From ccba7188c05e12fd853449ec529baa6cef31f42e Mon Sep 17 00:00:00 2001
From: Niko Papadopoulos <nikolaos.papadopoulos@embl.de>
Date: Mon, 27 Mar 2023 07:43:46 +0200
Subject: [PATCH] updated to now save morpholog tables
---
analysis/revision-remote_species.ipynb | 63 +++++++++++++++++---------
1 file changed, 41 insertions(+), 22 deletions(-)
diff --git a/analysis/revision-remote_species.ipynb b/analysis/revision-remote_species.ipynb
index c47af5e..228e48a 100644
--- a/analysis/revision-remote_species.ipynb
+++ b/analysis/revision-remote_species.ipynb
@@ -5,6 +5,8 @@
"id": "56159bf4-7e59-4416-a5ed-8054179cd39d",
"metadata": {},
"source": [
+ "# Remote orthologs (?)\n",
+ "\n",
"How good is protein structure at finding conserved function? To find out, we tried to compare enzyme function between distantly related species, to see how often function was correctly annotated by structural similarity. In particular, we were interested in cases where orthology via sequence similarity was no longer detectable but the annotated protein function was still similar. Enzymes are an interesting test case, since they have an easily accessible function description (EC number).\n",
"\n",
"The detailed strategy I am going to pursue here:\n",
@@ -17,6 +19,9 @@
"6. calculate how many digits of the EC overlap\n",
"7. plot the results\n",
"\n",
+ "\n",
+ "### 1.-2. build proteome, align against all proteomes\n",
+ "\n",
"```\n",
"# download Alphafold proteomes:\n",
"\n",
@@ -99,6 +104,16 @@
" return max_agreement"
]
},
+ {
+ "cell_type": "markdown",
+ "id": "0417dc0c-af62-4de8-9696-d733713cfa7b",
+ "metadata": {},
+ "source": [
+ "### 3.-7. keep human hits, remove homologs, subset only enzymes, calculate EC overlap, plot\n",
+ "\n",
+ "this is terrible design; all these tasks should be accomplished by different functions. At this point the revision had already dragged on long enough though, and I was going to use this function exactly twice. "
+ ]
+ },
{
"cell_type": "code",
"execution_count": 4,
@@ -111,7 +126,7 @@
"\n",
" best = query_foldseek[in_target].sort_values(\"e value\").drop_duplicates(\"query\")\n",
"\n",
- " informative_columns = [\"eggNOG_OGs\", \"Preferred_name\", \"GOs\", \"EC\"]\n",
+ " informative_columns = [\"eggNOG_OGs\", \"Preferred_name\", \"EC\"]\n",
"\n",
" best[\"corrected bit score\"] = best[\"bit score\"] / best[\"alignment length\"]\n",
"\n",
@@ -157,7 +172,7 @@
" ax.text(i-0.1, 4., str(c), fontsize='x-large')\n",
" ax.set_ylim(0, 5);\n",
" \n",
- " return b"
+ " return b, best"
]
},
{
@@ -171,7 +186,7 @@
"yeast_annot[\"max_annot_lvl\"].unique()\n",
"yeast_annot[\"id\"] = yeast_annot[\"#query\"].str.split(\"|\").str[1]\n",
"\n",
- "yeast_foldseek = pd.read_csv(\"/Users/npapadop/Documents/data/foldseek/yeast.m8\", sep=\"\\t\", header=None)\n",
+ "yeast_foldseek = pd.read_csv(\"../data/revision/yeast.m8\", sep=\"\\t\", header=None)\n",
"yeast_foldseek.columns = [\"query\", \"target\", \"seq. id.\", \"alignment length\", \"no. mismatches\",\n",
" \"no. gap open\", \"query start\", \"query end\", \"target start\", \"target end\",\n",
" \"e value\", \"bit score\"]\n",
@@ -240,12 +255,14 @@
{
"cell_type": "code",
"execution_count": 9,
- "id": "f7f4835c-03b8-4117-b494-387c570e5c12",
- "metadata": {},
+ "id": "b5f31271-9aab-4045-829e-cf030216ba3c",
+ "metadata": {
+ "tags": []
+ },
"outputs": [
{
"data": {
- "image/png": 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tN0nSwoULtWHDhqCGAwAA4c1yUcnIyFCbNm20YsUKvf322zp06JAk6ZtvvtH48eODHhAAAIQvy0VlzJgxmjRpkhYtWqSoqKjAeM+ePfXVV18FNRwAAAhvlovK+vXrdcUVVxQZr1Wrlvbt2xeUUAAAAFIpikq1atW0a9euIuNr165VvXr1ghIKAABAKkVRue666zR69Gjt3r1bLpdLBQUF+vLLL3X33Xdr0KBBocgIAADClOWiMnnyZDVs2FD16tXToUOH1KpVK3Xr1k1dunTRfffdF4qMAAAgTEVa2dgYo19++UXPPvusHnroIa1Zs0YFBQVq3769mjVrFqqMAAAgTFkuKs2aNdOGDRvUrFkzNWnSJFS5AAAArJ36qVSpkpo1a8bdPQAAoExYvkbln//8p/7xj3/o22+/DUUeAACAAEunfiTp+uuv15EjR9SuXTtFRUUpOjq60Nf3798ftHAAACC8WS4q06dPD0EMAACAoiwXlcGDB4ciBwAAQBGWi4ok+f1+vfPOO9q4caNcLpdatWqlyy+/XBEREcHOBwAAwpjlorJ161Zdcskl+vnnn9WiRQsZY/T999+rQYMG+uCDD3TGGWeEIicAAAhDlu/6ufPOO3XGGWcoKytLa9as0dq1a7Vjxw4lJibqzjvvDEVGAAAQpizPqGRkZGj58uVKSEgIjNWoUUNTp07V+eefH9RwAAAgvFmeUXG73Tp48GCR8UOHDikqKioooQAAAKRSFJW//OUvGjp0qFasWCFjjIwxWr58uW677TZdfvnlocgIAADClOWi8uSTT+qMM85QUlKSPB6PPB6Pzj//fDVt2lRPPPFEKDICAIAwZfkalWrVqiktLU1bt27Vxo0bZYxRq1at1LRp01DkAwAAYaxU66hIUtOmTSknAAAgpCyf+rn66qs1derUIuOPPPKI/vrXv1ra18yZM9W2bVvFxcUpLi5OSUlJ+uijj6xGAgAAFZTlopKRkaFLL720yPjFF1+sJUuWWNpX/fr1NXXqVK1atUqrVq1Sr169lJycrA0bNliNBQAAKiDLp35Odhty5cqVlZOTY2lfl112WaHHkydP1syZM7V8+XKdddZZVqMBAIAKxvKMSuvWrfXaa68VGZ8/f75atWpV6iB+v1/z58/X4cOHlZSUVOw2Pp9POTk5hT4AAEDFZXlG5f7779dVV12lbdu2qVevXpKkTz/9VK+++qreeOMNywHWr1+vpKQkeb1eVa1aVQsWLDhp4ZkyZYomTpxo+XsAAIDyyWWMMVaf9MEHH+jhhx9WZmamoqOj1bZtW40fP17du3e3HCA3N1c7duzQgQMH9NZbb+m5555TRkZGsWXF5/PJ5/MFHufk5KhBgwbKzs5WXFyc5e8NAEB5cvToUfXt21eSlJ6erujoaJsTlU5OTo7i4+NL9Pe7VEUllC688EKdccYZmjVr1v/c1soLBQCgvAvHomL5GpWsrCzt3Lkz8Pjrr7/WqFGjNHv2bOtJi2GMKTRrAgAAwpflonLdddfp888/lyTt3r1bF154ob7++muNGzdODz74oKV9jRs3Tl988YV+/PFHrV+/Xvfee68WL16sgQMHWo0FAAAqIMtF5dtvv9U555wjSXr99dfVpk0bLVu2TK+88opeeOEFS/v69ddfdcMNN6hFixbq3bu3VqxYoYULF+qiiy6yGgsAAFRAlu/6ycvLk9vtliR98skngXdMPvPMM7Vr1y5L+/rPf/5j9dsDABAyxhh5vV67Y5zUidmcnNPj8cjlcgVlX5aLyllnnaVnnnlGl156qRYtWqSHHnpIkvTLL7+oRo0aQQkFAIAdvF5v4GJVp0tOTrY7wkkF80Jfy6d+pk2bplmzZqlHjx4aMGCA2rVrJ0l69913A6eEAAAAgsHyjEqPHj20d+9e5eTkqHr16oHxoUOHKiYmJqjhAACwy+VnD1Nkpcp2xyjEGCN/Qb4kKaJSZNBOrwRDfkGe3s2cEfT9Wi4qkhQREVGopEhS48aNg5EHAABHiKxUWZERRd/bzm6V5bY7QpmyfOoHAACgrJRqRgUA4FzBvHPlxEU43W53UE81BPPOEFRcFBUAqGDKy50r5XkJeJQdy6d+5s6dW+wS97m5uZo7d25QQgEAAEilmFEZMmSILr74YtWuXbvQ+MGDBzVkyBANGjQoaOEAANZ5PB6lp6cHZV9erzewXkdaWpo8Hk9Q9ispqPtCxWW5qBhjij2nuHPnTsXHxwclFACg9FwuV0hOqXg8Hk7VoMyVuKi0b99eLpdLLpdLvXv3VmTk70/1+/3avn27Lr744pCEBAAA4anERSUlJUWSlJmZqb59+6pq1aqBr0VFRalx48a66qqrgh4QAACErxIXlfHjx0s6trDbtddey7lFAAAQcpavURk8eHAocgAAABRRoqKSkJCg77//XjVr1lT16tX/dIGe/fv3By0cAAAIbyUqKo8//rhiY2MlSdOnTw9lHgAAgIASFZUTT/dw6gcAAJSVUi2h7/f7tWDBAm3cuFEul0stW7ZUcnJyoVuWAQAATpXlZvHtt98qOTlZu3fvVosWLSRJ33//vWrVqqV3331Xbdq0CXpIAAAQniy/18/NN9+ss846Szt37tSaNWu0Zs0aZWVlqW3btho6dGgoMgIAgDBleUZl3bp1WrVqlapXrx4Yq169uiZPnqzOnTsHNRwAAAhvlmdUWrRooV9//bXI+G+//aamTZsGJRQAAIBUwqKSk5MT+Hj44Yd155136s0339TOnTu1c+dOvfnmmxo1apSmTZsW6rwAACCMlOjUT7Vq1Qot8maM0TXXXBMYM8ZIki677DL5/f4QxAQAAOGoREXl888/D3UOAACAIkpUVLp37x7qHAAAAEVYvpgWAACgrFBUAACAY1FUAACAY1FUAACAY1FUAACAY5Xorp/27dsXWkflz6xZs+aUAgEAABxXoqKSkpIS+Nzr9WrGjBlq1aqVkpKSJEnLly/Xhg0bNGzYsJCEBAAA4alERWX8+PGBz2+++Wbdeeedeuihh4psk5WVFdx0AAAgrFm+RuWNN97QoEGDioxff/31euutt4ISCgAAQCpFUYmOjtbSpUuLjC9dulQejycooQAAAKQSnvo50ahRo3T77bdr9erVOu+88yQdu0bl+eef1wMPPBD0gAAAIHxZLipjxoxRkyZN9MQTT+iVV16RJLVs2VIvvPCCrrnmmqAHBAAA4ctyUZGka665hlICAABCrlQLvh04cEDPPfecxo0bp/3790s6tn7Kzz//HNRwAAAgvFmeUfnmm2904YUXKj4+Xj/++KNuvvlmJSQkaMGCBfrpp580d+7cUOQEAABhyPKMSmpqqm688UZt2bKl0F0+/fr105IlS4IaDgAAhDfLRWXlypW69dZbi4zXq1dPu3fvDkooAAAAqRRFxePxKCcnp8j45s2bVatWraCEAgAAkEpRVJKTk/Xggw8qLy9PkuRyubRjxw6NGTNGV111VdADAgCA8GW5qPzrX//Snj17VLt2bR09elTdu3dX06ZNFRsbq8mTJ4ciIwAACFOW7/qJi4vT0qVL9dlnn2nNmjUqKChQhw4ddOGFF4YiHwAACGOWi8rcuXN17bXXqlevXurVq1dgPDc3V/Pnzy/2DQsBAABKw/KpnyFDhig7O7vI+MGDBzVkyJCghAIAAJBKUVSMMXK5XEXGd+7cqfj4+KCEAgAAkCyc+mnfvr1cLpdcLpd69+6tyMjfn+r3+7V9+3ZdfPHFIQkJAADCU4mLSkpKiiQpMzNTffv2VdWqVQNfi4qKUuPGjbk9GQAABFWJi8r48eMlSY0bN1b//v3ldrtDFgoAAEAqxTUqrVq1UmZmZpHxFStWaNWqVcHIBAAAIKkURWX48OHKysoqMv7zzz9r+PDhQQkFAAAglaKofPfdd+rQoUOR8fbt2+u7774LSigAAACpFAu+ud1u/frrr2rSpEmh8V27dhW6EwhA+DDGyOv1BnV/Pp9P0rHfOcUtiVBaHo8nqPsDEFqWm8VFF12ksWPHKi0tLbBuyoEDBzRu3DhddNFFQQ8IwPm8Xq/69u1rd4wSSU9PV3R0tN0xAJSQ5aLy6KOPqlu3bmrUqJHat28v6dgty3Xq1NG8efOCHhAAAIQvy0WlXr16+uabb/Tyyy9r3bp1io6O1pAhQzRgwABVrlw5FBkdhSluoCiPx6P09PSg7c/r9So5OVmSlJaWJo/HE7R9B3NfwRLs3yvBdGIup2Y8jt95FVOpLiqpUqWKhg4dGuws5QJT3EBRLpcrZP+teTyeCv/fcXn5vXK8PDoVv/MqJst3/UjSvHnzdMEFF6hu3br66aefJEmPP/640tLSghoOAACEN8szKjNnztQDDzygUaNGadKkSfL7/ZKk6tWra/r06Y5v3KeKKW4AoTRaUpTdIU5gJOX9/+eVJTntxEqupGl2h0BIWS4qTz31lJ599lmlpKRo6tSpgfFOnTrp7rvvtrSvKVOm6O2339amTZsUHR2tLl26aNq0aWrRooXVWGWGKW4AoRQlKcphdcDZb5hi7A6AELN86mf79u2Bu31O5Ha7dfjwYUv7ysjI0PDhw7V8+XItWrRI+fn56tOnj+X9AACAisnyjEpiYqIyMzPVqFGjQuMfffSRWrVqZWlfCxcuLPR4zpw5ql27tlavXq1u3bpZjQYAACoYy0XlH//4h4YPHy6v1ytjjL7++mu9+uqrmjJlip577rlTCpOdnS1JSkhIKPbrPp8vcCuvJOXk5JzS9wMAAM5muagMGTJE+fn5uueee3TkyBFdd911qlevnp544gn179+/1EGMMUpNTdUFF1yg1q1bF7vNlClTNHHixFJ/DwAAUL5YKir5+fl6+eWXddlll+mWW27R3r17VVBQoNq1a59ykBEjRuibb77R0qVLT7rN2LFjlZqaGnick5OjBg0anPL3BsKNkxcYk1hkDMDvLBWVyMhI3X777dq4caMkqWbNmkEJcccdd+jdd9/VkiVLVL9+/ZNu53a75XY7+/pzoDwoLwuMSSwyBoQ7y3f9nHvuuVq7dm1QvrkxRiNGjNDbb7+tzz77TImJiUHZLwAAqBgsX6MybNgw3XXXXdq5c6c6duyoKlWqFPp627ZtS7yv4cOH65VXXlFaWppiY2O1e/duSVJ8fDz/QgHKiP8yfynfTCOEjCT//38eIeetMpYvRbwXYXcKICxY/vV07bXXSpLuvPPOwJjL5ZIxRi6XK7BSbUnMnDlTktSjR49C43PmzNGNN95oNRqA0oiU84qKdGwZVABhz/Kvp+3btwftmxvDioIAAODkLBWVvLw89ezZU++//77lxd0AAACssnQxbeXKleXz+bgVDwAAlAnLd/3ccccdmjZtmvLz80ORBwAAIMDyNSorVqzQp59+qo8//lht2rQpctfP22+/HbRwAACUpROvncz359mYpPw58ecVzGtQLReVatWq6aqrrgpaAAAAnOLE95N7d90MG5OUbz6fTzExMUHZl+WiMmfOnKB8YwAAgP+l1Ksn7NmzR5s3b5bL5VLz5s1Vq1atYOYCAKDMnfg2LZe3G6bICBb0Kal8f15gFiqYb3djuagcPnxYd9xxh+bOnauCggJJUkREhAYNGqSnnnoqaFM9AACUtRPvao2MqKzIiCgb05Rfwbw72PJdP6mpqcrIyNB7772nAwcO6MCBA0pLS1NGRobuuuuuoAUDAACwPKPy1ltv6c033yy07P0ll1yi6OhoXXPNNYFl8QEAAE6V5RmVI0eOqE6dOkXGa9eurSNHjgQlFAAAgFSKopKUlKTx48fL6/UGxo4ePaqJEycqKSkpqOEAAEB4s3zq54knntDFF1+s+vXrq127dnK5XMrMzJTH41F6enooMp4SY0yhUuU0J2Zzck6Px+O4t04I9rE1xgTWUHC73UF9vU78+QFAeWC5qLRu3VpbtmzRSy+9pE2bNskYo/79+2vgwIGKjo4ORcZT4vV61bdvX7tjlEhycrLdEU4qPT3dcce3PB1bJ/78AKA8KNU6KtHR0brllluCnQVAGSm0vDVv22XdCT+zYC4VDqAoy0VlypQpqlOnjm666aZC488//7z27Nmj0aNHBy1csB3uMFCqVOo17kLDGKng/3/rVYqUnHR6oCBfVda8bHeKkwr26Uav1xuY1UpLS5PH4wnavoO5r2A4cZnwiPcibExS/gVzqXAARVn+qz1r1iy98sorRcbPOuss9e/f39FFRZUiJUeuMsiCQqXhcrlCdjrF4/FwqgYAHMByUdm9e7dOP/30IuO1atXSrl27ghIKQGiduLy1/zL/KbyZRpjK/30mKphLhQMoyvKvpwYNGujLL79UYmJiofEvv/xSdevWDVowVDzcgRU8p3oXUaHnRoqicgq4mwsILcu/nm6++WaNGjVKeXl56tWrlyTp008/1T333MMS+vhT5ekuHSffgSVxFxGA8GG5qNxzzz3av3+/hg0bptzcXEnH/nU3evRojR07NugBAQBA+LJcVFwul6ZNm6b7779fGzduVHR0tJo1a8Z5Wljy724H5I5w1m2dxki5x94QXFGVnHUDliT5/C4NX1LN7hgAUKZKfWa6atWq6ty5czCzIIy4I4w8Drwr1tknU5xV7ACgLFh+rx8AAICyQlEBAACORVEBAACORVEBAACORVEBAACORVEBAACORVEBAACOVeHf4cOYE9ae8OfZF6Q8OuHnVejnCABAGanwRcXn8wU+r7L2FRuTlG8+n08xMTF2xwAAhBlO/QAAAMeq8DMqJ74H0eH210kRlW1MU8748wKzULyXEwDADhW+qLhOfGe5iMoUlVJyOe0d+gAAYYFTPwAAwLEoKgAAwLEoKgAAwLEq/DUqcI4T12Lx+W0MUk6d+DNjXRsA4YKigjJz4po2w5dUtzFJ+ce6NgDCBUUFAGx24gxZ7rERu6KUO7knfM5MY8VEUUGZOXEtln93+6/cETaGKYd8/t9noljXpmI5cbZxmo05yjtmGismigrKzIlrsbgjJA9FpdRY1wZAuKCoAIDNTpwhGy0pyr4o5U6ufp+FYqaxYqKoAIDNTpwhi5IUJWbMSu7361KYaayYWEcFAAA4FkUFAAA4FkUFAAA4FkUFAAA4FkUFAAA4FkUFAAA4FkUFAAA4FkUFAAA4FkUFAAA4FkUFAAA4FkUFAAA4FkUFAAA4Fm9KCABAMfIL8uyOUIQxRv6CfElSRKVIR70RY6h+XhQVINzl2x2gGEaS//8/j5Ac92bCTvyZIejezZxhdwSIogKEvYj3IuyOAAAnRVEBAOD/eTwepaen2x3jpLxer5KTkyVJaWlp8ng8NicqXjBzUVSAMMQv4+BxcjZY53K5FB0dbXeMEvF4POUm66mgqMAWPr9Lxy5EcA5jpNyCY59HVZIcdI2apOM/s+DglzGA8sLWorJkyRI98sgjWr16tXbt2qUFCxYoJSXFzkgoI8OXVLM7AgCgHLB1HZXDhw+rXbt2evrpp+2MAQAAHMrWGZV+/fqpX79+dkZAGeK6iOBxcjYACKZydY2Kz+eTz+cLPM7JybExDaziuggAgFXlagn9KVOmKD4+PvDRoEEDuyMBAIAQKlczKmPHjlVqamrgcU5ODmUljBlj5PV6g7a/E/cVzP1Kx2ZonLTUNZwrV5KT7ogzko4vjF5ZzlskONfuAAi5clVU3G633G633THgEF6vV3379g3Jvo9fqxIs6enpnEpCiUyzOwDgMOWqqJyyAge+QYcxv+eqFOmsxTuc+PMCAIQVW4vKoUOHtHXr1sDj7du3KzMzUwkJCWrYsGHQv1+VNS8HfZ+wT7DvIjLGBC7WdrvdQT1Vw106+DNOviOOu+FgN1uLyqpVq9SzZ8/A4+PXnwwePFgvvPCCTalQXoTiLqKYmJig7g8oifJyRxx3w8EOthaVHj16yJjQXjTm5H+pSOXnXytOzQUAqNgq/DUq5eVfKhL/WgEA4I/K1ToqAAAgvFBUAACAY1FUAACAY1X4a1QAhB6rBAMIFYoKgFPGKsEAQoVTPwAAwLGYUQFwylglGECoUFQAnDJWCQYQKhQVi7hoEACAskNRsYiLBgEAKDtcTAsAAByLGRWLuGgQAICyQ1GxiIsGAQAoO5z6AQAAjkVRAQAAjsWpHwCoYIK5jAJLKMBuFBUAqGBCtYwCSyjADhQVAABCpLwsEurk2S2XMcbYHaK0cnJyFB8fr+zsbMXFxdkdBwAcIZh/HEO9hIJT/zgGy9GjR0O2SGgwlfXslpW/38yoAEAFE+xlFFhCAXaiqAAAECLlZZFQJy8QSlEBACBEWCT01LGOCgAAcCyKCgAAcCyKCgAAcCyKCgAAcCyKCgAAcCyKCgAAcCyKCgAAcCyKCgAAcCyKCgAAcCyKCgAAcCyKCgAAcCyKCgAAcCyKCgAAcCyKCgAAcCyKCgAAcCyKCgAAcCyKCgAAcCyKCgAAcCyKCgAAcCyKCgAAcCyKCgAAcCyKCgAAcCyKCgAAcCyKCgAAcCyKCgAAcCyKCgAAcCyKCgAAcCyKCgAAcCyKCgAAcCyKCgAAcCyKCgAAcCyKCgAAcCyKCgAAcCyKCgAAcCyKCgAAcCyKCgAAcCyKCgAAcCyKCgAAcCyKCgAAcCyKCgAAcCzbi8qMGTOUmJgoj8ejjh076osvvrA7EgAAcAhbi8prr72mUaNG6d5779XatWvVtWtX9evXTzt27LAzFgAAcAiXMcbY9c3PPfdcdejQQTNnzgyMtWzZUikpKZoyZcr/fH5OTo7i4+OVnZ2tuLi4UEYFAABBYuXvd2QZZSoiNzdXq1ev1pgxYwqN9+nTR8uWLSv2OT6fTz6fL/A4Oztb0rEXDAAAyofjf7dLMldiW1HZu3ev/H6/6tSpU2i8Tp062r17d7HPmTJliiZOnFhkvEGDBiHJCAAAQufgwYOKj4//021sKyrHuVyuQo+NMUXGjhs7dqxSU1MDjwsKCrR//37VqFHjpM8pD3JyctSgQQNlZWVxCstmHAvn4Fg4B8fCWSrC8TDG6ODBg6pbt+7/3Na2olKzZk1FREQUmT357bffisyyHOd2u+V2uwuNVatWLVQRy1xcXFy5/Y+uouFYOAfHwjk4Fs5S3o/H/5pJOc62u36ioqLUsWNHLVq0qND4okWL1KVLF5tSAQAAJ7H11E9qaqpuuOEGderUSUlJSZo9e7Z27Nih2267zc5YAADAIWwtKtdee6327dunBx98ULt27VLr1q314YcfqlGjRnbGKnNut1vjx48vcloLZY9j4RwcC+fgWDhLuB0PW9dRAQAA+DO2L6EPAABwMhQVAADgWBQVAADgWBQVAADgWBQVm82YMUOJiYnyeDzq2LGjvvjiC7sjhaUlS5bosssuU926deVyufTOO+/YHSlsTZkyRZ07d1ZsbKxq166tlJQUbd682e5YYWnmzJlq27ZtYGGxpKQkffTRR3bHgo79f+JyuTRq1Ci7o4QcRcVGr732mkaNGqV7771Xa9euVdeuXdWvXz/t2LHD7mhh5/Dhw2rXrp2efvppu6OEvYyMDA0fPlzLly/XokWLlJ+frz59+ujw4cN2Rws79evX19SpU7Vq1SqtWrVKvXr1UnJysjZs2GB3tLC2cuVKzZ49W23btrU7Spng9mQbnXvuuerQoYNmzpwZGGvZsqVSUlI0ZcoUG5OFN5fLpQULFiglJcXuKJC0Z88e1a5dWxkZGerWrZvdccJeQkKCHnnkEf3tb3+zO0pYOnTokDp06KAZM2Zo0qRJOvvsszV9+nS7Y4UUMyo2yc3N1erVq9WnT59C43369NGyZctsSgU4T3Z2tqRjfyBhH7/fr/nz5+vw4cNKSkqyO07YGj58uC699FJdeOGFdkcpM7a/e3K42rt3r/x+f5E3YKxTp06RN2oEwpUxRqmpqbrgggvUunVru+OEpfXr1yspKUler1dVq1bVggUL1KpVK7tjhaX58+drzZo1Wrlypd1RyhRFxWYul6vQY2NMkTEgXI0YMULffPONli5daneUsNWiRQtlZmbqwIEDeuuttzR48GBlZGRQVspYVlaWRo4cqY8//lgej8fuOGWKomKTmjVrKiIiosjsyW+//VZklgUIR3fccYfeffddLVmyRPXr17c7TtiKiopS06ZNJUmdOnXSypUr9cQTT2jWrFk2Jwsvq1ev1m+//aaOHTsGxvx+v5YsWaKnn35aPp9PERERNiYMHa5RsUlUVJQ6duyoRYsWFRpftGiRunTpYlMqwH7GGI0YMUJvv/22PvvsMyUmJtodCScwxsjn89kdI+z07t1b69evV2ZmZuCjU6dOGjhwoDIzMytsSZGYUbFVamqqbrjhBnXq1ElJSUmaPXu2duzYodtuu83uaGHn0KFD2rp1a+Dx9u3blZmZqYSEBDVs2NDGZOFn+PDheuWVV5SWlqbY2NjArGN8fLyio6NtThdexo0bp379+qlBgwY6ePCg5s+fr8WLF2vhwoV2Rws7sbGxRa7TqlKlimrUqFHhr9+iqNjo2muv1b59+/Tggw9q165dat26tT788EM1atTI7mhhZ9WqVerZs2fgcWpqqiRp8ODBeuGFF2xKFZ6O367fo0ePQuNz5szRjTfeWPaBwtivv/6qG264Qbt27VJ8fLzatm2rhQsX6qKLLrI7GsII66gAAADH4hoVAADgWBQVAADgWBQVAADgWBQVAADgWBQVAADgWBQVAADgWBQVAADgWBQVABXW4sWL5XK5dODAAbujACgligoAAHAsigqACikvL8/uCACCgKICoBBjjP75z3+qSZMmio6OVrt27fTmm28W2mbDhg269NJLFRcXp9jYWHXt2lXbtm076T4zMjJ0zjnnyO126/TTT9eYMWOUn58vSZo1a5bq1aungoKCQs+5/PLLNXjw4MDj9957Tx07dpTH41GTJk00ceLEwD4kyeVy6ZlnnlFycrKqVKmiSZMmFcmxb98+DRgwQPXr11dMTIzatGmjV199tdA2PXr00IgRIzRixAhVq1ZNNWrU0H333SfebQSwiQGAE4wbN86ceeaZZuHChWbbtm1mzpw5xu12m8WLFxtjjNm5c6dJSEgwV155pVm5cqXZvHmzef75582mTZuK3d/OnTtNTEyMGTZsmNm4caNZsGCBqVmzphk/frwxxph9+/aZqKgo88knnwSes3//fhMVFWXS09ONMcYsXLjQxMXFmRdeeMFs27bNfPzxx6Zx48ZmwoQJgedIMrVr1zb/+c9/zLZt28yPP/5oPv/8cyPJ/Pe//w1keeSRR8zatWvNtm3bzJNPPmkiIiLM8uXLA/vp3r27qVq1qhk5cqTZtGmTeemll0xMTIyZPXt2MH/MAEqIogIg4NChQ8bj8Zhly5YVGv/b3/5mBgwYYIwxZuzYsSYxMdHk5uaWaJ/jxo0zLVq0MAUFBYGxf//736Zq1arG7/cbY4y5/PLLzU033RT4+qxZs8xpp51m8vPzjTHGdO3a1Tz88MOF9jtv3jxz+umnBx5LMqNGjSq0zR+LSnEuueQSc9dddwUed+/e3bRs2bJQ3tGjR5uWLVuW6PUCCK5Ie+dzADjJd999J6/Xq4suuqjQeG5urtq3by9JyszMVNeuXVW5cuUS7XPjxo1KSkqSy+UKjJ1//vk6dOiQdu7cqYYNG2rgwIEaOnSoZsyYIbfbrZdffln9+/dXRESEJGn16tVauXKlJk+eHNiH3++X1+vVkSNHFBMTI0nq1KnTn2bx+/2aOnWqXnvtNf3888/y+Xzy+XyqUqVKoe3OO++8QnmTkpL06KOPyu/3BzIBKBsUFQABx68T+eCDD1SvXr1CX3O73ZKk6OhoS/s0xhT6o398TFJg/LLLLlNBQYE++OADde7cWV988YUee+yxQrkmTpyoK6+8ssj+PR5P4PM/Fo4/evTRR/X4449r+vTpatOmjapUqaJRo0YpNzfX0msCUHYoKgACWrVqJbfbrR07dqh79+7FbtO2bVu9+OKLysvLK9GsSqtWrfTWW28VKizLli1TbGxsoAxFR0fryiuv1Msvv6ytW7eqefPm6tixY2AfHTp00ObNm9W0adNTen1ffPGFkpOTdf3110s6VoC2bNmili1bFtpu+fLlRR43a9aM2RTABtz1AyAgNjZWd999t/7+97/rxRdf1LZt27R27Vr9+9//1osvvihJGjFihHJyctS/f3+tWrVKW7Zs0bx587R58+Zi9zls2DBlZWXpjjvu0KZNm5SWlqbx48crNTVVlSr9/ito4MCB+uCDD/T8888HisRxDzzwgObOnasJEyZow4YN2rhxo1577TXdd999ll5f06ZNtWjRIi1btkwbN27Urbfeqt27dxfZLisrS6mpqdq8ebNeffVVPfXUUxo5cqSl7wUgSGy+RgaAwxQUFJgnnnjCtGjRwlSuXNnUqlXL9O3b12RkZAS2WbdunenTp4+JiYkxsbGxpmvXrmbbtm0n3efixYtN586dTVRUlDnttNPM6NGjTV5eXqFt8vPzzemnn24kFbuvhQsXmi5dupjo6GgTFxdnzjnnnEJ34kgyCxYsKPScP15Mu2/fPpOcnGyqVq1qateube677z4zaNAgk5ycHHhO9+7dzbBhw8xtt91m4uLiTPXq1c2YMWMKXVwLoOy4jGFxAAA4rkePHjr77LM1ffp0u6MAEKd+AACAg1FUAACAY3HqBwAAOBYzKgAAwLEoKgAAwLEoKgAAwLEoKgAAwLEoKgAAwLEoKgAAwLEoKgAAwLEoKgAAwLEoKgAAwLH+D4y6slk1gC4qAAAAAElFTkSuQmCC\n",
+ "image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
@@ -255,8 +272,17 @@
}
],
"source": [
- "same_structure_same_EC(yeast_annot, yeast_foldseek, human_annot)\n",
- "plt.savefig(\"../data/yeast.svg\")"
+ "boxplot, table = same_structure_same_EC(yeast_annot, yeast_foldseek, human_annot)\n",
+ "plt.savefig(\"../data/yeast.svg\")\n",
+ "table.to_csv(\"../data/yeast.tsv\", sep=\"\\t\")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "3bd8cff8-b292-47b9-a4da-ba0894bed897",
+ "metadata": {},
+ "source": [
+ "now repeat for Arabidopsis:"
]
},
{
@@ -270,7 +296,7 @@
"arabidopsis_annot[\"max_annot_lvl\"].unique()\n",
"arabidopsis_annot[\"id\"] = arabidopsis_annot[\"#query\"].str.split(\"|\").str[1]\n",
"\n",
- "arabidopsis_foldseek = pd.read_csv(\"/Users/npapadop/Documents/data/foldseek/arabidopsis.m8\", sep=\"\\t\", header=None)\n",
+ "arabidopsis_foldseek = pd.read_csv(\"../data/revision/arabidopsis.m8\", sep=\"\\t\", header=None)\n",
"arabidopsis_foldseek.columns = [\"query\", \"target\", \"seq. id.\", \"alignment length\", \"no. mismatches\",\n",
" \"no. gap open\", \"query start\", \"query end\", \"target start\", \"target end\",\n",
" \"e value\", \"bit score\"]\n",
@@ -308,7 +334,7 @@
"id": "21080634-fbcd-4e68-9dbf-e1589e3dfe41",
"metadata": {},
"source": [
- "we don't want to get into quibbly territory, so we'll proceed with the IDs that are in both lists and will not wonder why they don't match to 100%."
+ "(same disclaimer about quibbly territory)"
]
},
{
@@ -333,7 +359,7 @@
"outputs": [
{
"data": {
- "image/png": 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\n",
+ "image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
@@ -343,17 +369,10 @@
}
],
"source": [
- "same_structure_same_EC(arabidopsis_annot, arabidopsis_foldseek, human_annot, lowest_relevant_OG=\"Eukaryota\")\n",
- "plt.savefig(\"../data/arabidopsis.svg\")"
+ "boxplot, table = same_structure_same_EC(arabidopsis_annot, arabidopsis_foldseek, human_annot, lowest_relevant_OG=\"Eukaryota\")\n",
+ "plt.savefig(\"../data/arabidopsis.svg\")\n",
+ "table.to_csv(\"../data/arabidopsis.tsv\", sep=\"\\t\")"
]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "48d39bb0-ed6d-4aea-9235-374a37592fbb",
- "metadata": {},
- "outputs": [],
- "source": []
}
],
"metadata": {
@@ -372,7 +391,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.10.8"
+ "version": "3.10.9"
}
},
"nbformat": 4,
--
GitLab