{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "** Figure 2: Global fragment size distribution **" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We start with creating the heatmap and histogram shown in Fig 2a. For this, we use the output files of Picard's CollectInsertSizeMetrics." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "%%bash\n", "wget http://medical-epigenomics.org/papers/peneder2020_f17c4e3befc643ffbb31e69f43630748/data/fragment_size.tar.gz #if needed, update with the path of the downloaded data directory on your system\n", "tar -xzf fragment_size.tar.gz" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We also need to load details about the samples, both clinical and genome-based:" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", "import glob\n", "from matplotlib import pyplot as plt\n", "import numpy as np\n", "\n", "clinical=pd.read_excel(\"../tables/Supplementary Table 1_Patient cohort.xlsx\",\"Patient clinical data\")\n", "genomic=pd.read_excel(\"../tables/Supplementary Table 2_ctDNA quantification.xlsx\",\"Genomic ctDNA quantification\")\n", "# note that in these two tables and the files other provided on this website, Rhabdomyosarcoma samples are encoded as \"Rha\" instead of \"RMS\"\n", "\n", "non_ews_cancers=list(clinical[clinical[\"Sample type\"]==\"Non-EwS sarcoma\"][\"Sample\"].values)\n", "fixation_excluded_samples=list(genomic[genomic[\"Excluded due to fixation (1=yes)\"]==1][\"Sample\"].values)\n", "size_selected=list(genomic[genomic[\"Excluded due to size selection prior to library preparation (1=yes)\"]==1][\"Sample\"].values)\n", "controls=list(clinical[clinical[\"Sample type\"]==\"Healthy control\"][\"Sample\"].values)\n", "\n", "ews_samples_to_plot=genomic[~genomic[\"Sample\"].isin(size_selected+fixation_excluded_samples+non_ews_cancers+controls)]\n", "zero_perc=list(ews_samples_to_plot[ews_samples_to_plot[\"Combined quantification: % ctDNA\"]==0][\"Sample\"].values)\n", "upto20_perc=list(ews_samples_to_plot[(ews_samples_to_plot[\"Combined quantification: % ctDNA\"]>0) & (ews_samples_to_plot[\"Combined quantification: % ctDNA\"]<=20)][\"Sample\"].values)\n", "morethan20_perc=list(ews_samples_to_plot[(ews_samples_to_plot[\"Combined quantification: % ctDNA\"]>20)][\"Sample\"].values)\n", "non_ews_cancers_to_plot=[x for x in non_ews_cancers if not x in size_selected+fixation_excluded_samples]\n" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [], "source": [ "# Turns Picard's output into a python dict\n", "def get_frag_distro(fraglen_histo,cumul, start_from):\n", " fdict={}\n", " total=0\n", " with open(fraglen_histo) as f:\n", " counter=False\n", " for line in f:\n", " if line.startswith(\"insert_size\"):\n", " counter=True\n", " continue\n", " if counter and line.replace(\"\\n\",\"\"):\n", " size,nr=line.split()\n", " if int(size)>=start_from:\n", " total+=int(nr)\n", " if cumul:\n", " fdict[int(size)]=int(total)\n", " else:\n", " fdict[int(size)]=int(nr)\n", " return fdict" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# A few basic settings:\n", "insertfolder=\"fragment_size\"\n", "relative_over_zoom_only=True\n", "zoomed_area_start=100\n", "zoomed_area_end=450\n", "log_vs_ctrl=True\n", "\n", "samplenamelist=[sample.replace(\"_insertsizemetrics.txt\",\"\").split(\"/\")[-1] for sample in glob.glob(insertfolder+\"/*insertsizemetrics.txt\")]\n", "distrofilelist=glob.glob(insertfolder+\"/*insertsizemetrics.txt\")\n", "\n", "#this stores the fragment size distribution of every sample:\n", "sampledict={}\n", "\n", "for distrofile in distrofilelist:\n", " samplename=distrofile.replace(\"_insertsizemetrics.txt\",\"\").split(\"/\")[-1]\n", " if samplename not in list(ews_samples_to_plot[\"Sample\"].values)+non_ews_cancers_to_plot+controls:\n", " continue\n", " fragdict=get_frag_distro(distrofile,False,0)\n", "\n", " # In case a value is missing in the provided histogram, fill it with 0 or the previous value\n", " fragdict_full={}\n", " for i in range(0,801):\n", " if i in fragdict.keys():\n", " fragdict_full[i]=fragdict[i]\n", " else:\n", " fragdict_full[i]=0\n", " fragdict=fragdict_full\n", "\n", " # devide by the total if relative\n", " if relative_over_zoom_only:\n", " allcounts=sum([value for key,value in fragdict.items() if zoomed_area_start<=key<=zoomed_area_end])\n", " else:\n", " allcounts=sum([value for value in fragdict.values()])\n", "\n", " fragdict={key:100*value/allcounts for key, value in fragdict.items()}\n", " fragweights_for_plot=list(fragdict.values())\n", "\n", " sampledict[samplename]=fragweights_for_plot[zoomed_area_start:zoomed_area_end+1]\n", "\n", "for sample,col in zip([\"EwS_7_1\",\"EwS_7_5\",\"EwS_7_2\"],[\"red\",\"hotpink\",\"coral\"]):\n", " plt.plot(list(range(zoomed_area_start,zoomed_area_end+1)),sampledict[sample],alpha=0.6,label=\"%s\"%(sample),color=col) \n", "\n", "# Plot range of healthy controls as grey area \n", "ctrl_y_vals=[]\n", "for sample in sampledict.keys():\n", " if not \"Ctrl\" in sample:\n", " continue\n", " ctrl_y_vals.append(sampledict[sample])\n", "min_ctrls=[]\n", "max_ctrls=[]\n", "for i in range(len(ctrl_y_vals[0])):\n", " min_ctrls.append(min([yvallist[i] for yvallist in ctrl_y_vals]))\n", " max_ctrls.append(max([yvallist[i] for yvallist in ctrl_y_vals]))\n", "plt.fill_between(list(range(zoomed_area_start,zoomed_area_end+1)),min_ctrls,max_ctrls,alpha=0.15, label=\"Range of the \"+str(len(ctrl_y_vals))+\" controls\",color=\"grey\")\n", "plt.legend(fontsize=6)\n", "plt.axvline(167*2,linewidth=1, color=\"black\", alpha=1,zorder=10,linestyle=\"--\")\n", "plt.axvline(167,linewidth=1, color=\"black\", alpha=1,linestyle=\"--\",zorder=10)\n", "plt.ylabel(\"Density in range 100-450bp (%)\")\n", "plt.xlabel(\"Fragment size (bp)\")\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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\n", 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0zOxmc8sf/OW0SUiYAJdc9c5pkzDTUBVGmnVeE6AAXqmqpwJnAL8pIqeulpYVsVF2lLH7B4d5Rp6mnUUog9quwMDtfetsOCxQRr7zxtnXiLfv0EJqmxABisiWo2VHUr0jfvZlwT1hdP1NUILmUGYuLGllI+KNGSo7oXjiI3uR8LWWCkHQiVb/Rdt01InOjTdtTXMjdEEcJDse28uCsIrtK2YkmKH77lIKmik2r2U8mnW8Jwrf2vg+sU1NZSdimm1gbI3UaNNeCNh96S1c+4vbG+267FDqMRdxO4jtpdrB2NtjtuuWQCP0Rat8sTHiui4XpC43iPg9XWErBreujhVSWLXmSVVvAW7x97tF5GrgeOCbqxlvZmU2CQkJQUC86EZ1pIhcFj2PpXIJEJGTcCFC1ydv1KGEbPv2aZOQMAGybWmd1hLLbDZ3TJLKRUS2Av8A/I6q7lotLTO72ez8o3M72ZSEjYX7/+4bpk3CTONA7Wx8ju9/AN6nqh8+EFpWuNkourVAcuuSzomiKhT7cieP6amr83IYWwgMMigEs6mgN1eweX7o7GHKjOEwx1phfn7EXF668iJj995554YkisksWWYRAWuFYpSR5a7MmV0IRUiEZ1ziPGsNd37gs+z4uaeihSClIAP3mS24S2xI4QL5glaf2UAxpbO5wacdwaq3w7G1zQ2Are1wxuw/xNnGuHAapronc3Y2NhfU28iocfKVbGAp+8aHfxCsD+Vhe372fViIEN7D5rXMxvaoUrbUZeptbwTbV8p59XIe63zVDLWQoOcyy0kWbD4iO5IgmysFSj+fQ0EKcelwrLe3KV0qHDOgsmPC1ulxTIFPk+PmU0q4/luf4n4nn1nNoykiWxx1/aUMtk+2nm9wdjuqzp4lpNOJ18Kne2msWWx/02EP1XiWsDYd9SJgBIxxdjYG1Kdq0Z7x62XQTMbsqVRAM5880NtUjUGI+sBN+1b3y6kq2FV6fYuIAO8CrlbV1WXJizCz2qhdH/3MtElImADXf/f/TJuEmUY42axSG/WTwK8C/05Evuav/7BaWmaWjUpISPAyG7tKTZbqFziIfvhps0lImGEsIyBeV6xss8kUM1ciRskyiy2db1KI8yJGEVHU4lKvRKE97ShjaIXRIEetoCMDIxdvZmTm2Q0uFKgFGblPxZlMVGFRvJ2MBUaRQYLULLzzAQJ2vvR36N2ej9lC2J46GUiH7YwS8eeVjYM27B0gMikJtkUS2sfP0b1RMIp4GyLxfmTGz5f4VMIS0txKnVrYdBhzZL5/P+qzGBzP3poDazDGVn5spYojU9Sl38GlMI7bi2jlh6ZeLqYKhRW/5mFyXH2ncD7EdInm/phHvZQfnOSMZILbUTXhoa2NjIA0Gqdle1N/6fYkLDFBbfutGHEcoHa8HV8m8VoT/g+ENurXT6O6mpjwfV3aaInKtUopLf4dxTdWl1TOpXI5FDebhISEQw7TCG7ehZkVEN/49j+fNgkJE+CHb3z7tEmYaQQ2apUC4oOKdLJJSJhhKEKxSgHxwcbKNptSsHtzyBSbay2T8fFj1NYyDw28dc/x49lcSa9X0usVWGsYjTKKoZ8Ez4PbYQalsz+p+ORwBLQ4X6aydjpxdhURS+79Y6rwJr1u/5WuGK9jiE6eVXv/neo4xtLqEndqjdUaA61ceLp9gqK68VSv2pAdaDvGcJBpdH0fpfKNqqqs1GMoVSxdMzS1n1Ep1fcWBRPSGbdECXHalGZhJPeSZpPerb3uOM2rwSJLuuKhW7KlRcde6k+o5fPUaB7q1P/3CaKdtizRl+nCajVKKbvCmmPHmU+dNgkJE+Dwn07rtJY4dE82hxAO/9mfnTYJCRPgPmemdVprbJSA5yvabKQU8ntzx0JlVGo8M3LslO0rZFl1JBevDlWjlCNDmeUM+zliIktxA1lekucl+TYXHnQ4bJIVqwutFYxXFQf1sPXvCe4KZWm49iXncfyfnQMD48zqF4wzod8vZN603gzFh7YMIS19eEulykDYMI/vmhN//K00ozZiR0oq0/uqLVDOC2ao9PYWLixkqc6sXcBm3gw+fN9MKjG+zWu1PDhzdhcawrGvFbvlQ0M4FwZnDh/YFJeBFGxPKPtU4UfLvqu3OTWrE2WuDPSLdWYJpnDvMCNfXuBDhqqbTyVyTyAKD+raSenm/CsXv5nH/czrfOhR78pQujmTwoUODS4OqCKFd0FouCr4zyp8q29jtXZLKEu0KovrfTjb0kb9rGsLYBUt/R9D6LccRJAsiAjc4klmoNfz1QI9/zduMjduliEiqCpijAsnmmdVqNPbbh8u/94OKKSTzVqjvGf3tElImADDQVqntYSqUCSZTUJCwlrDnWzSZrOm6J903LRJSJgAWw87ftokzDScgPgQ3GzUQLnJp9/N1KVX1Vo1K4W4bBVIFW7SpQ4RtK8uFGUpLtSn9SpY/zjybZsvlGZ4xVjlC003AWp5AsCxr3w57JZKpqKZYg2Uc60xiFXZ7fdHL2qpwjvVmkKdcjUeQ5r96rEj1X/jfYwP3iC4qUYeI7vR1audjVYhU7WvmH3GrZGXLQU5TyO0prTKAoyX7QCat+ejtWZh7iJ1d6VmB4553Cu4BZrhTVvv6wzvuUQbsV2T0t1vSTOB9j0dZghtAnyD8Xqaqm2NyqPndljQgME7Vpt/lw3DRm0MKtYAd77/Q9MmIWEC3PaRv582CTMNxbkrdF3rjZndbPZ8cdWhUhPWEbsuu2TaJMw0AhvVdS0HEblQRG4TkSsPBi0zu9kkJCQ4lGo6rwnwbuCsg0XHimQ285uGPPjHbiQ3LiTooMixiPtUITeWXuZsEgZFTqnCsHCvmMsLNvVGbMpHFNawazDP3kEfq1KFTBgWOUVhKEZ5ZVtjrQtZoEHWU0THv5CKpcWjh2cXsjK0IbJ9kcrUPk5NEpvjL4XOE2hLjlKn2/X2Kt6+JW7XKA/uA8H9IMg1DO5eqcJ4ViEMQtiKQEJkhtPO9CqRMEBLQQ9zsivr2wVZmulZyoXMp9KJBrD1XGIlmk/xcx7NXTyvMCb3kdaamVF9H8at+sQ2StEaLVYf6uJ3BXSmWInXq72GpqPc1PVItH4EuZOTTapvqyE1UXzfDldRlUd0m+aX0N4E9j0dUIVylQJiVf28z6pwUDCz2qgT3nDutElImAAPeOUbpk3CjENWvdkcbGwMKtYAwxtvnDYJCRNg4Za0TmuJZQTER4rIZdH1krWkZWY3m1vf9TfTJiFhAtz8v941bRJmGwqlj8bYvvB5o6KrM0HdwcKK2KiFUc41txyNMRYxivWhI8vChffMepYsL6u0KyF8JKLMzY3Y1+uxqT+itIbBKGcwylEVssy6McWFGy0LrUMjBrlE5mx4NJcqvCbg7EZ8CMXKnsXLEcqt1skUSicXCGESnG+Ou0zp/Xqqe63lA4vIAZazbxmz3WjIBBqCFNfPp1+pxCri5QDq7FjwaWdCWfwTUbm9mOb7K9uZluyhCsORUaXcFQWbqZcrRMN7EU3ju4ZpDvNo3Rev7q2fRz/HDXlZZHsV/J8AttykdX2Qq/nwIdLoP742VTvbfK5oVUA1sh8KsjBhLF5qF0I776+2mJ2NGqnLTbTOfv5DG1dWjxXbYMV1rn1dfvuu1amqNbFRCQkJ6wWXS238Wg4i8n7gS8BDRORGETn7QOiYWQHxfX71mdMmIWECnPDEZ0+bhJnGAWqjfvlg0jKzm83WJz8OymlTkbAcjjzl8ePuAgkHFZNExVgPrGyzGRrM9fPOPiNslgo9n4JVPX9qpea1c/9FC9lEAextbbIqPiyi1P3FRq4jlbzD2ZcIsZ0Klc2CtuQK1//Wq7nffz+vti3JcP5Rfd8g+hizy4gXJ06x0SHDkXAfnm2rXt0YY/49bZnQIj464fXFZiqmN/gWxf5EbbuR1teq5S7+PZpr3d8/V339sxSto3agcRFau6DxF49T4Hhc/5Lf5cQL/mRMLtT8UkRzJo3nSrCktR/cmO1NV93YuyKy2mvcoqfz7yCS47RteeIYQw0fu/bfb7x2QV7jP4vPsyooXm66ATCzJ5uEhARAN04ql7TZJCTMOHQCYfB6YGY3m02nnTJtEhImwPzD0zqtJRQm0jytB1a22fSU0TFDJFNM5tPsqlAMPWOZW0xuXYxhi/dpcvxiNleS9wrm+gUAoyJj5GMN570SYyzWGspSKEetOC9QpXTVoi30wQmJWnz10b/xotpHp7IJ8fYgRbADkTF7kBBbd1H+v4XF/Kh0jDenIZei9amZf/ZTqZlW9jYq8Tha+1gZreU4vj2ZumtoILdOIKbiyoItkrp2lb2SgsldfSPdb+yHRS1oVGt8Gt6wLtJM62PF+T6VIGqqGMQNnyq/Njuf+5+RW2n4sMXrUcWDbtjS1PcNW5ul5C/t++o7Nj/HbF+CbVSYt0puFq1xiBEd1iWr+zdywQU/uUgWg6lFT4GOOHbTUnGLJoJunJPNxpAcrQFu+6sLp01CwgS4+W+TBfGaQxe51hkzy0btv/LqaZOQMAH2ffub0yZhxiEb5mSzos3GZJatO/a7EBPGMiozz/q4A1KelxhRFCiKDFVnqSiibJobMd8fsbU/xKqwd9hnb9ZHVehljo1aGPYoS9cvyy0m82k2rFCUmWOhhqY+cvuwpO6YXR/Rqy+3x3SosqMjdmBTopCYtsdku357/SI1dTNsgVbuCA32iZhVUsi8mrg6Nvv7wCq1Q0v4Z+Pv3Xu9eUAHb1dZz4tSlqZKgwN1ehyoWSW3bv454glVxf0wxip7iUJd+GO7UvdrUBPUvyHsKDA4umzU16EsqNXWUdiKKjxFeI7Hbr1wzOSgtW5ja0b9XK+TbbiSNFidRuiIuix8OlZVER9CRIxnVaO1CnNfr6n7u89Eq/vb5gpWhQ3ERs3sySYhIcEjqb7XFg98y9umwpcmrAwnXvAnaZ3WEkGBsgEwswLiXV/+0rRJSJgAez6fYkWvNUJS0Pa13ljRycYOMvZdu71K5VKb6LuULINca/41yEr8djbI52oZhEq94wYeN6hNceVFpdasd+XG/iw4E3tAe/gZpOLxb//Ih9j6xDMaZRVNYSA/4137fmMt2nx6rA5uqU67iK36LQYvw2ikgZFIgNAlH/KfhdHuL0D0TpU6tGj8XM1D9I7cwsjUv4aKkxEVxvmaiZOVBTmZidPghCEXCa86NlcKd/3dhzn8YT/ZkJW0v2sXNGijDcsfjDpzr0R1Y2U05iQSibXkRLL4uK3hVahcWdT/E4uvKkQpdGKVd7n/AJiQDXKymVk2KiEhASr7pA2AtNkkJMw0ZMOcbGZWZnP02S+cNgkJE+CYX3vRtEmYfdhFrgkgImeJyLdF5BoR+b0DIWNFJ5t8vuA+D76LPCuZy0oGZUZRZuwb9LDW0OsVzOUlIsqoyCisYeRdDzbNjdg8N2Q+L7AqLBQ5ewfOzib3IUFHZUZZGobDvLYNCDyvDzNamd+HuiD7CfIdq6gV5nbubJrHVzYawdR9vK5hg9NCbcYuTXP2gC5zc9/GuRdIMzQGQNt0HSL7mvCO2Gik9enHqMraxMcGKMEeRtxcSmbpzRcM9/bdH16m9dy2U46ooHNlNc/ak1ouE8nZgMjdQDpkHDTnWWH+mJ2YYT3JsTtDY92i9au+UquuUd64l0Z9Y4qUZqjWzvlr3Yehop/qhptDFUqD2rbK3zfsdUK/OPyE0kr54/9GVivQje2SVggRyYD/DzgTuBG4VEQuUtVVWWLO7Mnmhje+edokJEyA6976pmmTMPvQRa7l8VjgGlX9vqoOgQ8Az1gtGTO72SQkJDh4g+Wxi+VTuRwP3BA93+jLVoUkIE5ImGUsbdR3h6o+er1IWdFmUwxy7rz2cCdjyG3Nx/ovs9C37O2VLvwEtZwl+OqUKgzznNK6tLwLCz3U++WIsZSF83/ShSzi7YOhARgrSEHjvSEMAVDz9Ba2n34G+b7YbkVrOUJVNm6nUfPULXlKkLcQ3XvZRsV3U5e5flqnzzWKhDAOUTgH8b5Nee79YXxq4+ATY4L/jCiZsQjQy0rUz0ton4n7DFHZVOu0xnE5uMhtfZ8m2apLPJ9HBjNWhZHPERMSmqn/LNWlBhmVLsxESFBvrbo3TFQAAB51SURBVPHGYkJZ+ntrKh+peI41OsZv/anHMDxpEFVSy+van7HcpR0ytAutte6+j2Ve1DKzSMZFw//MmUAh6pq0/JyCb1P97NqF0B2hLEY7q0yd8UX9s3LzllX6RnFAqu+bgBOi552+bFWYWTbqvs947rRJSJgAR5z9i9MmYfaxem3UpcDJInJ/EekDvwRctFoyZnazuf6vzp82CQkT4JZz3z5tEmYai8lrljJoD1DVAngpcDFwNfBBVb1qtbTMrMxmkHJIHxIYXnfztEmYfRyAUZ+qfgL4xMEgY0WbzY6te3n64y8HoNCM/WUPz5VXPGnPOFnAoHRDj9RQ2IzclGzNh2zLF7Aq7CrmuXOwhYWyx6h08oFdwzkGo5z9gz7gePuyyFwGv5FxoSd9ql+xAgV12EhwMpwSxIditH2t+HZni6Foww6jtg1xz/Guv8QCVTYRwUGnrur6xei0x1Ea9hWBhDIOIxmaelsa216tSF7U8EkLLw0xarwMorZhETTTurxc5Ouqs6OxfSXbL3V4T6hjzkT2IeH7Z+05aNsltd4197358fdr931XfKJGXVd/utsczMgLbferxbTLoV382UZVb+rncs/qzwXJXWGNkW3bPm0SEiZAtjWt05pC02az5jjpnDdMm4SECfDAV/3+tEmYeWyUzWZmBcR3ffriaZOQMAHu+Ow/T5uEhHXCik429+zZwsf/9XSXurXnmU0LMnKxfu2cz7cr6oRSNhJG9C2SK5K73Lq2MC5uigC5RYzzacIKFFLbOoSUI0E+EuQQuUJOZW9SwTPLd3/mU2x/5pmNMncf++xolWIEqGPdtvsQ8dbtz1C3TJreuK7i1YMtka3LQtqSZp9u4YLNa3mVWMGMQgc/hvf5iX1xAk2aSTP9bhb1DXR7mZDskWZq2coGqjlmRa9dfA7afkt3fe5THPeos2qZT+W7Rp2iJU7JE707jjktVsf9qOI1rvpo/f52LB6t65rl8bPWz7a+75TDBHkWzTbx3AKVoU0l9zHBj672p7tp3wTqoy4kNiohIWHdkDabhISEtYZwqJ5scoscPWhH1axSdzi3A1dYaTmjmIrGKJlPzxKyX7o20XgqlIUzhQ+m6xqrWRdhT6oydWzHMa9+GYSMlxanFg9H8pBhsWylCQmZM7vYhMXe2UVDm7OLQw54c/fKxUHAVmletEotE2dbrNwiQqbFEFaiK41IfI4PKUUC+1m2VPVBR10Ydx/KKzase37RiD0OhIawpn4ex0Kx0mStQtiD41/2O+w71rNL/h3NMBP1OM0smO1xpcm+0Kpvf4+O7zhmotBV11bjx2VROInQ34Y5lvE6bXzW7SqVd7R+wytWqadPbFRCQsJ6YaNsNjOrjfrheX8xbRISJsBNf/Hn0yZh9qGLXOuMdLJJSJhlHLJsVCnObDrT2tQeKtWx5hbJnAu90zr68BKCV22D9aEJVAX1aSsq1TZUYQogrqvlQ5UcIiDICSJaNDTOFS1BjSClVrIEMt9eHE0Gqd0Y/HAVTx/z/S3XhIZcZyn5QEDE78cq00qWo9Lk+wn30uxvmvdSuk/bV/K9NW+vhlbI0ZoUmyua+zIbyRsiGUNDZR6rxGP1cjsVbvjjrmRfrfCgbfkLMHe31HWx3Mw2VdxitTlGkA8RtSP6z6W1OjsumxgdYpJYxd1upz42ROxm0E65XIU1EanWxtVJXRfWt2pLbdawChyam80hhO1P+5lpk5AwAY54wlOnTcJsI9qQp42Z3Wx2PP2pU+FLE1aGo550VlqnNUSs6Jo2ZlZAfNPvpYDnhwKu+cvfnzYJM4/VxrNZckyR54jIVSJiRWSi0KIrOtlk/ZIdx+xGRMmMMiwyd0rzoSEzY6tQlIU1VahIERfKMs8sfZ/KZVhkDIscValCYI5GOWXhQlI0QiUEjKVykUgW0JQdlPfuRkZxfZil6Ic02LmIlwVkzvYmtNcwXsAiC7RU2IKKv4/kH+0QAmP2HNGAjfHiEKVBvtSy4bF99eljvPl7Bmbo7I3U1PIUgmxAQbxsByIZjIWxDCdtWxjfLp4DiVxUxsJBMP5c7NlVy63w7zRUoUObrgfSmcql7WrQdC+Qif5jjXmEdMjNRLUpPxtbN3/fTuUSr3VX+pdl7H1UOuhbCdaGjboSeCbwzkk7zCwblZCQwJppo1T1agBZLOdWB2Z2s+nvXHXGiYR1xNwxO6dNwswjaaPWGMe+5uVJ8HgI4P4vesW0SZhtLH2yOVJELoueL1DVC8KDiPwf4JiOfueo6kdXSsqKNhu7L2f/1w93Nh1Rz/BlbA8XfiLzzL2VyrdD5yzSt+RzRSXIsNblI+33C7LMNvym2oMH/yhbuLpgmxNS8mocHkCFu97zIY74pedUvlHBD0oKMIWTK0hJXR+ey6bNxpK+WBWN488NvxdT20+ocXKUhm9U5m1e8HXGPbs22kwLA7VPU0gR49tJ1EbEpYPJc0tRGJdiROpUI8ZoZQdlrdD3aZODL5tLBdP80lbd2lifzkUVn7ZFXOhWFbQUt0aVfI06PXKQh4WUPCrc8cG/5+hnPae2qSn9WkW2OrV/W2SDE1S6Qb6m4uxwguynLS/qWMfYXkbCP+rXJZJZVesAhKQ0GoXvqG2U/DzldZmN1hVR9xzSB3nftna63fB3Ufm9Ado/gF/OxbsumTdKVQ+q/cjMaqP2fPHL0yYhYQLs/sol0yZhpiG0flCja70xs5tNQkICBMvrrutAICK/KCI3Ao8HPi4iy4bGnFmZTUJCgsMaaaM+AnxkJX1WttnMW3joHvLM8fxl5efkqvu5xRhb8fDBx0nExbHJjSX3cpmiNAyLvKpXFYaD3MkEitqwIMS4oZCK9ycqM7Gtha3lAvc75/Xk+1t2Np5Om0fyHWobjgY6jDPGfIy6bCO66iCykYn48NAmxKWJ+1X+NZGsxrQEDlClgq3e5f3NUMFqxrDMxgyB1HrbmiCfscIgyMDC1EQ+T/V9bYNTr0WH6rOyswlyDXV+X7kzXlIU6TkByXF/fA6j7WVT7hXbTYUJjGUu3lCpsumRDhlbTC+1fKa9rE2bltYa0LGu1b226nVs7aBjXelq3yIuKpfF+q8AG0UbNbNs1ODGlKTuUMDw+lWnjk6YBJGAPcls1gg/fM+F0yYhYQLc8VfvnjYJM43qMN1xrTeSzCYhYcZxoMLgg4UVbzYhjvB8r6AoDaU17F/oodbQ65XM5SWZsYxKw6jMGAx6qMLmuRE7Nu3nsP5+APaM5rhz3xZKK8z1CnrGsr/fY2GUs7C/7+PgaGXrYEtTpeGtZAvWx8QJdhwqzhgkks1IZevhd/mSitdvxLolOl4qBCZ5SR4/oMOXpSGXEaI4JVLFjGna3jievYqF4u0yxAhaCSL8oNm4AKKKGyRUtjLifc7i2M/GKEWRoQq9XslgkKMYTGbrmEEqWCN1+B4/38HWSUMQ5Ya8rLalCTY0VZqZttwstPeYvzVv1NepXOp1ieVy8ZhNuVvLvqYh4uqQ04X1qSexblOtX2yIE7dt9m3HGIptrKr3tP424vLqHUrtRwWVrE+GqxTaeNuljYCZPdkc8ZxnT5uEhAlw9NOfM20SZh4bRUA8s5vN9sefsZTlZMIGwY5HP37aJMw29BBlo/Ks5PCt+7AqFGVWle3YVmD8uTSYshuBubxkc39UqbZ3D+bYPZir2hWlOy8Oi4wF22NUZpS+zFqD2nB0924JllaIiZoliu9F4dpXvIoHvPVtY2br4dgqQRUdzNP98XWiX4G26rqjrju9hzZTecReGZFKt+KQPPsShtQQ46GsVdCqONbMuy00/qyMce4IBopCGwQbYxnh2CqLM2WI3RWsNQ3XBRFv6uBNGmzPVipxLaVxX7G1nSl4Qvocrdbp/m/706jcf9/YLSEINePxGK+v0Pl/a1wNHld1hUBtskaRqjtmiWARVknrNRZaKXecOUAjTEWs9o5V4mFd18ZdYV0xsyebhIQEJ6s6JE82CQkJhx6SzGaNsfmUU6dNQsIE2HTqKdMmYbahuMwiGwAr2mz6WcljjrqenpRYFXYVm7AqjNTQE8uWfMCcKQDYX/ar8jkz4pi5ezkq380x+b0MNeOHxQ5uG22nVEPmt957i03sKua5fWEr85kbZ08xx7DMuHcwz2CUs3/Qr9K9lKWpQxrg5TtDg4yEY154NlJCtiCYEeT78Z+KGSmiiikAhWzkjppmVKvN4xQqouplOkIIJaDtCGXS5NnrcKCCDSEEfAqPRviBqtwNo7mp1eRE9T6sR0jPKxYf8tO1Kedw4T38u6Wo5T9VuAqowjjgRStiwZRSiUIq0YGfG7GQlYCFnv80BWQDdfM7VNdm5D7NSDFDi5SKKRQp/THez6GU1stmLFg4ee458He73Hf3oTcrhPsqnEM059X8SPVZy1DEtZW6jRrxauRalV2thXH1DfcR39/NfTQW3errMTlQ/KcRq+Dbav2SOkVN5XKhDbmWCtx5Z/fYk2CjnGxm14L4b941bRISJsDl33v/tEmYfah2X+uMmWWj9l39zWmTkDAB7tj13WmTMNvQjXOymdnNJiEhwWvSD0WZzb5hn8/d+CB6eUkvK9k36FOqMBy6lCz9fkEvK8mMsn/Yoyici4ExyhHb93Lfzbu5/5Y72W/73LhvB3fu30wZhQDdvX+O0TCnGORI7mw/rHWhJnWQgRWk8FcIH6kR++5Dewa5iymcHKPMBDsXyp27QJMP9zKBIDuJw0H46trdIDJ8iW0mFmNIxVLbV7Rs5Lu84YIbQAg7EIWGDH3El8UuCvgwoMbbZZTeHklVEGPJQ1pkFUajzFnGR24IoU6DHVMRbFqC7ZJUoSWk9KFVvXuCI6u2gRGbN0N69NTLKrw9kK3lSVwO1z7zsEao1GpWxuxZIluXxdo05j6yXWlPdZddTbt91eYA/7O2bIAk5GaJbI8qO6PYjsiHz1CB4dWLCIQmePdaqL5F5Dzg54Ah8D3ghap6z1J9ZlZmc/Kbzp82CQkTIK3TWqM7St9B2IA+DZymqg8HvgO8drkOM7vZ3HvZl6ZNQsIESOu0xvCq767rgIZV/ZSqFv7xEmDZnDwzu9ncdtHfT5uEhAmQ1mkdsLg26kgRuSy6XrLKN7wI+ORyjVYsIF4Y9iisYSA5oyLzfH/N8xfWUFgqWU3uQ4WW1nD3YDNWDYUa9o76jLx/lRH1qUEcLy8+HIIbFzDqQkpal/5Usy7fGxmzYSg2Bf8ZrcUjY/wz1LKGpmilKSypy7rCSy6FztCSkT1PbJvT6CPRfdw201q+4e/VKKWh8qchCuGAwCi3SAhtUbp5DamRdWiqkJ0MTS1XCCEionluyBWCXMOLl8S/S9Fa3kOkDRFvN2J0PICTjaKehn7xmnl529g6xjYs2nxulHe17UL4ThEpY35Xi62jr4tFcmPypeWgNENMhLEOIEzEEizTkqlcJskbJSLnAAXwvuXoSNqohIRZhgKrZJmWyxslIi8Ang78tOryhjszu9nc90UvnDYJCRPg2Oe/aNokzDQERezBN7QRkbOA1wBPVtV9k/SZ2c2mvzPlkD4UMH9cWqc1xQGcbJbB24E54NPiXEAuUdX/slSHFW02WggLd2xyzHVPq/SqMnJ8/qBnIfD+3l5DCsd07p6zmPmC3pwTYJdFRjl04SnF24DYYQaFuPFost8V32xrfr6yqYlkA6HdDW96Mw/4k7eNyz0M3TYZrXeN+bssxuRPwIfHMVDqQsZkA2NEBPh4O1XclDi9RxUnpWX/Y5pCEREnqwFcONWQthdcmFHxBPW9vKwU6Lv3aiz/CbKbMNaisg/n51TZKwWbIf99gk3L9ee+iRP/+q0R7S3BVWybFMY5mP93llq/jtQuKxpzKTp1gnaRfdaBxLORNXBNUNUHrbTPzJ5sEhISANQ5vW4ApM0mIWGWsXZs1Ioxs5vNtseeMW0SEibAlic8dtokzDzWQkC8GqxoszE9y8NOvZ75bIRV4Y79WymsYf8opygz+nnJXF4wlxfsHfYZlQZrDXO9gkcfdQOP334ND+3fwk3FDj51z8P4/p4jGNmMwhqMKHft3cy+hT6jQc6Jx9zFfD7i5l3b2bd3HntPHxkK2UCa8WmhYe8h1tliHPu056IDKr57SduY2K4jtpsglqW0GPeOwbrsaSqfqlhW5OUrtqeQUcenhTrubN9iMqU/N6rSsICzSdo2P2AuL9iUjyisqWICbc6HbO0NALhnuJndQxfv+ahNe9iWD7AIu0dzXL/rcEZFxqjM6OcFIooRGBQZCws9H/+5lsnYUVbHf64MP/DpcDoEGtHftrO9qSdTjTq5HG5Bjn7mc2FftD6xDE6b4zXclII4pf13EGESW6hOeVooN4uY1UhtC9MQMfl1rGIX27pz5VcXv6AtywInkzRay+jEy7dWezhRhXJjbDYza0H8g79OPjeHAm46/8+mTcLsI8WzWVsMbkm5vg8FDG9Mub7XFMqGOdmsaLOxheEb39uJ5Ja8V7rjtuJU1gpmrnRHflHUuvAS4Tj+f/edzBf7J7F1bohVYVDk7Bv0UBV6VRbNrEofcv0P71PdA7B15MMjRDEIoiyMY24LQDmvxFkvFc9mxW4N0TF8MXP3MXi7/E5T9MVcDCRil3wISzNy4TjjkBZxRkwLLJh+PWbm+u9iG1VsDa+2Dm4dIewEUKVnudkc5lglf1wXcRkye5mzgQ8s8HyvYHN/VLWJw38El5TCZzq1VrDWVKEsrA+TYMtWmIqwTtRzHVK2VCEocs9RgGfN2nb+NPrDYmvX4eZAqw2tusjNoCrvcFdYLm1Pw70kq/s2QmD4lDtVHyP+lRGPH6V40XZ4kVVBwW6MlJgze7LJtm+fNgkJEyCt0xrjUD3ZHEo48fVvaAgqEzYmdv7B66dNwoxj49jZzKyA+O6LL542CQkT4J5PpHVaUyhQlt3XOmNlJxujZHMlJivp90vPtwtDLzvJMkuvX5BnLqREURiKwsV77PlUvFv7TjW7z/QpSkOpwlyvoB/CidKjyGr+1bG6ilUn/2mYzluF0qeorXKhOBP5ez79KQ4/66k45td9OFmNe4jdHQL/Lz5NyWKq1ApLmrjXvHr1aahTgviULCLqPo0XPeVeRZ979WkeTPu1Vo1mLiRoHRbUjSM+HGidQhevznb9cj+34bmfuVQ8AYMidypwoPTlbXkN4NbLRumRFdQaJzrxKXi1NE5WU6VCFheqQn0oV9uUm937z5/mqCeeVYUNjUO7BveTWO4W7sO61elPQplWz51hRZZYt+r7Vusnzbr22oKTt1XhZKW+Fye7CfIb6+Vtmkn9J+nbitFG6pkqg01QnQt0C40mxBQ0T12YWTYqISEB9+M7hVNMF9Jmk5Aw60gC4rXFcS//nWmTkDABdv5mWqc1hepU5DNdWNFmI0Y57sh72NwbMp8V3LWwmWGZscsoZWnIMic7CPIaWzr+3mQlc72CHfP7OXbTLgY24zbdxqCfUVpDLysreYIx1rWfK8iNxXobjtEow5YGzaUOlSBShV+oQlECEqW4jaE1W1zx1Q0zCwGbRbKAUElrrC4WOJIPeJOZ+j0RH1+HjpQqlW5IAVuFhBSwQYbTI7K98SFAe87GxmZah5jIXDjVrGedPMgaZxczyDC5JeuVLsyEFcqQrrhKvxKZyHvZgMYhJEK7EN6jFGTkZTCFuIgWJVXaX1Pg7WWiuYxcTIKdjSjIHcJm07LD8Wlnx+xj4v6teV8yzOcS6ArBSZiGyGap7Yoy/hzJXLL2OFS2VVUfv9YuTKo0vkds21N5NAyX/h5LfMM1YaNE5M3AM3A639uAF6jqzUv1mVlt1C1v+/Npk5AwAa7538ldYU2hOEVK13VgOE9VH66qjwA+BixrwzCzbFRCQoI/DK7ByUZVd0WPW5hA55c2m4SEWcYaaqNE5A+BXwPuBZ6ybPsJgqLHg+8Gvr1q6tYXRwJ3TJuIhGWR1mkyPERVt620k4j8M26OuzAPLETPF6jqBVHfZVO5+HavBeZV9Q1L0rLCzeaypfLMbCQcSrT+KCOt02TYyPMkIicCn1DV05ZqN7MC4oSEhLWDiJwcPT4D+NZyfZLMJiEhYTV4i4g8BKf6/gGwZBoXWPlmc8HyTTYMDiVaf5SR1mkybKh5UtVnrbTPimQ2CQkJCatFktkkJCSsCybebETkLBH5tohcIyK/t5ZETUDLhSJym4hc2Sr/LRH5lohcJSJv9WXPF5GvRZcVkUdMh/IfLYjIvIh8RUS+7tfkjb78Xb7sChH5kIhsbfV7loioiGxI7UvC6jARGyUiGfAd4EzgRuBS4JdV9ZtrS96i9DwJ2AO8N6jbROQpwDnA01R1ICJHq+ptrX4PA/5RVR+47kT/CEJcEugtqrpHRHrAF4CXAd8MFqgicj5wm6q+xT9vAz6OS/77UlW9bDrUJxxsTHqyeSxwjap+X1WHwAdw6q6pQFU/D9zVKv4N4C2qOvBtbhvrCL+Moz1hHaAOe/xjz18abTQCbKJp6v5m4E9oGpslzAAm3WyOB26Inm/0ZRsJDwaeKCJfFpHPichjOto8D3j/OtP1Iw0RyUTkazjP4E+r6pd9+d8APwQeCvx3X/Yo4ARV/fi06E1YO8ySgDgH7gOcAbwa+KD/5QRARB4H7FPVKxfpn7AGUNXSewbvBB4rIqf58hcCxwFXA88TEQOcD7xyasQmrCkm3WxuAk6Innf6so2EG4EP+6P7V3DGRrFPyC+RTjVTg6reA3wWOCsqK3Fs7bOAbcBpwL+IyHW4H42LkpB4djDpZnMpcLKI3F9E+rj/uBetHVmrwj/iPU9F5ME4AeMd/tkAzyXJa9YVInKUiOzw95twCoZvi8iDfJkAPw98S1XvVdUjVfUkVT0JuAT4+SQgnh1MZEGsqoWIvBS4GMiAC1X1qjWlbAmIyPuBnwKOFJEbgTcAFwIXenX4EPhPWqvangTcoKrfnwa9P8I4FniP12Ya4IM4TdO/ish2XMy6r+OE+wkzjmRBnJCQsC6YJQFxQkLCBkbabBISEtYFabNJSEhYF6TNJiEhYV2QNpuEhIR1QdpsVggRKVte5CdNm6alICK/ICKnrqD9o0XkLw/wnSeJyH7vphCeV2S5LSIvF5HrReTtB0JLwsZBCgu6cuz35vedEJFcVYv1JGgZ/AIuidhEHvreiO5gGNJ9b6l5moCOPxORu4FkQTwjSCebgwAReYGIXCQi/xf4jIhsFZHPiMjlIvINEXlG1PZcHxfoCyLyfhF5lS//FxH5MxG5TESuFpHHiMiHReS7IvIHUf//6GPEfE1E3ukN5hCRPSLyhz5OzCUicl8R+Qmche55vv0DW3Q/R0Su9H0+78t+SkQ+5u8/EZ3g7hWR/+QdK88TkUt9PJpfn3CachF5n/9uHxKRzf4d14nIW/08fSVYFyfMHtJms3Jsiv4DfiQqfxTwbFV9Mi48wi+q6qNwLhRvE4fH4PyAfhz494z/ag99uo6/Bj4K/CbOX+gFInKEiJyC81z/SX9qKIHn+75bgEtU9ceBzwMvVtUv4txKXq2qj1DV77Xe93rgZ32fn29/UVX9D/49Z+OCWv+jv79XVR8DPAZ4sYjcf4J5ewjwDlU9BdgF/Neo7l5VfRjwdiDlTZ5RJDZq5ViMjfq0qoYYOwL8kbggXxYXjuO+wE8CH1XVBWBBRP6pNUbwN/sGcJWq3gIgIt/HOcI+ATgduNQ7tG/ChW4A56LxMX//VZwf0nL4N+DdIvJB4MNdDUTkSOBvgeeq6r0i8lTg4SLybN/kMOBk4Npl3nWDqv6bv/874LeBP/XP748+U/LvGUXabA4e9kb3zweOAk5X1ZH3Yp6fYIyB/7TRfXjOcZvYe1T1tR19R5EvWMkEa6uq/8WH3nga8FUROT2u9yzaB4A3RaE5BPgtVb14gu/TeN0Sz4vdJ8wQEhu1NjgMF+pyJC5c6f18+b8BPycuNu9W4OkrHPczwLNF5GgAEbmPiNxvmT67ceEbxiAiD1TVL6vq64HbaYYRAXgLcIWqxt7yFwO/IS7MJyLyYBHZMgHtJ4rI4/39r+BChAY8L/r80gRjJRyCSCebtcH7gH8SkW/gNDvfAlDVS0XkIuAK4FYcu3TvpIOq6jdF5HXAp8SFzRjh5Do/WKLbB4D/ISK/jZMpxXKb88RlNhTcRvZ14MlR/auAq4IKGyfj+Z/AScDlPkTE7TiN13L4NvCbInIhTjP2V1Hd4SJyBe4098sTjJVwCCJ5fa8zRGSrDwC+GSfIfYmqXj5tug4mvO3Rx5bL/ezbXgc8WlXv6Kh7ga976UEmMWEKSGzU+uMCf1K4HPiHWdtoPErgsOhEtGKIyMuB1+I0VwkzgHSySUhIWBekk01CQsK6IG02CQkJ64K02SQkJKwL0maTkJCwLkibTUJCwrogbTYJCQnrgv8fQcIhJDgJFE4AAAAASUVORK5CYII=\n", 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\n", 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Now, we create a heatmap of all relevant samples:\n", "\n", "df=pd.DataFrame(sampledict)\n", "df=df.transpose()\n", "df.columns=list(range(zoomed_area_start,zoomed_area_end+1))\n", "\n", "# Using the difference to the median of controls makes the signal more clearly visible\n", "if log_vs_ctrl:\n", " median_ctrl=df.loc[controls].median()\n", " df_log=df/median_ctrl\n", " df_log=np.log2(df_log)\n", " df=df_log\n", "\n", "# Max and min of the colorbar\n", "mymax=3\n", "mymin=-3\n", "\n", "for sampleset,samplesetname in zip([controls,zero_perc,upto20_perc,morethan20_perc,non_ews_cancers_to_plot],[\"Ctrl\",\"EwS, 0%\",\"EwS, <20%,>0%% \",\"EwS, >=20%\",\"Non-Ews cancers\"]):\n", "\n", " # within each group, order by tumor content\n", " samplesetdf=df.loc[sampleset]\n", " samplesetdf[\"Combined quantification: % ctDNA\"]=samplesetdf.apply(lambda row: genomic[genomic[\"Sample\"]==row.name][\"Combined quantification: % ctDNA\"].values[0],axis=1)\n", " samplesetdf=samplesetdf.sort_values(by=\"Combined quantification: % ctDNA\")\n", " samplesetdf=samplesetdf.drop(\"Combined quantification: % ctDNA\",axis=1)\n", "\n", " ax1=plt.gca()\n", "\n", " # set size of plots according to the nr. of samples in the group\n", " plt.gcf().set_size_inches(5,len(sampleset)/10)\n", " plt.imshow(samplesetdf,aspect='auto',vmin=mymin,vmax=mymax)#\n", " plt.colorbar()\n", " plt.xticks([0,167-zoomed_area_start,334-zoomed_area_start,zoomed_area_end-zoomed_area_start],[0,167,334])\n", " plt.yticks([],[])\n", " plt.xlabel(\"Fragment size [bp]\")\n", " plt.subplots_adjust(bottom=0.35)\n", "\n", " plt.axvline(167*2-zoomed_area_start,linewidth=1, color=\"black\", alpha=1,zorder=10,linestyle=\"--\")\n", " plt.axvline(167-zoomed_area_start,linewidth=1, color=\"black\", alpha=1,linestyle=\"--\",zorder=10)\n", " plt.title(samplesetname)\n", " plt.show()\n", " \n", " samplesetdf[\"local max\"]=samplesetdf.apply(lambda row: zoomed_area_start+list(row.values).index(row.max()),axis=1)\n", " samplesetdf.to_csv(samplesetname.replace(\" \",\"_\")+\".csv\")\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Finally, we produce a table of features of global fragmentation, which can then easily be compared to results from Mouliere et al, and used for machine learning:" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [], "source": [ "insertfolder=\"fragment_size\"\n", "zoomed_area_start=20 # for plots only\n", "zoomed_area_end=450 # for plots only\n", "plot=False # Set to True to generate plots for all samples\n", "\n", "samplenamelist=[sample.replace(\"_insertsizemetrics.txt\",\"\").split(\"/\")[-1] for sample in glob.glob(insertfolder+\"/*insertsizemetrics.txt\")]\n", "distrofilelist=glob.glob(insertfolder+\"/*insertsizemetrics.txt\")\n", "\n", "#this stores the fragment size distribution of every sample:\n", "distrodict={}\n", "# Stores fragmentation-based features of all samples:\n", "featuredict={}\n", "\n", "for distrofile in distrofilelist:\n", " sample_featuredict={}\n", " samplename=distrofile.replace(\"_insertsizemetrics.txt\",\"\").split(\"/\")[-1]\n", " if samplename not in list(ews_samples_to_plot[\"Sample\"].values)+non_ews_cancers_to_plot+controls:\n", " continue\n", " fragdict=get_frag_distro(distrofile,False,0)\n", "\n", " # In case a value is missing in the provided histogram, fill it with 0 or the previous value\n", " fragdict_full={}\n", " for i in range(0,801):\n", " if i in fragdict.keys():\n", " fragdict_full[i]=fragdict[i]\n", " else:\n", " fragdict_full[i]=0\n", " fragdict=fragdict_full\n", " allcounts=sum([value for value in fragdict.values()])\n", " fragdict={key:value/allcounts for key, value in fragdict.items()}\n", " fragweights_for_plot=list(fragdict.values())\n", " distrodict[samplename]=fragweights_for_plot[zoomed_area_start:zoomed_area_end+1]\n", " \n", " # Fragment based features, mainly from Mouliere et al.\n", " for start,end in [(20,150),(100,150),(125,180),(160,180),(180,220),(250,320),]:\n", " sample_featuredict[\"P(\"+str(start)+\"_\"+str(end)+\")\"]=sum(fragweights_for_plot[start:end])\n", " sample_featuredict[\"P(160_180)/P(180_220\"]=sum(fragweights_for_plot[160:180])/sum(fragweights_for_plot[180:220])\n", " sample_featuredict[\"P(20_150)/P(160_180)\"]=(sum(fragweights_for_plot[20:150])/sum(fragweights_for_plot[160:180]))\n", " sample_featuredict[\"P(100_150)/P(163_169)\"]=(sum(fragweights_for_plot[100:150])/sum(fragweights_for_plot[163:169]))\n", " sample_featuredict[\"P(20_150)/P(180_220)\"]=(sum(fragweights_for_plot[20:150])/sum(fragweights_for_plot[180:220]))\n", "\n", " # From Mouliere et al.\n", " local_minima=[84, 96, 106, 116, 126, 137, 148]\n", " local_maxima=[81, 92, 102, 112, 122, 134, 144]\n", "\n", " # to test whether Mouliere et al.'s positions local minima and maxima are similar to ours:\n", " \"\"\"\n", " my_local_max=[75+x for x in argrelextrema(np.array(fragweights_for_plot[75:150]), np.greater)]\n", " my_local_min=[75+x for x in argrelextrema(np.array(fragweights_for_plot[75:150]), np.less)]\n", " my_local_max_smooth=[75+x for x in argrelextrema(np.array(ndimage.gaussian_filter(fragweights_for_plot[75:150],mode=\"nearest\",sigma=1)), np.greater)]\n", " my_local_min_smooth=[75+x for x in argrelextrema(np.array(ndimage.gaussian_filter(fragweights_for_plot[75:150],mode=\"nearest\",sigma=1)), np.less)]\n", " print(\"##### MIN/MAX ###\")\n", " print(my_local_min)\n", " print(my_local_max)\n", " print(\"##### MIN/MAX SMOOTH ###\")\n", " print(my_local_min_smooth)\n", " print(my_local_max_smooth)\n", " \"\"\"\n", " periodicity=sum([fragweights_for_plot[x] for x in local_maxima])-sum([fragweights_for_plot[x] for x in local_minima])\n", " sample_featuredict[\"amplitude_10bp\"]=periodicity\n", " featuredict[samplename]=sample_featuredict\n", "\n", "df=pd.DataFrame(featuredict)\n", "df.transpose().to_csv(\"global_fragmentation_features.csv\")\n", "\n", "if plot:\n", " # Range of healthy controls as grey area \n", " ctrl_y_vals=[]\n", " for sample in distrodict.keys():\n", " if not \"Ctrl\" in sample:\n", " continue\n", " ctrl_y_vals.append(distrodict[sample])\n", " min_ctrls=[]\n", " max_ctrls=[]\n", " for i in range(len(ctrl_y_vals[0])):\n", " min_ctrls.append(min([yvallist[i] for yvallist in ctrl_y_vals]))\n", " max_ctrls.append(max([yvallist[i] for yvallist in ctrl_y_vals]))\n", "\n", " for sample in distrodict.keys():\n", " plt.plot(list(range(zoomed_area_start,zoomed_area_end+1)),distrodict[sample],alpha=0.6,label=\"%s\"%(sample)) \n", " plt.fill_between(list(range(zoomed_area_start,zoomed_area_end+1)),min_ctrls,max_ctrls,alpha=0.15, label=\"Range of the \"+str(len(ctrl_y_vals))+\" controls\",color=\"grey\")\n", " plt.legend(fontsize=6)\n", " plt.axvline(167*2,linewidth=1, color=\"black\", alpha=1,zorder=10,linestyle=\"--\")\n", " plt.axvline(167,linewidth=1, color=\"black\", alpha=1,linestyle=\"--\",zorder=10)\n", " plt.ylabel(\"Density\")\n", " plt.xlabel(\"Fragment size (bp)\")\n", " plt.title(sample)\n", " plt.show()\n", "\n", "\n", "\n" ] } ], "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" } }, "nbformat": 4, "nbformat_minor": 4 }