diff --git a/notebooks/MHWGPanels/Untitled.ipynb b/notebooks/MHWGPanels/Untitled.ipynb
new file mode 100644
index 0000000..4c5823a
--- /dev/null
+++ b/notebooks/MHWGPanels/Untitled.ipynb
@@ -0,0 +1,494 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "0641dc89-6873-4c07-b626-bb0bbca7e3c2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from matplotlib import pyplot as plt\n",
+    "import microhapdb\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import seaborn as sns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "9557141b-943d-470d-ba34-7b401b5b9ef3",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "3053\n"
+     ]
+    }
+   ],
+   "source": [
+    "all_markers = list(microhapdb.Marker.objectify(microhapdb.markers))\n",
+    "print(len(all_markers))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "ac0dac73-4fbd-4ee6-abb1-ba6fa390fff0",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1114\n"
+     ]
+    }
+   ],
+   "source": [
+    "markers = [m for m in all_markers if m.name not in microhapdb.repeats.index and len(m) < 250 and m.data.Ae > 2.5]\n",
+    "print(len(markers))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "c978528f-51a6-46df-924e-daa03c7f054c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "lengths = [len(m) for m in markers]\n",
+    "aes = [m.data.Ae for m in markers]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "fe445ea2-2631-498b-9d1e-65c6f6c0ffb0",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 750x750 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(5, 5), dpi=150)\n",
+    "plt.scatter(lengths, aes, marker=\"2\", color=\"red\", alpha=0.5)\n",
+    "plt.ylabel(\"$A_e$ (1KGP 26-population Average)\")\n",
+    "plt.xlabel(\"Marker length (bp)\")\n",
+    "#plt.legend(loc=\"upper left\")\n",
+    "plt.gca().spines[\"top\"].set_visible(False)\n",
+    "plt.gca().spines[\"right\"].set_visible(False)\n",
+    "plt.gca().yaxis.grid(True, color=\"#DDDDDD\")\n",
+    "plt.gca().set_axisbelow(True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "id": "3f7e4e76-40fd-4f20-92e5-9624b62a1439",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "13.533499999999993 8.62714999999999 7.323149999999999\n"
+     ]
+    }
+   ],
+   "source": [
+    "bp1, bp2, bp3 = np.quantile(aes, [0.99, 0.97, 0.95])\n",
+    "print(bp1, bp2, bp3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "id": "f5b8879a-aeb5-4c63-a039-75b3ded0d024",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Top=9 Middle=13 Bottom=18\n"
+     ]
+    }
+   ],
+   "source": [
+    "top = [m for m in markers if m.data.Ae > bp1]\n",
+    "top_loci = set([m.locus for m in top])\n",
+    "middle = [m for m in markers if m.data.Ae > bp2 and m.locus not in top_loci]\n",
+    "middle_loci = set([m.locus for m in middle])\n",
+    "bottom = [m for m in markers if m.data.Ae > bp3 and m.locus not in top_loci and m.locus not in middle_loci]\n",
+    "bottom_loci = set([m.locus for m in bottom])\n",
+    "print(f\"Top={len(top_loci)} Middle={len(middle_loci)} Bottom={len(bottom_loci)}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "id": "de0b2cd4-e69e-41c1-9443-9142b9e0e0b6",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "mh07WL-022 mh01KK-212 mh03LV-06 mh01WL-005 mh10WL-031 mh12KK-201 mh06WL-051 mh04WL-052 mh01WL-006\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(*top_loci)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "id": "a154e9bf-af79-476a-ae6b-fe5d79c8b397",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "         Name  NumVars  Extent     Ae     Start                   Source\n",
+      "mh01KK-212.v1       11     243 16.198 202647419 Gandotra2020;NimaGen2023\n",
+      "mh01KK-212.v2       17     243 16.242 202647419              Pakstis2021\n",
+      "mh01KK-212.v4        8     243 15.488 202647419                 Yu2022G3\n",
+      "mh01WL-005.v1        5     169 16.593 212172159        Yu2022G1;Yu2022G2\n",
+      "mh01WL-006.v3        7     213 14.513 236518814              NimaGen2023\n",
+      " mh03LV-06.v1       16     198 13.540  11914401          Voskoboinik2018\n",
+      "mh04WL-052.v1        9     243 20.722   2303789                 Yu2022G3\n",
+      "   mh06WL-051        8     240 18.952   1708564         Yu2022G3;Zhu2023\n",
+      "mh07WL-022.v2        5     238 13.637 115873343         Yu2022G3;Zhu2023\n",
+      "   mh10WL-031        6     238 13.828   3825864                 Yu2022G3\n",
+      "mh12KK-201.v1       12     177 15.170  27647394 Gandotra2020;NimaGen2023\n",
+      "mh12KK-201.v2       15     177 15.217  27647394              Pakstis2021\n"
+     ]
+    }
+   ],
+   "source": [
+    "!microhapdb marker --columns nxas --query \"Extent < 250 & Ae > 13.53\" mh07WL-022 mh01KK-212 mh03LV-06 mh01WL-005 mh10WL-031 mh12KK-201 mh06WL-051 mh04WL-052 mh01WL-006"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "id": "5c608d78-195c-49b5-9a7a-9d687ff242cc",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "mh12SHY-001 mh16WL-038 mh01WL-007 mh13WL-001 mh07SCUZJ-0502291 mh13USC-13qA mh06WL-017 mh17FHL-005 mh12SCUZJ-0392651 mh02WL-002 mh01WL-010 mh10WL-012 mh03FHL-001\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(*middle_loci)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "id": "6442ef30-91f4-4d4f-be8e-0eb7a953f273",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "                Name  NumVars  Extent     Ae     Start                             Source\n",
+      "          mh01WL-007        4     158  9.081 107376744 Yu2022G1;Yu2022G2;Yu2022G3;Zhu2023\n",
+      "       mh01WL-010.v2       10     237 11.378 168483954                           Yu2022G3\n",
+      "       mh01WL-010.v1        7     187 10.860 168484004                  Yu2022G1;Yu2022G2\n",
+      "       mh02WL-002.v2        5     201 10.233 204497437                           Yu2022G3\n",
+      "       mh02WL-002.v4        4     201  9.258 204497437                             Du2023\n",
+      "      mh03FHL-001.v2        4     213  9.914  11583728                           Yu2022G3\n",
+      "       mh06WL-017.v2       16     100  8.679  32663167                           Yu2022G4\n",
+      "       mh06WL-017.v1       32     199 10.392  32663167                  Yu2022G1;Yu2022G2\n",
+      "mh07SCUZJ-0502291.v1        5     225  9.083 149320697                            Zhu2023\n",
+      "       mh10WL-012.v2        6      88  9.940   4259581                           Yu2022G4\n",
+      "       mh10WL-012.v1        7     184 12.024   4259581          Yu2022G1;Yu2022G2;Zhu2023\n",
+      "      mh12SHY-001.v2        8     140  9.469  13420563 Yu2022G1;Yu2022G2;Yu2022G3;Zhu2023\n",
+      "   mh12SCUZJ-0392651        5     201  8.704 127034321                            Zhu2023\n",
+      "     mh13USC-13qA.v2        8     142 10.367  32979370                  Yu2022G1;Yu2022G2\n",
+      "       mh13WL-001.v1        7     181 11.232  94252435                  Yu2022G1;Yu2022G2\n",
+      "          mh16WL-038        7     125 10.836  88727378                           Yu2022G1\n",
+      "      mh17FHL-005.v1       19     215 11.581  78268165                            Fan2022\n",
+      "      mh17FHL-005.v3        6     249 13.133  78268165                            Zhu2023\n",
+      "      mh17FHL-005.v2        4     174  9.219  78268206                           Yu2022G1\n"
+     ]
+    }
+   ],
+   "source": [
+    "!microhapdb marker --columns nxas --query \"Extent < 250 & Ae < 13.53 & Ae > 8.63\" mh12SHY-001 mh16WL-038 mh01WL-007 mh13WL-001 mh07SCUZJ-0502291 mh13USC-13qA mh06WL-017 mh17FHL-005 mh12SCUZJ-0392651 mh02WL-002 mh01WL-010 mh10WL-012 mh03FHL-001"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "id": "78b1b73b-8d24-4a68-9c43-130d48cf4a23",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Name</th>\n",
+       "      <th>NumVars</th>\n",
+       "      <th>Extent</th>\n",
+       "      <th>Ae</th>\n",
+       "      <th>Start</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1687</th>\n",
+       "      <td>mh10WL-012.v2</td>\n",
+       "      <td>6</td>\n",
+       "      <td>88</td>\n",
+       "      <td>9.940</td>\n",
+       "      <td>4259581</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1109</th>\n",
+       "      <td>mh06WL-017.v2</td>\n",
+       "      <td>16</td>\n",
+       "      <td>100</td>\n",
+       "      <td>8.679</td>\n",
+       "      <td>32663167</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2572</th>\n",
+       "      <td>mh16WL-038</td>\n",
+       "      <td>7</td>\n",
+       "      <td>125</td>\n",
+       "      <td>10.836</td>\n",
+       "      <td>88727378</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2011</th>\n",
+       "      <td>mh12SHY-001.v2</td>\n",
+       "      <td>8</td>\n",
+       "      <td>140</td>\n",
+       "      <td>9.469</td>\n",
+       "      <td>13420563</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2141</th>\n",
+       "      <td>mh13USC-13qA.v2</td>\n",
+       "      <td>8</td>\n",
+       "      <td>142</td>\n",
+       "      <td>10.367</td>\n",
+       "      <td>32979370</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>110</th>\n",
+       "      <td>mh01WL-007</td>\n",
+       "      <td>4</td>\n",
+       "      <td>158</td>\n",
+       "      <td>9.081</td>\n",
+       "      <td>107376744</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2662</th>\n",
+       "      <td>mh17FHL-005.v2</td>\n",
+       "      <td>4</td>\n",
+       "      <td>174</td>\n",
+       "      <td>9.219</td>\n",
+       "      <td>78268206</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2204</th>\n",
+       "      <td>mh13WL-001.v1</td>\n",
+       "      <td>7</td>\n",
+       "      <td>181</td>\n",
+       "      <td>11.232</td>\n",
+       "      <td>94252435</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1688</th>\n",
+       "      <td>mh10WL-012.v1</td>\n",
+       "      <td>7</td>\n",
+       "      <td>184</td>\n",
+       "      <td>12.024</td>\n",
+       "      <td>4259581</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>137</th>\n",
+       "      <td>mh01WL-010.v1</td>\n",
+       "      <td>7</td>\n",
+       "      <td>187</td>\n",
+       "      <td>10.860</td>\n",
+       "      <td>168484004</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1110</th>\n",
+       "      <td>mh06WL-017.v1</td>\n",
+       "      <td>32</td>\n",
+       "      <td>199</td>\n",
+       "      <td>10.392</td>\n",
+       "      <td>32663167</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2105</th>\n",
+       "      <td>mh12SCUZJ-0392651</td>\n",
+       "      <td>5</td>\n",
+       "      <td>201</td>\n",
+       "      <td>8.704</td>\n",
+       "      <td>127034321</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>435</th>\n",
+       "      <td>mh02WL-002.v4</td>\n",
+       "      <td>4</td>\n",
+       "      <td>201</td>\n",
+       "      <td>9.258</td>\n",
+       "      <td>204497437</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>434</th>\n",
+       "      <td>mh02WL-002.v2</td>\n",
+       "      <td>5</td>\n",
+       "      <td>201</td>\n",
+       "      <td>10.233</td>\n",
+       "      <td>204497437</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>510</th>\n",
+       "      <td>mh03FHL-001.v2</td>\n",
+       "      <td>4</td>\n",
+       "      <td>213</td>\n",
+       "      <td>9.914</td>\n",
+       "      <td>11583728</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2660</th>\n",
+       "      <td>mh17FHL-005.v1</td>\n",
+       "      <td>19</td>\n",
+       "      <td>215</td>\n",
+       "      <td>11.581</td>\n",
+       "      <td>78268165</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1381</th>\n",
+       "      <td>mh07SCUZJ-0502291.v1</td>\n",
+       "      <td>5</td>\n",
+       "      <td>225</td>\n",
+       "      <td>9.083</td>\n",
+       "      <td>149320697</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>136</th>\n",
+       "      <td>mh01WL-010.v2</td>\n",
+       "      <td>10</td>\n",
+       "      <td>237</td>\n",
+       "      <td>11.378</td>\n",
+       "      <td>168483954</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2661</th>\n",
+       "      <td>mh17FHL-005.v3</td>\n",
+       "      <td>6</td>\n",
+       "      <td>249</td>\n",
+       "      <td>13.133</td>\n",
+       "      <td>78268165</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                      Name  NumVars  Extent      Ae      Start\n",
+       "1687         mh10WL-012.v2        6      88   9.940    4259581\n",
+       "1109         mh06WL-017.v2       16     100   8.679   32663167\n",
+       "2572            mh16WL-038        7     125  10.836   88727378\n",
+       "2011        mh12SHY-001.v2        8     140   9.469   13420563\n",
+       "2141       mh13USC-13qA.v2        8     142  10.367   32979370\n",
+       "110             mh01WL-007        4     158   9.081  107376744\n",
+       "2662        mh17FHL-005.v2        4     174   9.219   78268206\n",
+       "2204         mh13WL-001.v1        7     181  11.232   94252435\n",
+       "1688         mh10WL-012.v1        7     184  12.024    4259581\n",
+       "137          mh01WL-010.v1        7     187  10.860  168484004\n",
+       "1110         mh06WL-017.v1       32     199  10.392   32663167\n",
+       "2105     mh12SCUZJ-0392651        5     201   8.704  127034321\n",
+       "435          mh02WL-002.v4        4     201   9.258  204497437\n",
+       "434          mh02WL-002.v2        5     201  10.233  204497437\n",
+       "510         mh03FHL-001.v2        4     213   9.914   11583728\n",
+       "2660        mh17FHL-005.v1       19     215  11.581   78268165\n",
+       "1381  mh07SCUZJ-0502291.v1        5     225   9.083  149320697\n",
+       "136          mh01WL-010.v2       10     237  11.378  168483954\n",
+       "2661        mh17FHL-005.v3        6     249  13.133   78268165"
+      ]
+     },
+     "execution_count": 43,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "microhapdb.markers[microhapdb.markers.Name.isin([m.name for m in middle])].sort_values([\"Extent\", \"Ae\"])[[\"Name\", \"NumVars\", \"Extent\", \"Ae\", \"Start\"]]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1ef78edf-7c06-4231-98d1-edfc64b38193",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "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": "3.9.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/notebooks/MHWGPanels/markII.ipynb b/notebooks/MHWGPanels/markII.ipynb
new file mode 100644
index 0000000..bca6a27
--- /dev/null
+++ b/notebooks/MHWGPanels/markII.ipynb
@@ -0,0 +1,547 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "6226fc41-77cf-4ac4-8cc9-99dc7eb248c5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from collections import defaultdict\n",
+    "from itertools import chain, combinations\n",
+    "from matplotlib import pyplot as plt\n",
+    "import microhapdb\n",
+    "import networkx as nx\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import seaborn as sns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "a01b1b32-4b7e-4825-bf9c-6d3af6970c3f",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "3053\n"
+     ]
+    }
+   ],
+   "source": [
+    "all_markers = list(microhapdb.Marker.objectify(microhapdb.markers))\n",
+    "print(len(all_markers))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "3d6e794e-eaef-4e4c-bb37-b8bfb3d12202",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1673\n"
+     ]
+    }
+   ],
+   "source": [
+    "markers_nonrep = [m for m in all_markers if m.name not in microhapdb.repeats.index]\n",
+    "print(len(markers_nonrep))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "ced5a8af-957f-4b0a-bc95-10c26445ffec",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "164\n"
+     ]
+    }
+   ],
+   "source": [
+    "short_markers = [m for m in markers_nonrep if (len(m) <= 60 and m.data.Ae > 1.0)]\n",
+    "short_markers.sort(key=lambda m: m.data.Ae, reverse=True)\n",
+    "print(len(short_markers))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "962a970d-a6b8-46d1-9b23-58416387f977",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 750x750 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "lengths = [len(m) for m in short_markers]\n",
+    "aes = [m.data.Ae for m in short_markers]\n",
+    "plt.figure(figsize=(5, 5), dpi=150)\n",
+    "plt.scatter(lengths, aes, marker=\"2\", color=\"red\", alpha=0.5)\n",
+    "plt.ylabel(\"$A_e$ (1KGP 26-population Average)\")\n",
+    "plt.xlabel(\"Marker length (bp)\")\n",
+    "#plt.legend(loc=\"upper left\")\n",
+    "plt.gca().spines[\"top\"].set_visible(False)\n",
+    "plt.gca().spines[\"right\"].set_visible(False)\n",
+    "plt.gca().yaxis.grid(True, color=\"#DDDDDD\")\n",
+    "plt.gca().set_axisbelow(True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "ab94b8a5-ebdd-4622-b84f-75642630ad23",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Name</th>\n",
+       "      <th>NumVars</th>\n",
+       "      <th>Extent</th>\n",
+       "      <th>Chrom</th>\n",
+       "      <th>Start</th>\n",
+       "      <th>End</th>\n",
+       "      <th>Positions</th>\n",
+       "      <th>Positions37</th>\n",
+       "      <th>RSIDs</th>\n",
+       "      <th>Source</th>\n",
+       "      <th>Ae</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>409</th>\n",
+       "      <td>mh02KK-134.v4</td>\n",
+       "      <td>3</td>\n",
+       "      <td>40</td>\n",
+       "      <td>chr2</td>\n",
+       "      <td>160222900</td>\n",
+       "      <td>160222939</td>\n",
+       "      <td>160222900;160222924;160222939</td>\n",
+       "      <td>161079411;161079435;161079450</td>\n",
+       "      <td>rs12469721;rs3101043;rs3111398</td>\n",
+       "      <td>Staadig2021</td>\n",
+       "      <td>5.685</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1814</th>\n",
+       "      <td>mh10WL-042</td>\n",
+       "      <td>4</td>\n",
+       "      <td>58</td>\n",
+       "      <td>chr10</td>\n",
+       "      <td>126918899</td>\n",
+       "      <td>126918956</td>\n",
+       "      <td>126918899;126918909;126918914;126918956</td>\n",
+       "      <td>128607468;128607478;128607483;128607525</td>\n",
+       "      <td>rs10794140;rs11245233;rs61875476;rs10794141</td>\n",
+       "      <td>Yu2022G1</td>\n",
+       "      <td>6.815</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2471</th>\n",
+       "      <td>mh16WL-040.v1</td>\n",
+       "      <td>4</td>\n",
+       "      <td>24</td>\n",
+       "      <td>chr16</td>\n",
+       "      <td>8832741</td>\n",
+       "      <td>8832764</td>\n",
+       "      <td>8832741;8832746;8832747;8832764</td>\n",
+       "      <td>8926598;8926603;8926604;8926621</td>\n",
+       "      <td>rs9931331;rs12925234;rs12917990;rs12921984</td>\n",
+       "      <td>Yu2022G1</td>\n",
+       "      <td>5.910</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2815</th>\n",
+       "      <td>mh19USC-19qA.v3</td>\n",
+       "      <td>5</td>\n",
+       "      <td>49</td>\n",
+       "      <td>chr19</td>\n",
+       "      <td>33273772</td>\n",
+       "      <td>33273820</td>\n",
+       "      <td>33273772;33273786;33273812;33273817;33273820</td>\n",
+       "      <td>33764678;33764692;33764718;33764723;33764726</td>\n",
+       "      <td>rs10419866;rs12978036;rs10420798;rs11672621;rs...</td>\n",
+       "      <td>Yu2022G4</td>\n",
+       "      <td>5.084</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                 Name  NumVars  Extent  Chrom      Start        End  \\\n",
+       "409     mh02KK-134.v4        3      40   chr2  160222900  160222939   \n",
+       "1814       mh10WL-042        4      58  chr10  126918899  126918956   \n",
+       "2471    mh16WL-040.v1        4      24  chr16    8832741    8832764   \n",
+       "2815  mh19USC-19qA.v3        5      49  chr19   33273772   33273820   \n",
+       "\n",
+       "                                         Positions  \\\n",
+       "409                  160222900;160222924;160222939   \n",
+       "1814       126918899;126918909;126918914;126918956   \n",
+       "2471               8832741;8832746;8832747;8832764   \n",
+       "2815  33273772;33273786;33273812;33273817;33273820   \n",
+       "\n",
+       "                                       Positions37  \\\n",
+       "409                  161079411;161079435;161079450   \n",
+       "1814       128607468;128607478;128607483;128607525   \n",
+       "2471               8926598;8926603;8926604;8926621   \n",
+       "2815  33764678;33764692;33764718;33764723;33764726   \n",
+       "\n",
+       "                                                  RSIDs       Source     Ae  \n",
+       "409                      rs12469721;rs3101043;rs3111398  Staadig2021  5.685  \n",
+       "1814        rs10794140;rs11245233;rs61875476;rs10794141     Yu2022G1  6.815  \n",
+       "2471         rs9931331;rs12925234;rs12917990;rs12921984     Yu2022G1  5.910  \n",
+       "2815  rs10419866;rs12978036;rs10420798;rs11672621;rs...     Yu2022G4  5.084  "
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "highest = [m for m in short_markers if m.data.Ae > 5]\n",
+    "microhapdb.markers[microhapdb.markers.Name.isin([m.name for m in highest])]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "110e078d-07c2-4c5a-ad09-bbf548f47e0d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def build_graphs(markers):\n",
+    "    graphs = defaultdict(nx.Graph)\n",
+    "    chroms = sorted(set([m.chrom for m in markers]))\n",
+    "    for chrom in chroms:\n",
+    "        cmarkers = [m for m in markers if m.chrom == chrom]\n",
+    "        graphs[chrom].add_nodes_from(cmarkers)\n",
+    "        for mh1, mh2 in combinations(graphs[chrom].nodes, 2):\n",
+    "            if abs(mh1.start - mh2.start) >= 10e6:\n",
+    "                graphs[chrom].add_edge(mh1, mh2)\n",
+    "    return graphs"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "6fa464cc-6fab-4fd0-a8ae-06f796b01580",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "graphs = build_graphs(short_markers)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "dd36eeea-6a6d-4d30-a1db-08f331261517",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " chr1: nodes=19  edges=156\n",
+      "chr10: nodes=13  edges=69\n",
+      "chr11: nodes=13  edges=67\n",
+      "chr12: nodes=11  edges=49\n",
+      "chr13: nodes=4   edges=6\n",
+      "chr14: nodes=4   edges=4\n",
+      "chr15: nodes=5   edges=8\n",
+      "chr16: nodes=7   edges=18\n",
+      "chr17: nodes=10  edges=35\n",
+      "chr18: nodes=4   edges=5\n",
+      "chr19: nodes=4   edges=4\n",
+      " chr2: nodes=10  edges=44\n",
+      "chr20: nodes=3   edges=3\n",
+      "chr21: nodes=1   edges=0\n",
+      "chr22: nodes=3   edges=2\n",
+      " chr3: nodes=5   edges=9\n",
+      " chr4: nodes=11  edges=46\n",
+      " chr5: nodes=10  edges=35\n",
+      " chr6: nodes=7   edges=20\n",
+      " chr7: nodes=6   edges=13\n",
+      " chr8: nodes=7   edges=17\n",
+      " chr9: nodes=3   edges=3\n",
+      " chrX: nodes=4   edges=6\n"
+     ]
+    }
+   ],
+   "source": [
+    "for chrom, graph in graphs.items():\n",
+    "    print(f\"{chrom:>5s}: nodes={graph.number_of_nodes():<3d} edges={graph.number_of_edges()}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "8882d2b8-eeb9-42f3-9109-20c08da4ebd4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def clique_agg_ae(clique):\n",
+    "    return sum(marker.data.Ae for marker in clique)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "d9210e7f-d9a5-42d9-a281-a420f5c31647",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "cliques_by_chrom = dict()\n",
+    "best_clique_by_chrom = dict()\n",
+    "for chrom, graph in sorted(graphs.items(), key=lambda cg: cg[1].number_of_edges()):\n",
+    "    cliques = list(nx.find_cliques(graph, nodes=None))\n",
+    "    cliques_by_chrom[chrom] = cliques\n",
+    "    best_clique = sorted(cliques, key=lambda c: clique_agg_ae(c))[-1]\n",
+    "    best_clique_by_chrom[chrom] = best_clique"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "b89f306e-a99f-4ded-a144-889d481a36fd",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "104\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(sum([len(c) for c in best_clique_by_chrom.values()]))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "de049bed-d768-4ae8-a93a-47ec3d094701",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "mh01CP-010\n",
+      "mh01KK-002\n",
+      "mh01KK-211.v2\n",
+      "mh01USC-1pA\n",
+      "mh01USC-1pB\n",
+      "mh01USC-1pD\n",
+      "mh01WL-002.v3\n",
+      "mh01WL-053.v2\n",
+      "mh01WL-110\n",
+      "mh02CP-004\n",
+      "mh02KK-105\n",
+      "mh02KK-134.v4\n",
+      "mh02KK-139\n",
+      "mh02USC-2qB.v1\n",
+      "mh02USC-2qE\n",
+      "mh02WL-028.v2\n",
+      "mh02WL-059\n",
+      "mh02ZBF-002\n",
+      "mh03KK-009\n",
+      "mh03KK-216\n",
+      "mh03LV-06.v3\n",
+      "mh03WL-010\n",
+      "mh04KK-010.v1\n",
+      "mh04KK-013.v4\n",
+      "mh04USC-4qB\n",
+      "mh04USC-4qD\n",
+      "mh04WL-004.v3\n",
+      "mh04WL-047\n",
+      "mh05CP-006\n",
+      "mh05NH-09\n",
+      "mh05USC-5qB\n",
+      "mh05USC-5qD\n",
+      "mh05WL-068\n",
+      "mh05ZBF-001\n",
+      "mh06CP-007\n",
+      "mh06USC-6pA\n",
+      "mh06USC-6qA\n",
+      "mh06WL-041\n",
+      "mh06WL-076\n",
+      "mh06ZBF-001\n",
+      "mh07USC-7pB\n",
+      "mh07USC-7pC\n",
+      "mh07USC-7qA\n",
+      "mh07USC-7qB\n",
+      "mh07ZHA-004.v2\n",
+      "mh08USC-8pA\n",
+      "mh08USC-8pB\n",
+      "mh08USC-8qB\n",
+      "mh08ZBF-002\n",
+      "mh09KK-035.v2\n",
+      "mh09KK-152.v2\n",
+      "mh09USC-9qB\n",
+      "mh0XUSC-XpA\n",
+      "mh0XUSC-XpC\n",
+      "mh0XUSC-XqE\n",
+      "mh0XUSC-XqG\n",
+      "mh10CP-006\n",
+      "mh10KK-085\n",
+      "mh10KK-087\n",
+      "mh10USC-10pB\n",
+      "mh10WL-042\n",
+      "mh10WL-054.v2\n",
+      "mh11CP-005\n",
+      "mh11HYP-29\n",
+      "mh11KK-040\n",
+      "mh11KK-180.v4\n",
+      "mh11NH-19\n",
+      "mh11PK-63643.v1\n",
+      "mh12CP-003\n",
+      "mh12CP-007\n",
+      "mh12USC-12pB\n",
+      "mh12USC-12qA\n",
+      "mh12WL-031.v1\n",
+      "mh12WL-033\n",
+      "mh12WL-034\n",
+      "mh13KK-213.v4\n",
+      "mh13KK-217.v4\n",
+      "mh13KK-225.v4\n",
+      "mh13USC-13qC\n",
+      "mh14USC-14qA\n",
+      "mh14USC-14qC\n",
+      "mh15KK-066.v4\n",
+      "mh15LS-15qC\n",
+      "mh15USC-15qD\n",
+      "mh15WL-015.v2\n",
+      "mh16KK-096\n",
+      "mh16USC-16pB\n",
+      "mh16USC-16qA\n",
+      "mh16WL-040.v1\n",
+      "mh17KK-014\n",
+      "mh17KK-055.v1\n",
+      "mh17USC-17qB\n",
+      "mh17WL-022.v3\n",
+      "mh18KK-285.v2\n",
+      "mh18WL-018\n",
+      "mh18WL-032\n",
+      "mh19USC-19qA.v3\n",
+      "mh19USC-19qB.v1\n",
+      "mh20HYP-41\n",
+      "mh20NH-24\n",
+      "mh20USC-20qB\n",
+      "mh21KK-320.v4\n",
+      "mh22KK-060.v2\n",
+      "mh22WL-005.v2\n"
+     ]
+    }
+   ],
+   "source": [
+    "shorts = set()\n",
+    "for clique in best_clique_by_chrom.values():\n",
+    "    shorts.update(clique)\n",
+    "short_names = sorted([m.name for m in shorts])\n",
+    "print(*short_names, sep=\"\\n\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "7032f171-baf2-4f70-b747-81d84abe8a5a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 750x750 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "lengths = [len(m) for m in shorts]\n",
+    "aes = [m.data.Ae for m in shorts]\n",
+    "plt.figure(figsize=(5, 5), dpi=150)\n",
+    "plt.scatter(lengths, aes, marker=\"2\", color=\"red\", alpha=0.5)\n",
+    "plt.ylabel(\"$A_e$ (1KGP 26-population Average)\")\n",
+    "plt.xlabel(\"Marker length (bp)\")\n",
+    "#plt.legend(loc=\"upper left\")\n",
+    "plt.gca().spines[\"top\"].set_visible(False)\n",
+    "plt.gca().spines[\"right\"].set_visible(False)\n",
+    "plt.gca().yaxis.grid(True, color=\"#DDDDDD\")\n",
+    "plt.gca().set_axisbelow(True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a3ab777f-178b-4493-a6ca-b92459a28d5e",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "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": "3.9.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}