini\": 998, \"clust\": 979, \"rank\": 92, \"rankvar\": 571, \"group\": [960.0, 930.0, 747.0, 436.0, 144.0, 13.0, 1.0, 1.0, 1.0, 1.0, 1.0]}, {\"name\": \"MAL2\", \"ini\": 997, \"clust\": 999, \"rank\": 469, \"rankvar\": 18, \"group\": [978.0, 939.0, 747.0, 436.0, 144.0, 13.0, 1.0, 1.0, 1.0, 1.0, 1.0]}, {\"name\": \"TGFBI\", \"ini\": 996, \"clust\": 662, \"rank\": 311, \"rankvar\": 374, \"group\": [649.0, 630.0, 531.0, 310.0, 101.0, 10.0, 1.0, 1.0, 1.0, 1.0, 1.0]}, {\"name\": \"AGR2\", \"ini\": 995, \"clust\": 927, \"rank\": 349, \"rankvar\": 630, \"group\": [915.0, 885.0, 726.0, 436.0, 144.0, 13.0, 1.0, 1.0, 1.0, 1.0, 1.0]}, {\"name\": \"VIM\", \"ini\": 994, \"clust\": 373, \"rank\": 575, \"rankvar\": 355, \"group\": [368.0, 352.0, 309.0, 239.0, 101.0, 10.0, 1.0, 1.0, 1.0, 1.0, 1.0]}, {\"name\": \"GJA1\", \"ini\": 993, \"clust\": 458, \"rank\": 522, \"rankvar\": 408, \"group\": [459.0, 443.0, 384.0, 271.0, 101.0, 10.0, 1.0, 1.0, 1.0, 1.0, 1.0]}, {\"name\": \"SRGN\", \"ini\": 992, \"clust\": 140, \"rank\": 27, \"rankvar\": 775, \"group\": [139.0, 125.0, 93.0, 62.0, 34.0, 5.0, 1.0, 1.0, 1.0, 1.0, 1.0]}, {\"name\": \"IGFBP7\", \"ini\": 991, \"clust\": 479, \"rank\": 381, \"rankvar\": 139, \"group\": [478.0, 461.0, 401.0, 272.0, 101.0, 10.0, 1.0, 1.0, 1.0, 1.0, 1.0]}, {\"name\": \"SPP1\", \"ini\": 990, \"clust\": 334, \"rank\": 181, \"rankvar\": 94, \"group\": [333.0, 317.0, 275.0, 208.0, 90.0, 10.0, 1.0, 1.0, 1.0, 1.0, 1.0]}, {\"name\": \"CAV1\", \"ini\": 989, \"clust\": 687, \"rank\": 659, \"rankvar\": 893, \"group\": [669.0, 650.0, 534.0, 310.0, 101.0, 10.0, 1.0, 1.0, 1.0, 1.0, 1.0]}, {\"name\": \"DKK1\", \"ini\": 988, \"clust\": 468, \"rank\": 807, \"rankvar\": 169, \"group\": [465.0, 449.0, 389.0, 272.0, 101.0, 10.0, 1.0, 1.0, 1.0, 1.0, 1.0]}, {\"name\": \"C19orf33\", \"ini\": 987, \"clust\": 948, \"rank\": 10, \"rankvar\": 711, \"group\": [934.0, 904.0, 737.0, 436.0, 144.0, 13.0, 1.0, 1.0, 1.0, 1.0, 1.0]}, {\"name\": \"UCHL1\", \"ini\": 986, \"clust\": 208, \"rank\": 607, \"rankvar\": 805, \"group\": [207.0, 192.0, 160.0, 124.0, 61.0, 9.0, 1.0, 1.0, 1.0, 1.0, 1.0]}, {\"name\": \"SPARC\", \"ini\": 985, \"clust\": 503, \"rank\": 620, \"rankvar\": 285, \"group\": [498.0, 480.0, 415.0, 272.0, 101.0, 10.0, 1.0, 1.0, 1.0, 1.0, 1.0]}, {\"name\": \"TFPI2\", \"ini\": 984, \"clust\": 476, \"rank\": 773, \"rankvar\": 756, \"group\": [474.0, 458.0, 398.0, 272.0, 101.0, 10.0, 1.0, 1.0, 1.0, 1.0, 1.0]}, {\"name\": \"S100P\", \"ini\": 983, \"clust\": 924, \"rank\": 308, \"rankvar\": 897, \"group\": [917.0, 887.0, 726.0, 436.0, 144.0, 13.0, 1.0, 1.0, 1.0, 1.0, 1.0]}, {\"name\": \"DSP\", \"ini\": 982, \"clust\": 968, \"rank\": 741, \"rankvar\": 69, \"group\": [955.0, 925.0, 747.0, 436.0, 144.0, 13.0, 1.0, 1.0, 1.0, 1.0, 1.0]}, {\"name\": \"CTGF\", \"ini\": 981, \"clust\": 514, \"rank\": 995, \"rankvar\": 988, \"group\": [511.0, 492.0, 422.0, 272.0, 101.0, 10.0, 1.0, 1.0, 1.0, 1.0, 1.0]}, {\"name\": \"ALDH1A1\", \"ini\": 980, \"clust\": 832, \"rank\": 108, \"rankvar\": 456, \"group\": [830.0, 803.0, 657.0, 396.0, 139.0, 13.0, 1.0, 1.0, 1.0, 1.0, 1.0]}, {\"name\": \"MIR205HG\", \"ini\": 979, \"clust\": 871, \"rank\": 859, \"rankvar\": 975, \"group\": [866.0, 837.0, 686.0, 418.0, 144.0, 13.0, 1.0, 1.0, 1.0, 1.0, 1.0]}, {\"name\": \"BASP1\", \"ini\": 978, \"clust\": 366, \"rank\": 294, \"rankvar\": 281, \"group\": [366.0, 350.0, 307.0, 237.0, 100.0, 10.0, 1.0, 1.0, 1.0, 1.0, 1.0]}, {\"name\": \"IGFBP3\", \"ini\": 977, \"clust\": 623, \"rank\": 991, \"rankvar\": 240, \"group\": [614.0, 595.0, 506.0, 310.0, 101.0, 10.0, 1.0, 1.0, 1.0, 1.0, 1.0]}, {\"name\": \"SPINT2\", \"ini\": 976, \"clust\": 971, \"rank\": 577, \"rankvar\": 653, \"group\": [956.0, 926.0, 747.0, 436.0, 144.0, 13.0, 1.0, 1.0, 1.0, 1.0, 1.0]}, {\"name\": \"AKR1C3\", \"ini\": 975, \"clust\": 829, \"rank\": 692, \"rankvar\": 714, \"group\": [825.0, 798.0, 653.0, 394.0, 139.0, 13.0, 1.0, 1.0, 1.0, 1.0, 1.0]}, {\"name\": \"FSTL1\", \"ini\": 974, \"clust\": 454, \"rank\": 589, \"rankvar\": 587, \"group\": [442.0, 426.0, 373.0, 268.0, 101.0, 10.0, 1.0, 1.0, 1.0, 1.0, 1.0]}, {\"name\": \"MGST1\", \"ini\": 973, \"clust\": 569, \"rank\": 63, \"rankvar\": 425, \"group\": [715.0, 691.0, 554.0, 317.0, 101.0, 10.0, 1.0, 1.0, 1.0, 1.0, 1.0]}, {\"name\": \"ANXA1\", \"ini\": 972, \"clust\": 658, \"rank\": 109, \"rankvar\": 556, \"group\": [645.0, 626.0, 530.0, 310.0, 101.0, 10.0, 1.0, 1.0, 1.0, 1.0, 1.0]}, {\"name\": \"TM4SF1\", \"ini\": 971, \"clust\": 665, \"rank\": 871, \"rankvar\": 834, \"group\": [651.0, 632.0, 531.0, 310.0, 101.0, 10.0, 1.0, 1.0, 1.0, 1.0, 1.0]}, {\"name\": \"AKR1C2\", \"ini\": 970, \"clust\": 830, \"rank\": 647, \"rankvar\": 734, \"group\": [823.0, 797.0, 653.0, 394.0, 139.0, 13.0, 1.0, 1.0, 1.0, 1.0, 1.0]}, {\"name\": \"ANXA3\", \"ini\": 969, \"clust\": 901, \"rank\": 275, \"rankvar\": 622, \"group\": [892.0, 862.0, 708.0, 432.0, 144.0, 13.0, 1.0, 1.0, 1.0, 1.0, 1.0]}, {\"name\": \"RPS4Y1\", \"ini\": 968, \"clust\": 39, \"rank\": 680, \"rankvar\": 623, \"group\": [40.0, 38.0, 38.0, 37.0, 27.0, 5.0, 1.0, 1.0, 1.0, 1.0, 1.0]}, {\"name\": \"ESRP1\", \"ini\": 967, \"clust\": 990, \"rank\": 744, \"rankvar\": 434, \"group\": [974.0, 938.0, 747.0, 436.0, 144.0, 13.0, 1.0, 1.0, 1.0, 1.0, 1.0]}, {\"name\": \"AMIGO2\", \"ini\": 966, \"clust\": 636, \"rank\": 387, \"rankvar\": 296, \"group\": [626.0, 607.0, 518.0, 310.0, 101.0, 10.0, 1.0, 1.0, 1.0, 1.0, 1.0]}, {\"name\": \"NNMT\", \"ini\": 965, \"clust\": 517, \"rank\": 382, \"rankvar\": 943, \"group\": [519.0, 500.0, 422.0, 272.0, 101.0, 10.0, 1.0, 1.0, 1.0, 1.0, 1.0]}, {\"name\": \"CAV2\", \"ini\": 964, \"clust\": 688, \"rank\": 146, \"rankvar\": 480, \"group\": [670.0, 650.0, 534.0, 310.0, 101.0, 10.0, 1.0, 1.0, 1.0, 1.0, 1.0]}, {\"name\": \"COL1A2\", \"ini\": 963, \"clust\": 421, \"rank\": 7, \"rankvar\": 981, \"group\": [413.0, 397.0, 351.0, 264.0, 101.0, 10.0, 1.0, 1.0, 1.0, 1.0, 1.0]}, {\"name\": \"KRT7\", \"ini\": 962, \"clust\": 904, \"rank\": 81, \"rankvar\": 527, \"group\": [899.0, 869.0, 713.0, 432.0, 144.0, 13.0, 1.0, 1.0, 1.0, 1.0, 1.0]}, {\"name\": \"IFI27\", \"ini\": 961, \"clust\": 308, \"rank\": 581, \"rankvar\": 873, \"group\": [311.0, 295.0, 253.0, 188.0, 79.0, 10.0, 1.0, 1.0, 1.0, 1.0, 1.0]}, {\"name\": \"TSPAN8\", \"ini\": 960, \"clust\": 782, \"rank\": 745, \"rankvar\": 168, \"group\": [780.0, 754.0, 613.0, 365.0, 128.0, 13.0, 1.0, 1.0, 1.0, 1.0, 1.0]}, {\"name\": \"VAMP8\", \"ini\": 959, \"clust\": 857, \"rank\": 764, \"rankvar\": 999, \"group\": [849.0, 821.0, 675.0, 412.0, 144.0, 13.0, 1.0, 1.0, 1.0, 1.0, 1.0]}, {\"name\": \"HSPA1A\", \"ini\": 958, \"clust\": 347, \"rank\": 260, \"rankvar\": 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