Lecture-11-BroadSenseHeritability.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Estimating broad-sense Heritability ($H^{2}$)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Heritability is the proportion of phenotypic variance that can be attributed to genetic differences among individuals. It is defined as the ratio of genetic to total phenotypic variation in a population:\n",
    "\n",
    "\n",
    "<center>Phenotype (P) = Genotype (G) + Environment (E)</center>\n",
    "\n",
    "\n",
    "The genetic component of phenotypic variance can be separated into additive, dominance, and interaction (G x G) effects. Each of these components of variance contribute to broad-sense heritability:\n",
    "\n",
    "\\begin{equation*}\n",
    "H^{2} = \\frac{VG}{VP} \n",
    "\\end{equation*}\n",
    "\n",
    "\n",
    "<center>or</center>\n",
    "\n",
    "\n",
    "\\begin{equation*}\n",
    "H^{2} = \\frac{Va + Vd + Vi}{VP} \n",
    "\\end{equation*}\n",
    "\n",
    "\n",
    "There are several ways to estimate broad-sense heritability. For those of us that work on inbred lines, we can model the variance due to genetics and the environment using a mixed-effects model, while including the accession-id (also known as the genotype or ecotype in some fields of research) as a random effect. We can then use a trick described in [this paper](https://besjournals.onlinelibrary.wiley.com/doi/10.1111/j.2041-210x.2012.00261.x) and implemented in code described [here](https://jonlefcheck.net/2013/03/13/r2-for-linear-mixed-effects-models/)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Load the data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To investigate broad-sense heritability, let's use [publicly available](http://www.pnas.org/content/112/13/4032) glucosinolate data. The formatted data can be downloaded here:\n",
    "\n",
    "curl https://raw.githubusercontent.com/timeu/gwas-lecture/master/data/cmeyer_glucs2015/bmeyer_etal.txt --create-dirs --output data/cmeyer_glucs2015/bmeyer_etal.txt\n",
    "\n",
    "This is the R-script for estimating marginal and conditional variance in a mixed-model (merMod):<br>\n",
    "curl https://raw.githubusercontent.com/timeu/gwas-lecture/master/data/cmeyer_glucs2015/hdr.estimate_r2_mixedmodels.R --create-dirs --output data/cmeyer_glucs2015/hdr.estimate_r2_mixedmodels.R"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Loading required package: lme4\n",
      "Loading required package: Matrix\n"
     ]
    }
   ],
   "source": [
    "## if lme4 isn't installed, install it first:\n",
    "if (!require(\"lme4\")) install.packages(\"lme4\");\n",
    "library(lme4);\n",
    "\n",
    "source(\"data/cmeyer_glucs2015/hdr.estimate_r2_mixedmodels.R\");\n",
    "\n",
    "glucosinolateFileName <- \"data/cmeyer_glucs2015/bmeyer_etal.txt\";\n",
    "glucs <- read.table(glucosinolateFileName, header=T, sep=\"\\t\", as.is=T, stringsAsFactors=FALSE);\n",
    "glucs <- glucs[order(glucs[,\"accession_id\"]),];"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>2199</li>\n",
       "\t<li>24</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 2199\n",
       "\\item 24\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 2199\n",
       "2. 24\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1] 2199   24"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dim(glucs);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th></th><th scope=col>accession_id</th><th scope=col>sample_weight</th><th scope=col>G2P</th><th scope=col>G3B</th><th scope=col>G3HP</th><th scope=col>G4P</th><th scope=col>G2H3B</th><th scope=col>G4HB</th><th scope=col>G2H4P</th><th scope=col>G3MTP</th><th scope=col>⋯</th><th scope=col>G6MTH</th><th scope=col>G5MSP</th><th scope=col>G7MTH</th><th scope=col>G6MSH</th><th scope=col>G8MTO</th><th scope=col>G7MSH</th><th scope=col>G3BOP</th><th scope=col>G8MSO</th><th scope=col>G4BOB</th><th scope=col>G5BOP</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>892</th><td>1         </td><td>27.0      </td><td>1391.3143 </td><td>103708.84 </td><td> 35.89132 </td><td>5248.4694 </td><td>25310.19  </td><td> 0.000000 </td><td> 656.2984 </td><td>0         </td><td>⋯         </td><td>3611.0269 </td><td> 32.32934 </td><td>2951.46171</td><td>  96.03157</td><td> 8243.8638</td><td> 2142.1924</td><td> 0.00000  </td><td> 23523.238</td><td>1424.3284 </td><td>   0.00000</td></tr>\n",
       "\t<tr><th scope=row>1692</th><td>1         </td><td>22.1      </td><td>7734.5149 </td><td> 69932.37 </td><td>  0.00000 </td><td>2500.7568 </td><td>24289.34  </td><td> 0.000000 </td><td> 390.3385 </td><td>0         </td><td>⋯         </td><td> 116.8998 </td><td> 56.07342 </td><td>   0.00000</td><td> 247.84098</td><td>    0.0000</td><td> 1401.4957</td><td>67.66343  </td><td> 27462.923</td><td>1789.0852 </td><td> 920.67350</td></tr>\n",
       "\t<tr><th scope=row>683</th><td>2         </td><td>15.2      </td><td>8267.7205 </td><td>144750.06 </td><td>202.10448 </td><td>5545.6431 </td><td>78817.75  </td><td> 7.136438 </td><td>1966.7867 </td><td>0         </td><td>⋯         </td><td> 411.9168 </td><td> 76.65779 </td><td>   0.00000</td><td>1016.59783</td><td>    0.0000</td><td>11407.0228</td><td> 0.00000  </td><td>102816.760</td><td>8169.7092 </td><td>3357.24848</td></tr>\n",
       "\t<tr><th scope=row>870</th><td>2         </td><td>29.9      </td><td>1411.4871 </td><td> 27739.70 </td><td>  0.00000 </td><td> 116.5999 </td><td>24817.58  </td><td> 0.000000 </td><td> 435.3465 </td><td>0         </td><td>⋯         </td><td>2256.3011 </td><td>  0.00000 </td><td>  46.88039</td><td>   0.00000</td><td>  577.0562</td><td>  389.6314</td><td> 0.00000  </td><td>  7644.041</td><td> 284.5212 </td><td>   0.00000</td></tr>\n",
       "\t<tr><th scope=row>887</th><td>2         </td><td>31.0      </td><td>1055.4795 </td><td> 82117.61 </td><td> 88.72688 </td><td>2589.5366 </td><td>29056.36  </td><td>32.245193 </td><td>1213.7386 </td><td>0         </td><td>⋯         </td><td>8806.8255 </td><td>227.51344 </td><td>3107.01884</td><td> 428.95742</td><td>18943.1403</td><td> 2913.7202</td><td> 0.00000  </td><td> 36178.023</td><td>2610.6636 </td><td>  61.77065</td></tr>\n",
       "\t<tr><th scope=row>973</th><td>2         </td><td>30.9      </td><td> 967.1328 </td><td> 38721.42 </td><td>  0.00000 </td><td> 880.6843 </td><td>17378.24  </td><td>34.532081 </td><td> 391.1320 </td><td>0         </td><td>⋯         </td><td>2292.2790 </td><td>  0.00000 </td><td> 810.27345</td><td>  93.65825</td><td> 2614.6889</td><td>  970.8893</td><td> 0.00000  </td><td>  9763.230</td><td> 493.1664 </td><td>   0.00000</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|llllllllllllllllllllllll}\n",
       "  & accession\\_id & sample\\_weight & G2P & G3B & G3HP & G4P & G2H3B & G4HB & G2H4P & G3MTP & ⋯ & G6MTH & G5MSP & G7MTH & G6MSH & G8MTO & G7MSH & G3BOP & G8MSO & G4BOB & G5BOP\\\\\n",
       "\\hline\n",
       "\t892 & 1          & 27.0       & 1391.3143  & 103708.84  &  35.89132  & 5248.4694  & 25310.19   &  0.000000  &  656.2984  & 0          & ⋯          & 3611.0269  &  32.32934  & 2951.46171 &   96.03157 &  8243.8638 &  2142.1924 &  0.00000   &  23523.238 & 1424.3284  &    0.00000\\\\\n",
       "\t1692 & 1          & 22.1       & 7734.5149  &  69932.37  &   0.00000  & 2500.7568  & 24289.34   &  0.000000  &  390.3385  & 0          & ⋯          &  116.8998  &  56.07342  &    0.00000 &  247.84098 &     0.0000 &  1401.4957 & 67.66343   &  27462.923 & 1789.0852  &  920.67350\\\\\n",
       "\t683 & 2          & 15.2       & 8267.7205  & 144750.06  & 202.10448  & 5545.6431  & 78817.75   &  7.136438  & 1966.7867  & 0          & ⋯          &  411.9168  &  76.65779  &    0.00000 & 1016.59783 &     0.0000 & 11407.0228 &  0.00000   & 102816.760 & 8169.7092  & 3357.24848\\\\\n",
       "\t870 & 2          & 29.9       & 1411.4871  &  27739.70  &   0.00000  &  116.5999  & 24817.58   &  0.000000  &  435.3465  & 0          & ⋯          & 2256.3011  &   0.00000  &   46.88039 &    0.00000 &   577.0562 &   389.6314 &  0.00000   &   7644.041 &  284.5212  &    0.00000\\\\\n",
       "\t887 & 2          & 31.0       & 1055.4795  &  82117.61  &  88.72688  & 2589.5366  & 29056.36   & 32.245193  & 1213.7386  & 0          & ⋯          & 8806.8255  & 227.51344  & 3107.01884 &  428.95742 & 18943.1403 &  2913.7202 &  0.00000   &  36178.023 & 2610.6636  &   61.77065\\\\\n",
       "\t973 & 2          & 30.9       &  967.1328  &  38721.42  &   0.00000  &  880.6843  & 17378.24   & 34.532081  &  391.1320  & 0          & ⋯          & 2292.2790  &   0.00000  &  810.27345 &   93.65825 &  2614.6889 &   970.8893 &  0.00000   &   9763.230 &  493.1664  &    0.00000\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "| <!--/--> | accession_id | sample_weight | G2P | G3B | G3HP | G4P | G2H3B | G4HB | G2H4P | G3MTP | ⋯ | G6MTH | G5MSP | G7MTH | G6MSH | G8MTO | G7MSH | G3BOP | G8MSO | G4BOB | G5BOP | \n",
       "|---|---|---|---|---|---|\n",
       "| 892 | 1          | 27.0       | 1391.3143  | 103708.84  |  35.89132  | 5248.4694  | 25310.19   |  0.000000  |  656.2984  | 0          | ⋯          | 3611.0269  |  32.32934  | 2951.46171 |   96.03157 |  8243.8638 |  2142.1924 |  0.00000   |  23523.238 | 1424.3284  |    0.00000 | \n",
       "| 1692 | 1          | 22.1       | 7734.5149  |  69932.37  |   0.00000  | 2500.7568  | 24289.34   |  0.000000  |  390.3385  | 0          | ⋯          |  116.8998  |  56.07342  |    0.00000 |  247.84098 |     0.0000 |  1401.4957 | 67.66343   |  27462.923 | 1789.0852  |  920.67350 | \n",
       "| 683 | 2          | 15.2       | 8267.7205  | 144750.06  | 202.10448  | 5545.6431  | 78817.75   |  7.136438  | 1966.7867  | 0          | ⋯          |  411.9168  |  76.65779  |    0.00000 | 1016.59783 |     0.0000 | 11407.0228 |  0.00000   | 102816.760 | 8169.7092  | 3357.24848 | \n",
       "| 870 | 2          | 29.9       | 1411.4871  |  27739.70  |   0.00000  |  116.5999  | 24817.58   |  0.000000  |  435.3465  | 0          | ⋯          | 2256.3011  |   0.00000  |   46.88039 |    0.00000 |   577.0562 |   389.6314 |  0.00000   |   7644.041 |  284.5212  |    0.00000 | \n",
       "| 887 | 2          | 31.0       | 1055.4795  |  82117.61  |  88.72688  | 2589.5366  | 29056.36   | 32.245193  | 1213.7386  | 0          | ⋯          | 8806.8255  | 227.51344  | 3107.01884 |  428.95742 | 18943.1403 |  2913.7202 |  0.00000   |  36178.023 | 2610.6636  |   61.77065 | \n",
       "| 973 | 2          | 30.9       |  967.1328  |  38721.42  |   0.00000  |  880.6843  | 17378.24   | 34.532081  |  391.1320  | 0          | ⋯          | 2292.2790  |   0.00000  |  810.27345 |   93.65825 |  2614.6889 |   970.8893 |  0.00000   |   9763.230 |  493.1664  |    0.00000 | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "     accession_id sample_weight G2P       G3B       G3HP      G4P      \n",
       "892  1            27.0          1391.3143 103708.84  35.89132 5248.4694\n",
       "1692 1            22.1          7734.5149  69932.37   0.00000 2500.7568\n",
       "683  2            15.2          8267.7205 144750.06 202.10448 5545.6431\n",
       "870  2            29.9          1411.4871  27739.70   0.00000  116.5999\n",
       "887  2            31.0          1055.4795  82117.61  88.72688 2589.5366\n",
       "973  2            30.9           967.1328  38721.42   0.00000  880.6843\n",
       "     G2H3B    G4HB      G2H4P     G3MTP ⋯ G6MTH     G5MSP     G7MTH     \n",
       "892  25310.19  0.000000  656.2984 0     ⋯ 3611.0269  32.32934 2951.46171\n",
       "1692 24289.34  0.000000  390.3385 0     ⋯  116.8998  56.07342    0.00000\n",
       "683  78817.75  7.136438 1966.7867 0     ⋯  411.9168  76.65779    0.00000\n",
       "870  24817.58  0.000000  435.3465 0     ⋯ 2256.3011   0.00000   46.88039\n",
       "887  29056.36 32.245193 1213.7386 0     ⋯ 8806.8255 227.51344 3107.01884\n",
       "973  17378.24 34.532081  391.1320 0     ⋯ 2292.2790   0.00000  810.27345\n",
       "     G6MSH      G8MTO      G7MSH      G3BOP    G8MSO      G4BOB     G5BOP     \n",
       "892    96.03157  8243.8638  2142.1924  0.00000  23523.238 1424.3284    0.00000\n",
       "1692  247.84098     0.0000  1401.4957 67.66343  27462.923 1789.0852  920.67350\n",
       "683  1016.59783     0.0000 11407.0228  0.00000 102816.760 8169.7092 3357.24848\n",
       "870     0.00000   577.0562   389.6314  0.00000   7644.041  284.5212    0.00000\n",
       "887   428.95742 18943.1403  2913.7202  0.00000  36178.023 2610.6636   61.77065\n",
       "973    93.65825  2614.6889   970.8893  0.00000   9763.230  493.1664    0.00000"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "head(glucs);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "'data.frame':\t2199 obs. of  24 variables:\n",
      " $ accession_id : int  1 1 2 2 2 2 4 4 4 6 ...\n",
      " $ sample_weight: num  27 22.1 15.2 29.9 31 30.9 17.8 24.6 29.5 18.3 ...\n",
      " $ G2P          : num  1391 7735 8268 1411 1055 ...\n",
      " $ G3B          : num  103709 69932 144750 27740 82118 ...\n",
      " $ G3HP         : num  35.9 0 202.1 0 88.7 ...\n",
      " $ G4P          : num  5248 2501 5546 117 2590 ...\n",
      " $ G2H3B        : num  25310 24289 78818 24818 29056 ...\n",
      " $ G4HB         : num  0 0 7.14 0 32.25 ...\n",
      " $ G2H4P        : num  656 390 1967 435 1214 ...\n",
      " $ G3MTP        : num  0 0 0 0 0 0 0 0 0 0 ...\n",
      " $ G4MTB        : num  322 0 0 0 323 ...\n",
      " $ G3MSP        : num  0 0 0 0 0 ...\n",
      " $ G5MTP        : num  0 0 0 0 80.3 ...\n",
      " $ G4MSB        : num  0 68.6 87 0 22.5 ...\n",
      " $ G6MTH        : num  3611 117 412 2256 8807 ...\n",
      " $ G5MSP        : num  32.3 56.1 76.7 0 227.5 ...\n",
      " $ G7MTH        : num  2951.5 0 0 46.9 3107 ...\n",
      " $ G6MSH        : num  96 248 1017 0 429 ...\n",
      " $ G8MTO        : num  8244 0 0 577 18943 ...\n",
      " $ G7MSH        : num  2142 1401 11407 390 2914 ...\n",
      " $ G3BOP        : num  0 67.7 0 0 0 ...\n",
      " $ G8MSO        : num  23523 27463 102817 7644 36178 ...\n",
      " $ G4BOB        : num  1424 1789 8170 285 2611 ...\n",
      " $ G5BOP        : num  0 920.7 3357.2 0 61.8 ...\n"
     ]
    }
   ],
   "source": [
    "str(glucs);\n",
    "\n",
    "## note that accession_id isn't a factor yet...\n",
    "## it is numeric, so it is important to be explicit..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "glucs$accession_id <- as.factor(glucs$accession_id);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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kbx2aFqaOO1Eb4k+G6RG7NIyz2lbFnk8iyGAAIIIIAAAgi8RyBNgbWRHr2Bctd7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",
      "text/plain": [
       "Plot with title “G2P_per_mg”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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NDXaS1W/FM5myo+QkdDAAEEEEAAAQQKFij0CNZQ3aMLlC8pu2bu/U0Nz1F8Ws4/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\nUYF1V1FrX/s3/po2YV/lq0pcPPmb6K9Qximh+UefL1AuVlaHToY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lwY+M16Vmbo\nN3j3x//hGaNp3/4c5aXM+IrM0G8opyj5tJO1kNfj+5udGff9fUWJW77bdY9u5PX1jm+scReE\n7r816r9F497H7yu+f2+3l3GeUQYpbn7D9/wwz+PXKW4u6JYpnjdXcVHmcR9B2lAppF2uG3kd\np+VxYxcX+bSxWsiuLiZD6+gI1npa0M+F8eEGBQxtbJdLFe/Ta4oLLI//Tkk277MNbfyW4vv3\ndp+v1Cuh7awRr8P9CzLjnt5LSdO8fb6f/6f49uE57PFvKC6svT1xf3js1d3afqMx38bPIRfZ\nHnch9obymEJDAAEEEKgRgWwFlosavzG4SPFRBzf/7/4Oxf3xG/6YTJ/fCG9U9lBcgB2h+A3p\nPaWP0l77tGb6DfQBxUex3EYrryjvKv0VtzTblbbA8vb7DfHrioswb8edivf3x0rcJmvCb8Zx\nm6IJb6u3280Fj9/0ffsLlUKa35B9+wMLuXF0GxckJyouCBYpzyujlNB6acT34yLTj0XIMRr/\ngTJD8TwXZ4U2FzC+j3nKxzIr8fPE14e5Py7Eff/ue0gZrritq1yruP8EJbRQYLmguUn5pBI/\nP8NyHQ29fX4OvK98QumuHKwsVMLz+DsaH6CMUiYp3pZtlNC+phH3+W+qb6bThZ7t3P94po8B\nAggggEANCCQLLL8Z+8iC3whDYRMY/KYxW/GbUHgDCQXWNPX1UOJ2oyb8xuJl2muPaKZPaYXi\nKiz7KY34jewLStrtSltgeTv9Bhk3F0vu95tv3JIFlgsUH135h+LtDK2nRlycHRo6Ug5dxPn+\nXdwm2x7qOEyxkeOixAkFsUZbm4sUryfkPI27gAgtFFhhfrbhf4SFCxza0Ov9buL2NnIBNzPq\nf1XjXtbFU9z8nPPzxAVLcPYyXtbr8LoKbWH7vpVYQSiyz0n0/0TTvl8f2QrtHY28qSS34/Pq\n87IUWEKgVZ6A/6dDQwCB8guM1F34f+l/Vvy/97j5mpZblW8oWytPK6F5fEWYyAynZYb9Ev3x\nZIMmdlAeVd6OZ2jcb26O2yilkO3ybfNtExMLTstMt7f9XmSZ4iJxX8XrcGHpAs9H4C5QCm0+\nKuM2VJnbMvbhPxdqdJ8PJ1vHjtCYjzTGbb4mRiguvk5Sfqi4MNhN+UAJbY5GzggTGvZRNlZ8\nBO0iZW/FR7Vc5BTark3c0EeH7lW+rKyn+Dm0leIi1vs/Ronbk5rwfg9X4qLsOU17XcW2+Dnt\ndb2gHKY84Ymozc6Mr5sZbqSht/+3SnI7XLy5AKchUJECFFgV+bCwUVUo4Dc3N/9PPFsL/Ztr\nZvxmlCyOfFsXHm4uonK1zTSjr+KjNe21QrervXUm5yX3IZ/tD+v4nEauV/ZXdld+oUxVfITw\n54oLh7Rthm6wibKL4mItbv+piauiDh8l+UQ0HY8u1YR9naeUwYq318vfrITm04d/ChPR0K+/\nLhpdlH1auUEppLlATxaKXo/30217xdvgtoXioilX8/MvLrBsXYoWnt9hXaEw8vVdcQv9oc//\nSXAL+7Jmas2/Pv2dfG7F8xlHYK0K+A+chgAC5Rfwm6Cbi55sbd1MZyg+wjK+fqWQFo7S+GhJ\ne63Q7apPrDRsf6K7ZbLQffCN5ygHKFsqhyqHKPspP1X2UHIVP5qVs43XnL2VcYoLtbj9LZ7Q\n+Ggl3/twEeUCy0dmblY6ai4QfBsXWE6hBVZ33daPR7MSt3CE0EVIQ2bG3zW8KF4oMf5iYrqQ\nAjaxipbJQtfzQWZlg7KtVH39lbggzLEY3Qh0vkD4o+v8e+YeEagtAZ+acfMbdrYW+pP/08+2\nbD5907WQ39R8JCvZhqrjfuUHStrtCgVgr8RKs91PYpHUky5GP6ZspUxSLlNcZG2k+E31YGW4\nkra5qPKRkhOVvZQ0zWY+NXhAlhuFQjIUBVkW+UjXOpme4PqRBfLo6KFlRmZZbmv1LVFeVV5X\nXIANUR7IEm/zQuV9pZKat90tHMlaM7XmXz/ngl/czzgCFSFAgVURDwMbUQMC72gfH1NcFIxL\n7O92mj5cmao8l5hX6KTf7O9WdlKSRcQ31Xeg4iPYabcrnIpKFhgnal1uySNba3rz+3elFouP\n8Pl01cPKXxI3n6dpF6IukgopTN7Q7c5VfNTtHmVfJdka1fF15YTEDL/h+5q17yT6Pfm9TJ8L\nmHyai50fZxb8Rz43aGeZf0/Mc0Hi55r97OTTmfcqvnj9k0rcttXEBOVPiouwSmp+fvpaqwOV\nj0cb5sfngmiaUQQQQACBGhG4WvvpN6u4EPGbm48q+bqT0xS/afhN2QWDE/8vfYymfftfKcl2\njjo8b5/kjMT0Fpr2G+t8xfdziPI/io9WuMgYqLil2S6fLvN9+43vTOVE5TZltuLrfDwemt8Y\nvezg0JEZNmT6H0z0/yPT/78afiUzz8t4HV7vCYqvibpacd/NSmi7a8R9j4aODoZ+g7atb+NM\nU65Rfq7cqbytuN9WZyg9FTcXkD6N6HkuWI5VjlRcqLnvRiW0XhoJ6/D2h9yh8QmKL9r2fJ+2\ns0khLRi7oP614qLqG8q7ylvKMCW0rTTi54PzU8UFy+mKj26tUsYpofk54W37RegocBi2L/kc\nOC+z/o8l1ntipv/4qH9Ljc9W/LdzleLbPqF4H72Njyo0BBBAAIEaEQhFwAGJ/R2r6acUvzE4\nS5T7FR9pitsYTXi+i4BkO0cdnrdPckaWaR+deFwJ9+ehC4PNlLjlu12+jY/euJjyuvzG/ozi\n9U1XblVCy/Xm2qAFfNsHw4KZ4b4aunDzvBczfX5jvlZxAeB+x/d9udJdCS1tgRVu5yLDBY+P\nnoX1+4jPJOX3ynAl2fqp45dKvE2LNf0TJd6mUGCF9Yah78vFzyOKjyb2VgptwfiLWkEoCl24\n3aeMybLSrdU3QfE+hu2ZofETlLhVUoHl7dpIuU6ZqsxRXFxvqngfvK80BBBAAAEEWgT8Ju03\nwB6d5OH721EZ1MH95btdLpK2UYZ0sL5CZq+vG7k4iZuvtXGxuIWS6zTk0Zr3f0ohzffndbuw\n6JvnClwY2dRHWBrzvE2pF7tFK3SR4ULULj5Kta7SUeujBbztI5W1te0dbWOYPyCMJIZDNe19\nvz7RzyQCCCCAAAIIlEjAhapP3fnoWi21uMCq1v32EbZXlOR/Rn6uPhdYPv1NQ6DiBLpV3Bax\nQQgggEB6gfV0E5969anDrtq8D7uk2PhnUyxbikUL2b5ZJbhjF5EunO9UPO5TxAcoJyi+/uoK\nhYYAAggggAACCGQVOEy9vn4q33xey96QWb6jU79arOhWyPYVfadagY9cXar4OjcfsXJmKtco\n/RUaAggggAACCCCAQIEC3XU7X9i+cYG352YIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCA\nAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggg\ngAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAII\nIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAAC\nCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAA\nAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCA\nAAIIIIBAJwj8f+4bnnUTlQHDAAAAAElFTkSuQmCC",
      "text/plain": [
       "Plot with title “G3B_per_mg”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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qT+qvxSOV95UWnUZmnGZOWORgvQjwACCCCAAAIIVE0gtcA6TQCXK763qkx7TguN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\nztiphbUbq3TGrnTkXiy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lQ27uLyC0qr\n7TQ90Os8qsQKXCSUaTb08+iCOG6Pa8LH06ydopnenwOihb6S9R0Z9eVHfenQj/twfkaJ6XHZ\nY/9HQ++jXx/3K95XF2/rKnFbUxO3Kt6eXx8uejzu15LXFdpmGnH/iYrX43FnWyWlhf07QQ96\nWPE6ws+Ai+uVlWuz/hnZ0AWcn4e4/a8mwmOfzsbP13CC4uKShgACCCDQZQJFBdYndAz+z95F\nyvLZ8Syj4SWK++M3fBcnfrPzm8JnFBcwKyiXKl72G0qz5jMMNyivKx9VfCbIRdHRih//LcXN\nfeOVl5UPKUMVL/sBxW+6fvMdpYR2pUb8eD8ubt4/9+cLrLLH8JHs8fElwkOyPl+iW0JxW09x\n4fma4gKyleY3Vu/rLq08OHqMnQ5VzlNsdbcyVomb/bytf22S67JlDtAwtK9oxI9rVGDZwbYu\nPNdWUlsoYLyNXysLZSvYXEO/5vyaCM+7j/M2xQVkeC1pdO5Z2Oc0fEAJjw8Flouh3yp7KvHr\nWpOlWtg/H+PZykqKf2bCz5WLqcuVbRRvO3i5eArt0xrx8fkxi2Wd22ro14/7b836GCCAAAII\ndJFAeCPYOdtnv0lNU/yGNDrrCwP/5/+E8pIS3ggu1LjfBPwmETe/sbrf85u13TTTy52SW8j7\ncY1ylTJC+ZLi5b6j5NuX1eF5/xbNSC2w/Pgyx1BUYJ2YbX+naPse3V35vBKKVPeltMe0sPdr\nmYIHba2+vZT3ZXm/hk7Rtvym7/WE+GyLTeP2uCbC/P6GB0QPDAXDH9V3XJSTNO7C5XXF68s/\nv+oq1UIB42JjZO4RX9C01/2prP9D2fQfsul44H3zsuE5DgXWFPUtHC+YOB72z89VvJ7NNe3t\n+WdllBKaX9czlLtCh4ZPKZOV+PGefZDidVBgWYM2KALDB2WrbBSBagqsrsPyGRefLXgxd4j+\nbfwi5bPKusrtSmg3h5FsOCkbxm8uuUXmTm6SdV6Ym+k3ll2ivo2y8XOivjDqMwcnK35Tm5/W\n6jG4EPymcolityuUPysuDp1Wm8+uuC2rPDt37K1//kOj2781+ebYPhrzfsRtmiZWU1x8HaYc\nreynbKm8rMQtXyTG81zQ7B93ROMuJp24+azOROV7yi/jGS2M+/XhYi1uPs4fK+E1tFU20/bj\nsvEw8CVCN79GTp87Nu+fuzR4I5pudfSfufXck63oAQ2nRyv169oF1RJZ3yoaLqf8RMnvh4/Z\nZ+NoCAyaAAXWoNGz4QoKvDM7Jv9GXdRC/9qaGRdYT+YWDm+GQ3P9+clQOPkMQLPm/fKbU9Fy\nvlT0muJ9mp/W6jH4Dd2Fi4s8F5+O3yyvVo5XblVaaVP0oDWUdyv351bwfU2fGfX5bMce0XQ8\nahu7OX9XllYOULz875TQ7HtdmCgYunhr1P5TM86OZrpw8/6HIjGa1dJoeN3FDw5n3TbMOtfJ\nhj+MF8qNr52bnpibbnUyv3+hMPL9XfkW5rk/vP5tlW++rJp/TeaXYRqBtgoMb+vaWTkC9RLw\nWSq3cAlw3tRb/y6RjYYCKszx2YpWWngDXrSfB3u/epRFlPCY8JCFNDJSye+T5/sxcQv7H/eF\n8VaPwY//ueKza7sqLlzeq/gS3m7Z9HUaprZr9YDtFJ91OSv34Mtz074k26jAyi06d19dYHn/\n4gIrv1zK9FQtHM7apDyu7LJ+jvPNz6Wf31CEhOf/I+p7Kr9wNh2fTXKXL9cNRGt1PS5E3Zaa\nN+jz72j1uJCkITAoAv39hjwoO8VGEehSgYey/fYbdlEL/fnf2IuWLdP3cLbQWgULf019vkyy\nptJsv9bVfL/RxvsU3mxdeMWtaDvx/FbGfVZkT8XbvFT5ouK+rysuDA5WWmkuqny241BlWyWl\nfVULT1N2LnhQKCTDm3vBIh3XFc5OxTvm593t9nmDNz8Sw0XUNbl4mbgYyx4y6IPx2R6EM1nx\nDvm1unjcwTgCC1qAAmtBi7O9Kgv4N/+/Krsrm+cOdANN7634sorvXRmI5jMxvjTloiRuozTx\nLcVnhPwb/MWK2zcUv1HG7ZvZxEVR57PZeL7AODTrz68jemjT0ZnZ3PgM3w/Ud5niM0JxuyOb\neDXuTBifoGWPV5ZQrlR2UPJtmDo+o3w8N8Nv3L6XLu/qxY70P2ouQrqlHaQdXSm3s1/RtF87\n12f9l2TTfj3YJW6naeJPytZxZweM++fNv0TsovhsZ2je/38PEwwRQAABBLpPwGdJ/CYVFyKb\nadqXPHz/yFGK//P3m/JzWeLftv3m4Mf7vp64+Rcf9/v+pP7aGVrAy/5e2Vv5tHKb4r4jlNDC\nti5Vx37KPkro+6nG46LJl8v8eL+BuVA7VHGR9oTiMxyhYNPom+socww7anmv90Hl+8qqyk7K\nbGWKcqLyHsWFoM/Ova68WwnNhZIf7/0r0/xG+2PFj3EmKeco31Ps8KTi/pcVFxYLK262CMXr\nVRr/sLKvErZ/gcbj5iI2nNmK++PxUzThbR0QdX4l6/Prox1tnFYajv0RjR+i+Gzh+Vn/tzWM\n2y804eX/onxQ8evkTMV9fn2FtplG3PfD0NHiMOyfn6O4DdeE13913JmNT9LQxxLaOzTi1+UM\nxft6gvI35RnF67hFoSGAAAIIdJlAUYHlQ9hE8Q3R/g/e8VkYv1lsqsQtFDhlipP4cfG4iwi/\nUbpICNubpvH82ZcR6jsut9zDmnax4YIi3/x4F1Ne5xzlDmUt5VHlIiW0lGPwG+dvFJ/J8npD\nseE380lZX9jePzW9pRK3UODsEXeWGN9Ny/gMTdiut+Gi7kHlp8pKSr6NUsepyizFyzuvKLa2\nZdw6vcD6pXbW7j5mH8ckxa+FfBuqjq8q/uUgHLOf+98qKyihdVKB5X1aRTlPmag8rfxOWVPx\nMfjMGw0BBBBAoGICfpMepyy0AI7Lb45rK+9UXMg0ai6mXCj57FF/zet8l7JMfwsmzl9Eyy+X\ne4y35TdKF6F2a9RceK3faGY//SM1fx3FBcJi/SwbZntfN1Z8psTFbDc1v/ZcZIQzRHb1cZRp\nq2mhjZRmz0WZ9bR7mTENNrCs+n3sLixpCCCAAAIIINBEYHvNe0pxMUbrXyBfYPX/iO5bYop2\n+X4l/0vM99TnAqtdl1+1ahoCzQWa/abb/JHMRQABBBasgC8Z7qz4slXdms/4vTvhoO9MWHYg\nFm1l/6YOwIYv1Dp8OftSxeO+rO3XyMeVW5RfKDQEEEAAAQQQQKBQYC/1vpGQg7Tshtnyp2jY\n7tbK/g3EPvnMlY/vFcVnrBzfE3eOMlqhIYAAAggggAACCLQoMEKPW1Mpc29hi5vgYQgggAAC\nCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAA\nAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCA\nAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggg\ngAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAII\nIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAAC\nCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggEAZgf8PK2mI76yaSW8AAAAASUVORK5CYII=",
      "text/plain": [
       "Plot with title “G3HP_per_mg”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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o3WjtYGubgaqZymPKoUNReJeyv+Ggr/tuJ4ZbRCQwABBBBAAAEEkgVSr8HKP4B/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",
      "text/plain": [
       "Plot with title “G4P_per_mg”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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5VLlGuVO5VhyhHKY8onFRoCCCCAAAIIIFC1wMCqH9nW9ogee6xynLKd4nuzPqXs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\ngD9x35vfD9d7R17hlim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TH4jdjb9WPD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\nAElFTkSuQmCC",
      "text/plain": [
       "Plot with title “G2H3B_per_mg”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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RDIWmAdJpW/Kj4FeIGyrXK5sp+ykfId5SXFbZLy2e6xfv32jYYMEEAAAQQQQACB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\nXmCNlYpPCS6pUGeulvPpzfUqXJ7FEEAAAQQQQACBdwnkvcCapT3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cORxivV96Jy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\nAAAASUVORK5CYII=",
      "text/plain": [
       "Plot with title “G4HB_per_mg”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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4HlQup65RZl+0htPY1/Jpl/cjSfUQQQQAABBBBAoHACeQussyT0EcWXCv8aad2l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\nAAAASUVORK5CYII=",
      "text/plain": [
       "Plot with title “G2H4P_per_mg”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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lTl+8q2Cg0BBBBAAAEEEEAgEihaYO2mZT+rvKCcrDyiPKp43NoKDQEEEEAAAQQQ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\nqK9VdikD4Ks+eyoPKL7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v6drYX+rXgd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\nBBBAAAEEWkrg/wGOXIMk/HdFJAAAAABJRU5ErkJggg==",
      "text/plain": [
       "Plot with title “G3MTP_per_mg”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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FI7WK+L7GfKpsqGyk+UpZWzFV/VulLZV+EWohAoCCCAAAIIINCaAqkdrFjpcU0c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\ns6CNv8aspW4RDlzQgBo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6Ic1ku7/z1t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\nAgi0lMD/B4BB4oAvDGN2AAAAAElFTkSuQmCC",
      "text/plain": [
       "Plot with title “G4MTB_per_mg”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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1fFg5/VyK2UQRXeYjuNu6zCsQxDAAEEEEAAgToXoMCq3QPkM1iVtjUrHcg4BBBA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\nELBAnrcI/RU4/gDRjyourmgIIIAAAggggAACGQJ5CqwVuv3rir/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CCAAAIIIIAA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\nAAEEEEAAAQQQQAABBCoU+P8BH6oWDNfdCL8AAAAASUVORK5CYII=",
      "text/plain": [
       "Plot with title “G3MSP_per_mg”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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CCAQKkEOlNgBaiNNDJOeZ/iy4TLFZ/p8mXDycopCg0BBBBAAAEEECiNQL0F1hoS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\nyhRlsjJdcZH1jHKBsoZCQwABBBBAAAEEOiVQhjNYp0jo1ETpOQ3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rbWffAb89GK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\nIIAAAqUS+P+SGv9/srWv5wAAAABJRU5ErkJggg==",
      "text/plain": [
       "Plot with title “G5MTP_per_mg”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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BBBBAAAEEECgQSCmwlmj9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\nIIAAAggggEBJgf8PvIVG3dhu97MAAAAASUVORK5CYII=",
      "text/plain": [
       "Plot with title “G4MSB_per_mg”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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hbI2sGKKV7RxA+UgcoBiq/P2kO5Q/E1TZcqQ5Q1XedpA0YqZyoLFX8u1n3KLYrf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zNbmatUU3nbXeFI1sqplT/9XPfpfAqB1SZAB2u10bLi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\nSUVORK5CYII=",
      "text/plain": [
       "Plot with title “G6MTH_per_mg”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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pxqPXPYLgIIIIAAAgiUFGj0i9z5qpySDz0rEEAAAQQQQKBaAo1eYPXUV+X4y6P9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\nwPKOzFR8Nsgf8bCF4rcEn1VmKP7k9Fpsj2un/Nbm8cp2yqMKDQE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bTDOvKbOSDl8YOVLxfwTDE3RtzfdTlj1Wmvd++/Gdo7i1K9sqtgvN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\ngAACCCCAAAIIIIAAAggggAACOQX+P4Zq1QM8AARdAAAAAElFTkSuQmCC",
      "text/plain": [
       "Plot with title “G5MSP_per_mg”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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eLmPfN9NjX1Bq8R63Mth4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\nn8v+x8brSB+j9BKb9fy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AABBBCoOgHO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",
      "text/plain": [
       "Plot with title “G7MTH_per_mg”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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AABBBCocwHuwarzJ4jdQwABBBBAAIH+J0CB1f+eM/YYAQQQQAABBOpcgAKrzp8g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\nHurbe+7vSfSnzfsy5nzFn+21QKEhgAACCCCAAAI1EejqEuF+2sp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DlQaVGmKxco71ZcoL6g+GzNrkpot2jE239X6Ohi6MdO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\nAABJRU5ErkJggg==",
      "text/plain": [
       "Plot with title “G6MSH_per_mg”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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ZjivyIcraymtCnfUu5XaAgggAACCCCAQFkCjV5g+c3r5yjXKWco45T0lax5mvem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\ngNL5T82rpzZWneGrcurpEaEvCCCAAAIINLBAnluEZvDHF/izorp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+X0ZPoaDeOW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\nCCCAAAIIIIAAAggggEA3Av8fW8iDW+kEh5kAAAAASUVORK5CYII=",
      "text/plain": [
       "Plot with title “G8MTO_per_mg”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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231aZoSxQ3H77e3mfP5+XuQ1NTbvrPz5Dtc0lrfp+VP3s2sfrb654\nez7P9lmieP1NFLfxDSU+Zx7XZjoe/dhQQ9v4nK2v2G+y4nNh4xbF52yY8rri8zVSeTUZel44\nf17fbfKyfl34Z87nz+3w63oNZbQSzt8WGrej9+nj9PkbqNjC1j5/9so6Z7uo3uepq3Pmcx/O\nn7e/2jnTtM+92xZ+5tzmpcrOio/LPwt+3fjYfW7dHvssUrZTpik+fz5nbyrzFR+Lz4XPn1+X\nK3/mGht303O6awp+iX7m/bN/vubdrNR98Q9kLRe/mB5S/MIqpszVQn6xhh/aYtYpxzJ+8T6s\n+Ieh1DLh3XnzNn7pzgl6na/8Za/xVb/sNe4fKv8CWU/j/mUxXNlQ4/7B8y8Or+sfyI5f9hr3\nLwv/4thc4/5F619KW2rcPv7FsY3G/cvCvzj8A+kf+I5f9q/87Y5Vvzj0ERD+ZeFf9otnv/yi\n692+XV9/4F4v7zfVsepYeTv+ZTFWyfpl4Xq3J/yycPuX6A1+1S8L/aLfSXU+3nf0C9q/LFqU\nxRrfXsOOX/bqXPkX3AxlgToh/sXhX9bztO7WrUuXvqXxOYp/afh18Lbq/YtygTJbbyyba7jy\nl317u3/Z+zXlXzz+JduquCzWdty26YpfQz5W/6LyL2X/rMW/7DXZ8QYxX8MWZV3F58HHsLba\nOlLD8Mve815WRij+ZZ8uy3Q8U5XOftkPVsdxq7YVq37Z+5fkU8oArbeDEs6ZHX1e9Ga6YmZ0\n/vwLueP8yWLXhtZWn7/wC97Hr75Sq53i87dc9QWLVvDx+XUZftnb1xua07q0dbJGwy/77vxc\neJPpskjnyefZ529jxceRVeyQLrq6utTtblF8XtZUarGsOnb9DM1e0dr6zzfoFSvCOfNrpfvn\npq1tvs5Hi7blczJGWaKUWla1WxuIx0vdXjnX8++DrFJsO4tdLmsfPVfX3u7z559Xnz+30T9X\nlDoQ+KuO8QXFb/zFFL+p+Q31u8UszDIIIIAAAggggEA9CnxEB+0e9a3K3p0A+H8WByi+irRC\n2U+hIIAAAggggAACCGQIuOP0WcW3HtzR8u2avyt/Un6dDB/S0LeNPH+58hmFggACCCCAAAII\nINCFgO/ru0PlZ2PckYrjzpefKbhM2UShIIAAAggggAAC3RIo9NBdtzZa4Sv7QeLhyiDFfxEx\nX6EggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggUCcC9XiLsJZPrT/AjoIAAgggULsC\n/tw5h1LhAnSwKvwE5Wjeb7XsiTmWZ1EEEEAAgeoT8B9p+UOW/QHQlAoWqPVPcq9g+rI37XVt\n8VGFj5kojvZ6LfZ75ebiFq/rpfxp5+7AH6f4E+8pnQt8WLPHK6d3vhhzE4Efa/iA8itEuhTw\nh2H7Y4b8eY2UChegg1XhJyhH8/wZXv4Uen+uF6VrAX89yyQFr66ttkoWeUxDf2YcpXOB/TXb\nH//Ca6tzpzDXX4nkr7PCK4gUHq5feBZzKk2gqdIaRHsQQAABBBBAAIFqF6CDVe1nkPYjgAAC\nCCCAQMUJ0MGquFNCgxBAAAEEEECg2gXoYFX7GaT9CCCAAAIIIFBxAnSwKu6U0CAEEEAAAQQQ\nqHYBOljVfgZpPwIIIIAAAghUnAAdrIo7JTQIAQQQQAABBKpdgA5WtZ9B2o8AAggggAACFSdA\nB6viTgkNQgABBBBAAIFqF6CDVe1n8J/t9ye5L/vnJGNdCNgKry6QktnBya8xStcC/Cx2bRQv\ngVes0fl4+BkMP5OdL81cBBAoi8BQbWWDsmypPjayiQ5zYH0calmOcsuybKU+NjJYhzmqPg61\nLEdpqyFl2VJ9bISfxfo4zxwlAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAAC\nCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAA\nAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCA\nAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCPScQHPPbZot96LAxtrXQYqHs5TlSr2UYTrQ\nDZQRGemvuneUuPg1P07ZS1mhzFEKlTzLFtpGpdQfr4b4eGYXaFCeY82zrHdXba/P0Wrze5Vn\nlKzCa26lyhgN/LO0fYL0djLMGuR5DfTUslnt6q26IdrRbsp+in9XLVCWKumS97Xl9WvRK+3C\nNAJ9InCh9uoOVXuSFRp+SamX8t860HDs6eGNKYStNP1CavnnNL1JajlP5lk2Y/WKqjpDrbHN\n5wu0Ks+x5lnWu6u216ff4J5XFrrxBUq9v+b8H5pblPTP299U505XuuR5DfTUsuk29eb0qdrZ\nTCX2cgfr3IxG5HltefVa9MpgoQqB3hc4XLv0D+3vlLHKXsoExXWfVuqhTNRB+s3wioz8WwTQ\nqPH7FP9ic/2Wijse7yiTlTWUUPIsG9ap1OH71LBlil8TWR2sPMeaZ1l7VNvrc6TaHH5+Outg\n1fNrrklG9yh+Pd2kHKUcpPxMaVOeVQYpoeR5DfTUsqEtfTH0MdllkvJVZUfFHasXFRt+VIlL\nsa8tr1OLXrEF4wj0mYAvOfuHdpriWzahDNCI66cqcX2YX0tD/7JfpNxdxEGdpWX8C+2TqWXP\nyKjPs2xqcxUzubZacn1ybEuSYVYHK8+x5lm22l6fJ8hoRuLkWzeFOlj1/po7KDFyRyBd/qQK\n/4ydmMzI8xroqWXTbeztaf9usskRqR3vmdT7CnooeV5bteoVLBgi0KcCR2nv/sH9r4xWXJrM\n83MktVy20cHZ4LtFHOTDWsYdDT//EBffEnpXeTSqzLNstFpFjfoYbPNbxbcoPJ7VwcpzrHmW\nPSrZZzW8PkNb31Kbj1MeVwp1sOr9Nfcx2UxSTlfS5WRV+HX2zWRGcC3mNdBTy6bb2JvT7jA9\norgTlfWfXV/F8iMdYV6e11YteomitopfAJTqFPDtQBf/AKdLqNsjPaPGpndNjucxDfdVfFvU\nbwD+RRWX/prwsi8r8+IZGvctQ/+i20XxcnmW1eIVW2xyuHKSkj7m0Og8x5pnWW+/ml6ffpO7\nRNlauVXprNT7a+5a4WyuXJOBNCapey0Z5nkN9NSyGc3stSrfGvRx7aC0pvbq26gbKi1KmFfs\na0ur5Pr5ymPrbVPKJNCvTNthM70vsH6yy7czdj0nqdsoY14tVYVfSBfpoLaKDsy/2K5UvqT4\nzdPP1gxQsqxU3fGXhO5ArKt4+WKXnaFlK7WcXUTDetKlml6fd8jKKabwmstWWkfVn1X8H5Y7\nk0XyvAZ6atmkKRU3+LJa5KvnP4paVuxry6vUm1fEVD2jXMGqnnOVbql/OF18WyNdQgdrjfSM\nGpsemxzPmxoerWySDF/Q0L/sv6K4dGbl+bFXnmW9bjWXPMeaZ1mbdLb8nAStGl+fvOb+9RXv\n83ib4k7W5xT/PLrkeQ301LIrW1JZ/56k5pyvvKJcoIRS7GvLy9eTV/CpuiFXsKrulK1q8JJk\nLKuTHO7ph0vPq1aqsZFLdTy/VW5Ugsc0jT+hvKh8XfFfF4Z5WVaaveoZCHv5L+5cill25ZLV\n+29PunS27Wp+ffKaW/317k6Vb6vurVyl/EwJJc9roKeWDW2plOHH1ZCfKLMV/4Xvu0ooxb62\nFmuFevEKNlU5LPQmUpUHU2eNDren1so47lA3P2NeLVXdr4P5uRJ+2YRj8/+gfctnoLK94mk/\nfBtcNLpaCfX2yrPsahupwok8x5pnWVPU6uuT19w/X+hbaPQhZZzizsFnlLjkeQ301LJxe/p6\n3FetfqH4P4EHKr7SHpdiX1tepx68YpuqHOcKVlWeto5GF/MDNr16D6/bLff/EF18Kd3PVc1S\nQkdKo85IWvMAABLVSURBVKsV17+jzFN8FavYZbVoVZeedKnH12c9veb8eU5/Vfzc4pnKT5V0\nyfMa6Kll023qi2l/ftz3lXOVR5VjlZlKnhK/trxeLXvlcanoZbmCVdGnp9PGhf/9HJSxVKh7\nJGNerVStqQN5TJmoZL2Ot00O9KVkaC9fzfItjbj4DWI7xdsKt1TzLBtvqxrH8xxr3mXtEV6L\nsU2oq7bXJ6+5lWdxDw3uVYYq71WyOleqXnWFJpxv14US6sJrwK8tl1C/cmrlv6GulGXj7fTF\nuH83+Sq7O1e3KAcrWZ2rUl5b2lTNefmYKAhUhMDTasUbSnjg0Y0arvh2zhNKrV+hfEbH2K74\nodG47KeJNuWuqPL9Gvey/svCuHxFE67/YFSZZ9lotYodPU4t8zFmfQ5WnmPNs6wxnlaq8fX5\nuNpd6HOw6v01N1g2kxTflvetwa5KntdATy3bVRt7cv5Z2rh/9n6nNHexozyvLW+qFr26IGI2\nAr0ncIp25R9eX31xB+FExW8OvvWzm1Lr5VAdoK86+S8pL1cOU9yB8pvj28rOSij+n+Tzipe/\nWPGylyTT/uUXlzzLxutV6vhxalihDlaeY82zrC2q9fXpn6FCHax6f81dlLyW/PiBr8hk5XTV\nh5LnNdBTy4a29PZwbe1wruKfPf9nL8vKdb4S6JLnteXla83Lx0RBoKIEPqLWzFH8Q+x4/DSl\nXsrROlB/gGg4fncu71f8YYjp4tuDtyu+uhWW/4vGN1DSJc+y6XUrbbqzDpbbmudY8yzrbVfj\n67OzDpaPqZ5fc74yHn52Cg2vNFJU8rwGemrZqDm9Nvo+7amQUVw/MmpRnteWV6slr4iBUQQq\nR8APUW6p7KD4L+fqsWyog/ZVuyFFHLyfd9hdyepYpVfPs2x63WqbznOseZat1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ThQRzZTcWeM0vMC6Q5Wz++x9/dwuna5TDkttesNND1H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",
      "text/plain": [
       "Plot with title “G7MSH_per_mg”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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bbMOY5hCCCAAAIIINAPBCiw6vMgbaTNfk/JW2ANrs9usFUEEEAAAQQQ6AsBCqz6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\nrkJggg==",
      "text/plain": [
       "Plot with title “G3BOP_per_mg”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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LbUxEHKK4rfNumM5kLAn9PZVkkXEf+jeXsrvrqRdb9m\nax23ia2DFf8enYz5RbKctixZKb7C5wLhHuXy1AZdUExVXCSFoiLVpejkZC09XVlDuUXZU0m3\nnprxBeWo1IJ7k2kXPennv2OTZaFPatX8pJe5OPRnpz6iXKUUa3/TQptepxQqYnweP6Q8pfj+\nE9qnNfK0cqZytJJuvrp0heLC4U7lSqUj7Wuplb1d39fvUXye3K5XWpRTFPvG7ReauFXxVclK\nan582N7O+0Y75v3/cTTNKAIIIIDAKhK4TLfjF5O4ENlO00sVf+7jm4qftL+quGBw4v8l+0nd\n6w9V4uYXdc+/PZ7ZxvhGmr9IeVvx7XxQuUjx2x4uMgYrbln26wPq79v3C893lKMVv132muIr\nEx4PLcsxTNBK3q6vcpytrKe4+Tg939s9SvFVn2B7rcZD21kj7vdAmNHO0C+QP1e8jjNFccHx\nI+UG5XXF823lgqCP4uZix5/L8jIXDC6U7Hqx4nn3K962m4ee95gnona+xj3fGRfN3yqZ5/0I\nra9GPO2+9v2nYp9zk3EX0i5691DSzVe9pile9x7lLOUrym+V6YrnP6ysrZTbwjn2fvxScVH1\nReVNxbeR3vbvNc+360LTdgcrf1A8z8VkaL5Pet55YUaZQ/t6Oz7XceulCc//VzwzGZ+i4cvR\n/I017vu3H7ve1zMUu/kYvY1S73PqSkMAAQQQ6KhAKAImpjY0XtP/VvzE7PgtFD/Jb6vELbxw\nDY1naryH4vVuT81va3ILLXhICbfnoV+kN1TiVup+eZ0vK36x97b8wvqo4u35xfwvSmhZjsEv\neFcpvpLl7X5McfPxX6ksV8Ix+LZ/ofRWQstaYIX19tXI9Uq4Xd+Gr7i8oPxGWUdJN19l+6my\nRAn7tFTjLjAGKqH11IiXpwussK++whS3QgVWWP4tjXg7i5Vwm29r/GYlfS41a0VbX2MXKy60\nw3oeusA+SWlUOtLCOT5CG3ld8bbtcqsyTkk3339PUPyfjLA/vg/9WVlLCa2SCizv07rKH5VX\nlFnKtcoGio/Bx0pDAAEEEKgQgQHaD78AdfQFrtTD8e1towxpZ4VS98svlJspa7azvayLV9MK\nwwus1F/zXCxupPgqUqF2qGb+qdCCEub5SpG37Rd2F1ClNBeFmyqbK3GxV8q65fZx0ebbHKu0\n5VBo294/F2I7KL6qlGVddW+zXaclLjJcCHubmyhrKKW0Ueq0teL7XCW3QW3s3DDN97Ff1cZy\nZiOAAAIIIFD1Ai5Ub1J8dY226gTiAmvV3eqqvaUZurlnlfR/hn6keS6wvqrQEOh0Af8PjoYA\nAgh0t4CvevmtV791SCtPwIa+wlVq81uWq7KVs3+vdsIOuoh04X6D4nG/RT1ROUrx569+r9AQ\nQAABBBBAAIGCAgdorj8/VWoOU9+rk/7tvfWsbh1u5exfh29UG/CVq/OVBYqvWDkzlSuUgQoN\nAQQQQAABBBBAoEwBf47NH2wPf+Fa5mZYDQEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBA\nAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQ\nQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEE\nEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAAB\nBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAA\nAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBA\nAAEEECgm8P/D4wVnY9E8DwAAAABJRU5ErkJggg==",
      "text/plain": [
       "Plot with title “G8MSO_per_mg”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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4dATRHAwaqpw8lgapDAnzUmz96EC/fZ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\nSUVORK5CYII=",
      "text/plain": [
       "Plot with title “G4BOB_per_mg”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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3pDtoAAAggggAACCHQRoMDqwsEEAggggAACCCBQvUD/6jdRd1sYoSMepgxS5itz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ACGdT10cXayMlBJt2VVYP1GO/bj5WLTxzRNsWW6tarj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\nAggggAACCCCAAAIIIIBAGQL/H2eIwZseo+o2AAAAAElFTkSuQmCC",
      "text/plain": [
       "Plot with title “G5BOP_per_mg”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## adjust the ion counts by sample weight\n",
    "for( j in 3:ncol(glucs)){\n",
    "    glucosinolateVariableName <- colnames(glucs)[j];\n",
    "    glucs[[paste0(glucosinolateVariableName, \"_per_mg\")]] <- glucs[,glucosinolateVariableName] / glucs[,\"sample_weight\"]; ## in mg\n",
    "}\n",
    "\n",
    "## there are 22 glucosinolate phenotypes, let's look at their distributions\n",
    "options(repr.plot.width=5, repr.plot.height=4)\n",
    "\n",
    "scaledGlucosinolates <- colnames(glucs)[grep(\"per_mg$\", colnames(glucs))];\n",
    "for( col_j in scaledGlucosinolates ){\n",
    "    scaledGluc_j <- glucs[,col_j];\n",
    "    hist(scaledGluc_j, breaks=100, col=\"cadetblue3\", main=col_j, xlab=paste0(\"Ion counts, \", col_j));\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There's a surprising amount of zero-inflation in the data. To analyze data such as these, one can choose between (a) a zero-inflated model, (b) logistic regression (focusing on presence/absence of each metabolite), (c) attempting to standardize the data and analyze it using traditional linear approaches (not recommended but the most common approach; linear models are very robust), (d) analyzing the data as presence/absence data and, separately, abundance data before combining the results using Brown's _P_ value or a weighted Z-score approach. \n",
    "\n",
    "### Let's use linear models to investigate the data, which is what the authors did"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " [1] \"G2P_per_mg\"   \"G3B_per_mg\"   \"G3HP_per_mg\"  \"G4P_per_mg\"   \"G2H3B_per_mg\"\n",
      " [6] \"G4HB_per_mg\"  \"G2H4P_per_mg\" \"G3MTP_per_mg\" \"G4MTB_per_mg\" \"G3MSP_per_mg\"\n",
      "[11] \"G5MTP_per_mg\" \"G4MSB_per_mg\" \"G6MTH_per_mg\" \"G5MSP_per_mg\" \"G7MTH_per_mg\"\n",
      "[16] \"G6MSH_per_mg\" \"G8MTO_per_mg\" \"G7MSH_per_mg\" \"G3BOP_per_mg\" \"G8MSO_per_mg\"\n",
      "[21] \"G4BOB_per_mg\" \"G5BOP_per_mg\"\n",
      "Investigating: G2P_per_mg \n",
      "Investigating: G3B_per_mg \n",
      "Investigating: G3HP_per_mg \n",
      "Investigating: G4P_per_mg \n",
      "Investigating: G2H3B_per_mg \n",
      "Investigating: G4HB_per_mg \n",
      "Investigating: G2H4P_per_mg \n",
      "Investigating: G3MTP_per_mg \n",
      "Investigating: G4MTB_per_mg \n",
      "Investigating: G3MSP_per_mg \n",
      "Investigating: G5MTP_per_mg \n",
      "Investigating: G4MSB_per_mg \n",
      "Investigating: G6MTH_per_mg \n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "singular fit\n",
      "singular fit\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Investigating: G5MSP_per_mg \n",
      "Investigating: G7MTH_per_mg \n",
      "Investigating: G6MSH_per_mg \n",
      "Investigating: G8MTO_per_mg \n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "singular fit\n",
      "singular fit\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Investigating: G7MSH_per_mg \n",
      "Investigating: G3BOP_per_mg \n",
      "Investigating: G8MSO_per_mg \n",
      "Investigating: G4BOB_per_mg \n",
      "Investigating: G5BOP_per_mg \n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "singular fit\n",
      "singular fit\n"
     ]
    }
   ],
   "source": [
    "results <- data.frame(method=character(), glucosinolate_name=character(), H2=numeric(), pvalue=numeric(), stringsAsFactors=FALSE);\n",
    "\n",
    "scaledGlucosinolates <- colnames(glucs)[grep(\"per_mg$\", colnames(glucs))]; print(scaledGlucosinolates);\n",
    "for( col_j in scaledGlucosinolates ){\n",
    "        cat(\"Investigating:\", col_j, \"\\n\");\n",
    "        log_of_y <- log(glucs[,col_j] + 0.01); ## add an offset to avoid 0s which return -Inf\n",
    "        lm.null <- lm(log_of_y ~ 1, data=glucs);\n",
    "        lmer.alt <- lmer(log_of_y ~ 1 + (1|accession_id), data=glucs, REML=FALSE);\n",
    "\n",
    "        results[nrow(results) + 1, \"method\"] <- \"linear\";\n",
    "        results[nrow(results), \"glucosinolate_name\"] <- col_j;\n",
    "\n",
    "        ourEstimate <- r.squared.merMod(lmer.alt);\n",
    "        results[nrow(results), \"H2\"] <- ourEstimate['Conditional'] - ourEstimate['Marginal'];\n",
    "\n",
    "        ## note that the mixed model has to be specified first\n",
    "        ## if sigma is on the boundary, this approach is conservative; consider exactLRT which estimates the p-value using simulations.\n",
    "        ## source: https://bbolker.github.io/mixedmodels-misc/glmmFAQ.html\n",
    "        results[nrow(results), \"pvalue\"] <- anova(lmer.alt, lm.null)[2, \"Pr(>Chisq)\"];\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>method</th><th scope=col>glucosinolate_name</th><th scope=col>H2</th><th scope=col>pvalue</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>linear       </td><td>G2P_per_mg   </td><td>5.194926e-01 </td><td>5.937229e-136</td></tr>\n",
       "\t<tr><td>linear       </td><td>G3B_per_mg   </td><td>4.989630e-01 </td><td>7.346473e-124</td></tr>\n",
       "\t<tr><td>linear       </td><td>G3HP_per_mg  </td><td>5.071535e-01 </td><td>8.838029e-120</td></tr>\n",
       "\t<tr><td>linear       </td><td>G4P_per_mg   </td><td>3.666834e-01 </td><td> 1.641691e-71</td></tr>\n",
       "\t<tr><td>linear       </td><td>G2H3B_per_mg </td><td>7.050472e-01 </td><td>9.713906e-289</td></tr>\n",
       "\t<tr><td>linear       </td><td>G4HB_per_mg  </td><td>1.522374e-01 </td><td> 1.159233e-13</td></tr>\n",
       "\t<tr><td>linear       </td><td>G2H4P_per_mg </td><td>6.352970e-01 </td><td>9.440562e-217</td></tr>\n",
       "\t<tr><td>linear       </td><td>G3MTP_per_mg </td><td>1.585773e-01 </td><td> 4.626363e-21</td></tr>\n",
       "\t<tr><td>linear       </td><td>G4MTB_per_mg </td><td>2.579267e-01 </td><td> 7.941672e-37</td></tr>\n",
       "\t<tr><td>linear       </td><td>G3MSP_per_mg </td><td>2.506799e-01 </td><td> 1.255756e-34</td></tr>\n",
       "\t<tr><td>linear       </td><td>G5MTP_per_mg </td><td>1.112331e-01 </td><td> 5.956378e-07</td></tr>\n",
       "\t<tr><td>linear       </td><td>G4MSB_per_mg </td><td>4.537109e-01 </td><td> 1.415129e-99</td></tr>\n",
       "\t<tr><td>linear       </td><td>G6MTH_per_mg </td><td>1.648877e-14 </td><td> 9.999981e-01</td></tr>\n",
       "\t<tr><td>linear       </td><td>G5MSP_per_mg </td><td>2.756142e-01 </td><td> 2.469766e-39</td></tr>\n",
       "\t<tr><td>linear       </td><td>G7MTH_per_mg </td><td>1.673128e-02 </td><td> 3.529490e-01</td></tr>\n",
       "\t<tr><td>linear       </td><td>G6MSH_per_mg </td><td>4.547944e-02 </td><td> 1.442736e-02</td></tr>\n",
       "\t<tr><td>linear       </td><td>G8MTO_per_mg </td><td>1.589535e-12 </td><td> 1.000000e+00</td></tr>\n",
       "\t<tr><td>linear       </td><td>G7MSH_per_mg </td><td>1.314698e-02 </td><td> 4.577004e-01</td></tr>\n",
       "\t<tr><td>linear       </td><td>G3BOP_per_mg </td><td>7.746160e-02 </td><td> 1.528177e-04</td></tr>\n",
       "\t<tr><td>linear       </td><td>G8MSO_per_mg </td><td>2.392383e-02 </td><td> 2.027322e-01</td></tr>\n",
       "\t<tr><td>linear       </td><td>G4BOB_per_mg </td><td>4.272188e-02 </td><td> 1.619177e-02</td></tr>\n",
       "\t<tr><td>linear       </td><td>G5BOP_per_mg </td><td>1.143020e-16 </td><td> 9.999954e-01</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|llll}\n",
       " method & glucosinolate\\_name & H2 & pvalue\\\\\n",
       "\\hline\n",
       "\t linear           & G2P\\_per\\_mg   & 5.194926e-01     & 5.937229e-136   \\\\\n",
       "\t linear           & G3B\\_per\\_mg   & 4.989630e-01     & 7.346473e-124   \\\\\n",
       "\t linear           & G3HP\\_per\\_mg  & 5.071535e-01     & 8.838029e-120   \\\\\n",
       "\t linear           & G4P\\_per\\_mg   & 3.666834e-01     &  1.641691e-71   \\\\\n",
       "\t linear           & G2H3B\\_per\\_mg & 7.050472e-01     & 9.713906e-289   \\\\\n",
       "\t linear           & G4HB\\_per\\_mg  & 1.522374e-01     &  1.159233e-13   \\\\\n",
       "\t linear           & G2H4P\\_per\\_mg & 6.352970e-01     & 9.440562e-217   \\\\\n",
       "\t linear           & G3MTP\\_per\\_mg & 1.585773e-01     &  4.626363e-21   \\\\\n",
       "\t linear           & G4MTB\\_per\\_mg & 2.579267e-01     &  7.941672e-37   \\\\\n",
       "\t linear           & G3MSP\\_per\\_mg & 2.506799e-01     &  1.255756e-34   \\\\\n",
       "\t linear           & G5MTP\\_per\\_mg & 1.112331e-01     &  5.956378e-07   \\\\\n",
       "\t linear           & G4MSB\\_per\\_mg & 4.537109e-01     &  1.415129e-99   \\\\\n",
       "\t linear           & G6MTH\\_per\\_mg & 1.648877e-14     &  9.999981e-01   \\\\\n",
       "\t linear           & G5MSP\\_per\\_mg & 2.756142e-01     &  2.469766e-39   \\\\\n",
       "\t linear           & G7MTH\\_per\\_mg & 1.673128e-02     &  3.529490e-01   \\\\\n",
       "\t linear           & G6MSH\\_per\\_mg & 4.547944e-02     &  1.442736e-02   \\\\\n",
       "\t linear           & G8MTO\\_per\\_mg & 1.589535e-12     &  1.000000e+00   \\\\\n",
       "\t linear           & G7MSH\\_per\\_mg & 1.314698e-02     &  4.577004e-01   \\\\\n",
       "\t linear           & G3BOP\\_per\\_mg & 7.746160e-02     &  1.528177e-04   \\\\\n",
       "\t linear           & G8MSO\\_per\\_mg & 2.392383e-02     &  2.027322e-01   \\\\\n",
       "\t linear           & G4BOB\\_per\\_mg & 4.272188e-02     &  1.619177e-02   \\\\\n",
       "\t linear           & G5BOP\\_per\\_mg & 1.143020e-16     &  9.999954e-01   \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "method | glucosinolate_name | H2 | pvalue | \n",
       "|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n",
       "| linear        | G2P_per_mg    | 5.194926e-01  | 5.937229e-136 | \n",
       "| linear        | G3B_per_mg    | 4.989630e-01  | 7.346473e-124 | \n",
       "| linear        | G3HP_per_mg   | 5.071535e-01  | 8.838029e-120 | \n",
       "| linear        | G4P_per_mg    | 3.666834e-01  |  1.641691e-71 | \n",
       "| linear        | G2H3B_per_mg  | 7.050472e-01  | 9.713906e-289 | \n",
       "| linear        | G4HB_per_mg   | 1.522374e-01  |  1.159233e-13 | \n",
       "| linear        | G2H4P_per_mg  | 6.352970e-01  | 9.440562e-217 | \n",
       "| linear        | G3MTP_per_mg  | 1.585773e-01  |  4.626363e-21 | \n",
       "| linear        | G4MTB_per_mg  | 2.579267e-01  |  7.941672e-37 | \n",
       "| linear        | G3MSP_per_mg  | 2.506799e-01  |  1.255756e-34 | \n",
       "| linear        | G5MTP_per_mg  | 1.112331e-01  |  5.956378e-07 | \n",
       "| linear        | G4MSB_per_mg  | 4.537109e-01  |  1.415129e-99 | \n",
       "| linear        | G6MTH_per_mg  | 1.648877e-14  |  9.999981e-01 | \n",
       "| linear        | G5MSP_per_mg  | 2.756142e-01  |  2.469766e-39 | \n",
       "| linear        | G7MTH_per_mg  | 1.673128e-02  |  3.529490e-01 | \n",
       "| linear        | G6MSH_per_mg  | 4.547944e-02  |  1.442736e-02 | \n",
       "| linear        | G8MTO_per_mg  | 1.589535e-12  |  1.000000e+00 | \n",
       "| linear        | G7MSH_per_mg  | 1.314698e-02  |  4.577004e-01 | \n",
       "| linear        | G3BOP_per_mg  | 7.746160e-02  |  1.528177e-04 | \n",
       "| linear        | G8MSO_per_mg  | 2.392383e-02  |  2.027322e-01 | \n",
       "| linear        | G4BOB_per_mg  | 4.272188e-02  |  1.619177e-02 | \n",
       "| linear        | G5BOP_per_mg  | 1.143020e-16  |  9.999954e-01 | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "   method glucosinolate_name H2           pvalue       \n",
       "1  linear G2P_per_mg         5.194926e-01 5.937229e-136\n",
       "2  linear G3B_per_mg         4.989630e-01 7.346473e-124\n",
       "3  linear G3HP_per_mg        5.071535e-01 8.838029e-120\n",
       "4  linear G4P_per_mg         3.666834e-01  1.641691e-71\n",
       "5  linear G2H3B_per_mg       7.050472e-01 9.713906e-289\n",
       "6  linear G4HB_per_mg        1.522374e-01  1.159233e-13\n",
       "7  linear G2H4P_per_mg       6.352970e-01 9.440562e-217\n",
       "8  linear G3MTP_per_mg       1.585773e-01  4.626363e-21\n",
       "9  linear G4MTB_per_mg       2.579267e-01  7.941672e-37\n",
       "10 linear G3MSP_per_mg       2.506799e-01  1.255756e-34\n",
       "11 linear G5MTP_per_mg       1.112331e-01  5.956378e-07\n",
       "12 linear G4MSB_per_mg       4.537109e-01  1.415129e-99\n",
       "13 linear G6MTH_per_mg       1.648877e-14  9.999981e-01\n",
       "14 linear G5MSP_per_mg       2.756142e-01  2.469766e-39\n",
       "15 linear G7MTH_per_mg       1.673128e-02  3.529490e-01\n",
       "16 linear G6MSH_per_mg       4.547944e-02  1.442736e-02\n",
       "17 linear G8MTO_per_mg       1.589535e-12  1.000000e+00\n",
       "18 linear G7MSH_per_mg       1.314698e-02  4.577004e-01\n",
       "19 linear G3BOP_per_mg       7.746160e-02  1.528177e-04\n",
       "20 linear G8MSO_per_mg       2.392383e-02  2.027322e-01\n",
       "21 linear G4BOB_per_mg       4.272188e-02  1.619177e-02\n",
       "22 linear G5BOP_per_mg       1.143020e-16  9.999954e-01"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "results;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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AAAIIVFogyz1YSSj/VaFv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\n8P99oiGAAAIIIIAAAgj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      "text/plain": [
       "Plot with title “Heritability of glucosinolates”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "title <- paste0(\"Heritability of glucosinolates\");\n",
    "hist(results[,\"H2\"], breaks=25, col=\"red\", main=title, xlab=expression(paste(\"H\"^\"2\")))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you were interested in mapping the genetic bases of glucosinolates, which would you start with?"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "R",
   "language": "R",
   "name": "ir"
  },
  "language_info": {
   "codemirror_mode": "r",
   "file_extension": ".r",
   "mimetype": "text/x-r-source",
   "name": "R",
   "pygments_lexer": "r",
   "version": "3.5.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}