07-gish.ipynb

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    "### Notebook index\n",
    "\n",
    "[3 Minimal examples](03-minimal.ipynb)  \n",
    "[4 Plotting chromosomes](04-plotting.ipynb)   \n",
    "[5 Multiple OTUs](05-multiple.ipynb)    \n",
    "[6 Changing units](06-units.ipynb)  \n",
    "[7 GISH](07-gish.ipynb)  \n",
    "[8 Groups](08-groups.ipynb)  \n",
    "[9 Circular Plots](09-circular.ipynb)  \n",
    "[10 Plotting alongside phylogeny](10-phylogeny.ipynb)  \n",
    "[11 Citrus](11-citrushelp.ipynb)  \n",
    "[12 Human Karyotype](12-human.ipynb)  "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4706064e",
   "metadata": {},
   "source": [
    "# GISH"
   ]
  },
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    "# press Ctrl + Enter to RUN active cell\n",
    "\n",
    "# SHOW keyboard shortcuts Ctrl + M then H (only jupyter notebooks and colab)\n",
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    "# Ctrl + D (or X) DELETE a line of code\n",
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    "# press Ctrl + M to escape from cell (opposite to ENTER)\n",
    "\n",
    "# then !\n",
    "# B to ADD cell below or A above\n",
    "# M to turn code cell into MARKDOWN\n",
    "# Y turn markdown to CODE\n",
    "# O to toggle OUTPUT\n",
    "# D D to DELETE cell\n",
    "\n",
    "# If in jupyter-lab:\n",
    "# collapse cell clicking in the blue left bar\n",
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    "# if in colab:\n",
    "# remove bar at 80 in tools, preferences, 80 -> 0"
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     "text": [
      "version 2.0.6 See help: ?idiogramFISH - browseVignettes('idiogramFISH') - https://ferroao.gitlab.io/manualidiogramfish\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# install if necessary\n",
    "\n",
    "if (system.file(package = \"idiogramFISH\") == '') {\n",
    "  install.packages(\"idiogramFISH\")\n",
    "}\n",
    "\n",
    "library(idiogramFISH)"
   ]
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    "\n",
    "## GISH of monocentric chromosomes\n",
    "\n",
    "You need the data.frame of chr. sizes, and a d.f. of marks \n",
    "### Chr. sizes:"
   ]
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       "<table class=\"dataframe\">\n",
       "<caption>A data.frame: 13 × 4</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>OTU</th><th scope=col>chrName</th><th scope=col>shortArmSize</th><th scope=col>longArmSize</th></tr>\n",
       "\t<tr><th></th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>1</th><td>Parental 1   </td><td>1</td><td>3.2</td><td>4</td></tr>\n",
       "\t<tr><th scope=row>2</th><td>Parental 1   </td><td>4</td><td>1.5</td><td>2</td></tr>\n",
       "\t<tr><th scope=row>3</th><td>Parental 1   </td><td>5</td><td>4.8</td><td>6</td></tr>\n",
       "\t<tr><th scope=row>4</th><td>Parental 1   </td><td>6</td><td>6.1</td><td>7</td></tr>\n",
       "\t<tr><th scope=row>8</th><td>Allopolyploid</td><td>1</td><td>3.2</td><td>4</td></tr>\n",
       "\t<tr><th scope=row>9</th><td>Allopolyploid</td><td>2</td><td>4.5</td><td>5</td></tr>\n",
       "\t<tr><th scope=row>10</th><td>Allopolyploid</td><td>3</td><td>2.0</td><td>3</td></tr>\n",
       "\t<tr><th scope=row>11</th><td>Allopolyploid</td><td>4</td><td>1.5</td><td>2</td></tr>\n",
       "\t<tr><th scope=row>12</th><td>Allopolyploid</td><td>5</td><td>4.8</td><td>6</td></tr>\n",
       "\t<tr><th scope=row>13</th><td>Allopolyploid</td><td>6</td><td>6.1</td><td>7</td></tr>\n",
       "\t<tr><th scope=row>5</th><td>Parental 2   </td><td>1</td><td>3.2</td><td>4</td></tr>\n",
       "\t<tr><th scope=row>6</th><td>Parental 2   </td><td>2</td><td>4.5</td><td>5</td></tr>\n",
       "\t<tr><th scope=row>7</th><td>Parental 2   </td><td>3</td><td>2.0</td><td>3</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
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      "text/latex": [
       "A data.frame: 13 × 4\n",
       "\\begin{tabular}{r|llll}\n",
       "  & OTU & chrName & shortArmSize & longArmSize\\\\\n",
       "  & <fct> & <chr> & <dbl> & <dbl>\\\\\n",
       "\\hline\n",
       "\t1 & Parental 1    & 1 & 3.2 & 4\\\\\n",
       "\t2 & Parental 1    & 4 & 1.5 & 2\\\\\n",
       "\t3 & Parental 1    & 5 & 4.8 & 6\\\\\n",
       "\t4 & Parental 1    & 6 & 6.1 & 7\\\\\n",
       "\t8 & Allopolyploid & 1 & 3.2 & 4\\\\\n",
       "\t9 & Allopolyploid & 2 & 4.5 & 5\\\\\n",
       "\t10 & Allopolyploid & 3 & 2.0 & 3\\\\\n",
       "\t11 & Allopolyploid & 4 & 1.5 & 2\\\\\n",
       "\t12 & Allopolyploid & 5 & 4.8 & 6\\\\\n",
       "\t13 & Allopolyploid & 6 & 6.1 & 7\\\\\n",
       "\t5 & Parental 2    & 1 & 3.2 & 4\\\\\n",
       "\t6 & Parental 2    & 2 & 4.5 & 5\\\\\n",
       "\t7 & Parental 2    & 3 & 2.0 & 3\\\\\n",
       "\\end{tabular}\n"
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       "\n",
       "A data.frame: 13 × 4\n",
       "\n",
       "| <!--/--> | OTU &lt;fct&gt; | chrName &lt;chr&gt; | shortArmSize &lt;dbl&gt; | longArmSize &lt;dbl&gt; |\n",
       "|---|---|---|---|---|\n",
       "| 1 | Parental 1    | 1 | 3.2 | 4 |\n",
       "| 2 | Parental 1    | 4 | 1.5 | 2 |\n",
       "| 3 | Parental 1    | 5 | 4.8 | 6 |\n",
       "| 4 | Parental 1    | 6 | 6.1 | 7 |\n",
       "| 8 | Allopolyploid | 1 | 3.2 | 4 |\n",
       "| 9 | Allopolyploid | 2 | 4.5 | 5 |\n",
       "| 10 | Allopolyploid | 3 | 2.0 | 3 |\n",
       "| 11 | Allopolyploid | 4 | 1.5 | 2 |\n",
       "| 12 | Allopolyploid | 5 | 4.8 | 6 |\n",
       "| 13 | Allopolyploid | 6 | 6.1 | 7 |\n",
       "| 5 | Parental 2    | 1 | 3.2 | 4 |\n",
       "| 6 | Parental 2    | 2 | 4.5 | 5 |\n",
       "| 7 | Parental 2    | 3 | 2.0 | 3 |\n",
       "\n"
      ],
      "text/plain": [
       "   OTU           chrName shortArmSize longArmSize\n",
       "1  Parental 1    1       3.2          4          \n",
       "2  Parental 1    4       1.5          2          \n",
       "3  Parental 1    5       4.8          6          \n",
       "4  Parental 1    6       6.1          7          \n",
       "8  Allopolyploid 1       3.2          4          \n",
       "9  Allopolyploid 2       4.5          5          \n",
       "10 Allopolyploid 3       2.0          3          \n",
       "11 Allopolyploid 4       1.5          2          \n",
       "12 Allopolyploid 5       4.8          6          \n",
       "13 Allopolyploid 6       6.1          7          \n",
       "5  Parental 2    1       3.2          4          \n",
       "6  Parental 2    2       4.5          5          \n",
       "7  Parental 2    3       2.0          3          "
      ]
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   "source": [
    "parentalAndHybChrSize"
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    "</div>\n",
    "\n",
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   "source": [
    "### Marks' positions data "
   ]
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       "<table class=\"dataframe\">\n",
       "<caption>A data.frame: 15 × 4</caption>\n",
       "<thead>\n",
       "\t<tr><th scope=col>OTU</th><th scope=col>chrName</th><th scope=col>markName</th><th scope=col>chrRegion</th></tr>\n",
       "\t<tr><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>Allopolyploid</td><td>1</td><td>Parental 1</td><td>p  </td></tr>\n",
       "\t<tr><td>Allopolyploid</td><td>1</td><td>Parental 2</td><td>q  </td></tr>\n",
       "\t<tr><td>Allopolyploid</td><td>1</td><td>Parental 2</td><td>cen</td></tr>\n",
       "\t<tr><td>Allopolyploid</td><td>2</td><td>Parental 2</td><td>w  </td></tr>\n",
       "\t<tr><td>Allopolyploid</td><td>3</td><td>Parental 2</td><td>w  </td></tr>\n",
       "\t<tr><td>Allopolyploid</td><td>4</td><td>Parental 1</td><td>w  </td></tr>\n",
       "\t<tr><td>Allopolyploid</td><td>5</td><td>Parental 1</td><td>w  </td></tr>\n",
       "\t<tr><td>Allopolyploid</td><td>6</td><td>Parental 1</td><td>w  </td></tr>\n",
       "\t<tr><td>Parental 1   </td><td>6</td><td>Parental 1</td><td>w  </td></tr>\n",
       "\t<tr><td>Parental 1   </td><td>5</td><td>Parental 1</td><td>w  </td></tr>\n",
       "\t<tr><td>Parental 1   </td><td>1</td><td>Parental 1</td><td>w  </td></tr>\n",
       "\t<tr><td>Parental 1   </td><td>4</td><td>Parental 1</td><td>w  </td></tr>\n",
       "\t<tr><td>Parental 2   </td><td>2</td><td>Parental 2</td><td>w  </td></tr>\n",
       "\t<tr><td>Parental 2   </td><td>1</td><td>Parental 2</td><td>w  </td></tr>\n",
       "\t<tr><td>Parental 2   </td><td>3</td><td>Parental 2</td><td>w  </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 15 × 4\n",
       "\\begin{tabular}{llll}\n",
       " OTU & chrName & markName & chrRegion\\\\\n",
       " <chr> & <dbl> & <fct> & <fct>\\\\\n",
       "\\hline\n",
       "\t Allopolyploid & 1 & Parental 1 & p  \\\\\n",
       "\t Allopolyploid & 1 & Parental 2 & q  \\\\\n",
       "\t Allopolyploid & 1 & Parental 2 & cen\\\\\n",
       "\t Allopolyploid & 2 & Parental 2 & w  \\\\\n",
       "\t Allopolyploid & 3 & Parental 2 & w  \\\\\n",
       "\t Allopolyploid & 4 & Parental 1 & w  \\\\\n",
       "\t Allopolyploid & 5 & Parental 1 & w  \\\\\n",
       "\t Allopolyploid & 6 & Parental 1 & w  \\\\\n",
       "\t Parental 1    & 6 & Parental 1 & w  \\\\\n",
       "\t Parental 1    & 5 & Parental 1 & w  \\\\\n",
       "\t Parental 1    & 1 & Parental 1 & w  \\\\\n",
       "\t Parental 1    & 4 & Parental 1 & w  \\\\\n",
       "\t Parental 2    & 2 & Parental 2 & w  \\\\\n",
       "\t Parental 2    & 1 & Parental 2 & w  \\\\\n",
       "\t Parental 2    & 3 & Parental 2 & w  \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 15 × 4\n",
       "\n",
       "| OTU &lt;chr&gt; | chrName &lt;dbl&gt; | markName &lt;fct&gt; | chrRegion &lt;fct&gt; |\n",
       "|---|---|---|---|\n",
       "| Allopolyploid | 1 | Parental 1 | p   |\n",
       "| Allopolyploid | 1 | Parental 2 | q   |\n",
       "| Allopolyploid | 1 | Parental 2 | cen |\n",
       "| Allopolyploid | 2 | Parental 2 | w   |\n",
       "| Allopolyploid | 3 | Parental 2 | w   |\n",
       "| Allopolyploid | 4 | Parental 1 | w   |\n",
       "| Allopolyploid | 5 | Parental 1 | w   |\n",
       "| Allopolyploid | 6 | Parental 1 | w   |\n",
       "| Parental 1    | 6 | Parental 1 | w   |\n",
       "| Parental 1    | 5 | Parental 1 | w   |\n",
       "| Parental 1    | 1 | Parental 1 | w   |\n",
       "| Parental 1    | 4 | Parental 1 | w   |\n",
       "| Parental 2    | 2 | Parental 2 | w   |\n",
       "| Parental 2    | 1 | Parental 2 | w   |\n",
       "| Parental 2    | 3 | Parental 2 | w   |\n",
       "\n"
      ],
      "text/plain": [
       "   OTU           chrName markName   chrRegion\n",
       "1  Allopolyploid 1       Parental 1 p        \n",
       "2  Allopolyploid 1       Parental 2 q        \n",
       "3  Allopolyploid 1       Parental 2 cen      \n",
       "4  Allopolyploid 2       Parental 2 w        \n",
       "5  Allopolyploid 3       Parental 2 w        \n",
       "6  Allopolyploid 4       Parental 1 w        \n",
       "7  Allopolyploid 5       Parental 1 w        \n",
       "8  Allopolyploid 6       Parental 1 w        \n",
       "9  Parental 1    6       Parental 1 w        \n",
       "10 Parental 1    5       Parental 1 w        \n",
       "11 Parental 1    1       Parental 1 w        \n",
       "12 Parental 1    4       Parental 1 w        \n",
       "13 Parental 2    2       Parental 2 w        \n",
       "14 Parental 2    1       Parental 2 w        \n",
       "15 Parental 2    3       Parental 2 w        "
      ]
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   "source": [
    "dfAlloParentMarks"
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    "</div>\n",
    "<div class=\"verysmall\">"
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      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.frame: 3 × 2</caption>\n",
       "<thead>\n",
       "\t<tr><th scope=col>OTU</th><th scope=col>note</th></tr>\n",
       "\t<tr><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>Parental 1   </td><td>Parental One </td></tr>\n",
       "\t<tr><td>Parental 2   </td><td>Parental Two </td></tr>\n",
       "\t<tr><td>Allopolyploid</td><td>Allopolyploid</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 3 × 2\n",
       "\\begin{tabular}{ll}\n",
       " OTU & note\\\\\n",
       " <chr> & <chr>\\\\\n",
       "\\hline\n",
       "\t Parental 1    & Parental One \\\\\n",
       "\t Parental 2    & Parental Two \\\\\n",
       "\t Allopolyploid & Allopolyploid\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 3 × 2\n",
       "\n",
       "| OTU &lt;chr&gt; | note &lt;chr&gt; |\n",
       "|---|---|\n",
       "| Parental 1    | Parental One  |\n",
       "| Parental 2    | Parental Two  |\n",
       "| Allopolyploid | Allopolyploid |\n",
       "\n"
      ],
      "text/plain": [
       "  OTU           note         \n",
       "1 Parental 1    Parental One \n",
       "2 Parental 2    Parental Two \n",
       "3 Allopolyploid Allopolyploid"
      ]
     },
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   ],
   "source": [
    "# We will use column note to add a note to the right of the karyotype of the \n",
    "# OTU in column OTU\n",
    "notesdf2<-read.table(text=\n",
    "\"           OTU                note\n",
    "\\\"Parental 1\\\"     \\\"Parental One\\\"  \n",
    "\\\"Parental 2\\\"     \\\"Parental Two\\\"  \n",
    "\\\"Allopolyploid\\\"  Allopolyploid  \", header=TRUE, stringsAsFactors=FALSE,fill=TRUE)\n",
    "notesdf2"
   ]
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   "source": [
    "### Plotting \n",
    "\n",
    "<div class=\"fold s\">"
   ]
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      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 1200,
       "width": 1200
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# svg(\"gish.svg\",width=7,height=9 )\n",
    "#png(\"parentalAndHybChrSize.png\", width=700, height=900)\n",
    "\n",
    "# REORDER OTUs\n",
    "\n",
    "parentalAndHybChrSize$OTU<-factor(parentalAndHybChrSize$OTU,levels=c(\"Parental 1\", \"Allopolyploid\",\"Parental 2\") )\n",
    "\n",
    "parentalAndHybChrSize<-parentalAndHybChrSize[order(parentalAndHybChrSize$OTU),]\n",
    "\n",
    "par(mar=rep(0,4) )\n",
    "options(repr.plot.width = 12, repr.plot.height = 12, repr.plot.res = 200)\n",
    "suppressMessages(\n",
    "plotIdiograms(dfChrSize = parentalAndHybChrSize,  # d.f. of chr. sizes\n",
    "              dfMarkPos = dfAlloParentMarks,      # d.f. of marks' positions\n",
    "              cenColor  = NULL,            # no cen. color for GISH\n",
    "              \n",
    "              karHeiSpace=5,               # karyotype height including spacing\n",
    "              karSepar = FALSE,            # equally sized (height) karyotypes\n",
    "              \n",
    "              legend=\"\"                   # no legend\n",
    "              \n",
    "              ,notes=notesdf2              # data.frame with notes NEW\n",
    "              #,OTUasNote=TRUE             # TRY THIS (OTU name to the right)\n",
    "              ,notesTextSize = 1.3         # font size of notes\n",
    "              ,notesPosX = 1.5              # space from chr. (right) to note\n",
    "              ,ruler = FALSE       \n",
    "              \n",
    "              ,moveKarHor = \"Allopolyploid\"# OTU to move to the right\n",
    "              ,mkhValue = 7                # amount to move to right\n",
    "              ,anchor = TRUE               # show anchor for moveKarHor OTUs\n",
    "              ,moveAnchorV = 4             # modify anchor Vertical portion position\n",
    "              ,moveAnchorH = -1.5          # modify anchor Horizon. portion position  \n",
    "              \n",
    "              ,ylimBotMod = 1              # ylim bottom argument mod.\n",
    "              ,xlimRightMod = 4\n",
    ")\n",
    ")\n",
    "# dev.off()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8ab840dc",
   "metadata": {},
   "source": [
    "## GISH of holocentric chromosomes\n",
    "\n",
    "You need the data.frame of chr. sizes, and a d.f. of marks \n",
    "\n",
    "### Chr. sizes: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "38cf1da5",
   "metadata": {
    "attributes": {
     "classes": [],
     "comment": "NA,",
     "echo": "F",
     "id": ""
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.frame: 13 × 3</caption>\n",
       "<thead>\n",
       "\t<tr><th scope=col>OTU</th><th scope=col>chrName</th><th scope=col>chrSize</th></tr>\n",
       "\t<tr><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>Parental 1   </td><td>7</td><td>4</td></tr>\n",
       "\t<tr><td>Parental 1   </td><td>4</td><td>2</td></tr>\n",
       "\t<tr><td>Parental 1   </td><td>5</td><td>6</td></tr>\n",
       "\t<tr><td>Parental 1   </td><td>6</td><td>7</td></tr>\n",
       "\t<tr><td>Parental 2   </td><td>1</td><td>4</td></tr>\n",
       "\t<tr><td>Parental 2   </td><td>2</td><td>5</td></tr>\n",
       "\t<tr><td>Parental 2   </td><td>3</td><td>3</td></tr>\n",
       "\t<tr><td>Allopolyploid</td><td>7</td><td>4</td></tr>\n",
       "\t<tr><td>Allopolyploid</td><td>2</td><td>5</td></tr>\n",
       "\t<tr><td>Allopolyploid</td><td>3</td><td>3</td></tr>\n",
       "\t<tr><td>Allopolyploid</td><td>4</td><td>2</td></tr>\n",
       "\t<tr><td>Allopolyploid</td><td>5</td><td>6</td></tr>\n",
       "\t<tr><td>Allopolyploid</td><td>6</td><td>7</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 13 × 3\n",
       "\\begin{tabular}{lll}\n",
       " OTU & chrName & chrSize\\\\\n",
       " <chr> & <chr> & <dbl>\\\\\n",
       "\\hline\n",
       "\t Parental 1    & 7 & 4\\\\\n",
       "\t Parental 1    & 4 & 2\\\\\n",
       "\t Parental 1    & 5 & 6\\\\\n",
       "\t Parental 1    & 6 & 7\\\\\n",
       "\t Parental 2    & 1 & 4\\\\\n",
       "\t Parental 2    & 2 & 5\\\\\n",
       "\t Parental 2    & 3 & 3\\\\\n",
       "\t Allopolyploid & 7 & 4\\\\\n",
       "\t Allopolyploid & 2 & 5\\\\\n",
       "\t Allopolyploid & 3 & 3\\\\\n",
       "\t Allopolyploid & 4 & 2\\\\\n",
       "\t Allopolyploid & 5 & 6\\\\\n",
       "\t Allopolyploid & 6 & 7\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 13 × 3\n",
       "\n",
       "| OTU &lt;chr&gt; | chrName &lt;chr&gt; | chrSize &lt;dbl&gt; |\n",
       "|---|---|---|\n",
       "| Parental 1    | 7 | 4 |\n",
       "| Parental 1    | 4 | 2 |\n",
       "| Parental 1    | 5 | 6 |\n",
       "| Parental 1    | 6 | 7 |\n",
       "| Parental 2    | 1 | 4 |\n",
       "| Parental 2    | 2 | 5 |\n",
       "| Parental 2    | 3 | 3 |\n",
       "| Allopolyploid | 7 | 4 |\n",
       "| Allopolyploid | 2 | 5 |\n",
       "| Allopolyploid | 3 | 3 |\n",
       "| Allopolyploid | 4 | 2 |\n",
       "| Allopolyploid | 5 | 6 |\n",
       "| Allopolyploid | 6 | 7 |\n",
       "\n"
      ],
      "text/plain": [
       "   OTU           chrName chrSize\n",
       "1  Parental 1    7       4      \n",
       "2  Parental 1    4       2      \n",
       "3  Parental 1    5       6      \n",
       "4  Parental 1    6       7      \n",
       "5  Parental 2    1       4      \n",
       "6  Parental 2    2       5      \n",
       "7  Parental 2    3       3      \n",
       "8  Allopolyploid 7       4      \n",
       "9  Allopolyploid 2       5      \n",
       "10 Allopolyploid 3       3      \n",
       "11 Allopolyploid 4       2      \n",
       "12 Allopolyploid 5       6      \n",
       "13 Allopolyploid 6       7      "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "parentalAndHybHoloChrSize"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b15710bd",
   "metadata": {},
   "source": [
    "</div>\n",
    "<div class=\"verysmall\">"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a4e422de",
   "metadata": {},
   "source": [
    "### Marks' positions data \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "d378f779",
   "metadata": {
    "attributes": {
     "classes": [],
     "comment": "NA,",
     "echo": "F",
     "id": ""
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.frame: 13 × 4</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>OTU</th><th scope=col>chrName</th><th scope=col>markName</th><th scope=col>chrRegion</th></tr>\n",
       "\t<tr><th></th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>1</th><td>Allopolyploid</td><td>7</td><td>Parental 1</td><td>w</td></tr>\n",
       "\t<tr><th scope=row>4</th><td>Allopolyploid</td><td>2</td><td>Parental 2</td><td>w</td></tr>\n",
       "\t<tr><th scope=row>5</th><td>Allopolyploid</td><td>3</td><td>Parental 2</td><td>w</td></tr>\n",
       "\t<tr><th scope=row>6</th><td>Allopolyploid</td><td>4</td><td>Parental 1</td><td>w</td></tr>\n",
       "\t<tr><th scope=row>7</th><td>Allopolyploid</td><td>5</td><td>Parental 1</td><td>w</td></tr>\n",
       "\t<tr><th scope=row>8</th><td>Allopolyploid</td><td>6</td><td>Parental 1</td><td>w</td></tr>\n",
       "\t<tr><th scope=row>9</th><td>Parental 1   </td><td>6</td><td>Parental 1</td><td>w</td></tr>\n",
       "\t<tr><th scope=row>10</th><td>Parental 1   </td><td>5</td><td>Parental 1</td><td>w</td></tr>\n",
       "\t<tr><th scope=row>11</th><td>Parental 1   </td><td>7</td><td>Parental 1</td><td>w</td></tr>\n",
       "\t<tr><th scope=row>12</th><td>Parental 1   </td><td>4</td><td>Parental 1</td><td>w</td></tr>\n",
       "\t<tr><th scope=row>13</th><td>Parental 2   </td><td>2</td><td>Parental 2</td><td>w</td></tr>\n",
       "\t<tr><th scope=row>14</th><td>Parental 2   </td><td>1</td><td>Parental 2</td><td>w</td></tr>\n",
       "\t<tr><th scope=row>15</th><td>Parental 2   </td><td>3</td><td>Parental 2</td><td>w</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 13 × 4\n",
       "\\begin{tabular}{r|llll}\n",
       "  & OTU & chrName & markName & chrRegion\\\\\n",
       "  & <chr> & <dbl> & <fct> & <fct>\\\\\n",
       "\\hline\n",
       "\t1 & Allopolyploid & 7 & Parental 1 & w\\\\\n",
       "\t4 & Allopolyploid & 2 & Parental 2 & w\\\\\n",
       "\t5 & Allopolyploid & 3 & Parental 2 & w\\\\\n",
       "\t6 & Allopolyploid & 4 & Parental 1 & w\\\\\n",
       "\t7 & Allopolyploid & 5 & Parental 1 & w\\\\\n",
       "\t8 & Allopolyploid & 6 & Parental 1 & w\\\\\n",
       "\t9 & Parental 1    & 6 & Parental 1 & w\\\\\n",
       "\t10 & Parental 1    & 5 & Parental 1 & w\\\\\n",
       "\t11 & Parental 1    & 7 & Parental 1 & w\\\\\n",
       "\t12 & Parental 1    & 4 & Parental 1 & w\\\\\n",
       "\t13 & Parental 2    & 2 & Parental 2 & w\\\\\n",
       "\t14 & Parental 2    & 1 & Parental 2 & w\\\\\n",
       "\t15 & Parental 2    & 3 & Parental 2 & w\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 13 × 4\n",
       "\n",
       "| <!--/--> | OTU &lt;chr&gt; | chrName &lt;dbl&gt; | markName &lt;fct&gt; | chrRegion &lt;fct&gt; |\n",
       "|---|---|---|---|---|\n",
       "| 1 | Allopolyploid | 7 | Parental 1 | w |\n",
       "| 4 | Allopolyploid | 2 | Parental 2 | w |\n",
       "| 5 | Allopolyploid | 3 | Parental 2 | w |\n",
       "| 6 | Allopolyploid | 4 | Parental 1 | w |\n",
       "| 7 | Allopolyploid | 5 | Parental 1 | w |\n",
       "| 8 | Allopolyploid | 6 | Parental 1 | w |\n",
       "| 9 | Parental 1    | 6 | Parental 1 | w |\n",
       "| 10 | Parental 1    | 5 | Parental 1 | w |\n",
       "| 11 | Parental 1    | 7 | Parental 1 | w |\n",
       "| 12 | Parental 1    | 4 | Parental 1 | w |\n",
       "| 13 | Parental 2    | 2 | Parental 2 | w |\n",
       "| 14 | Parental 2    | 1 | Parental 2 | w |\n",
       "| 15 | Parental 2    | 3 | Parental 2 | w |\n",
       "\n"
      ],
      "text/plain": [
       "   OTU           chrName markName   chrRegion\n",
       "1  Allopolyploid 7       Parental 1 w        \n",
       "4  Allopolyploid 2       Parental 2 w        \n",
       "5  Allopolyploid 3       Parental 2 w        \n",
       "6  Allopolyploid 4       Parental 1 w        \n",
       "7  Allopolyploid 5       Parental 1 w        \n",
       "8  Allopolyploid 6       Parental 1 w        \n",
       "9  Parental 1    6       Parental 1 w        \n",
       "10 Parental 1    5       Parental 1 w        \n",
       "11 Parental 1    7       Parental 1 w        \n",
       "12 Parental 1    4       Parental 1 w        \n",
       "13 Parental 2    2       Parental 2 w        \n",
       "14 Parental 2    1       Parental 2 w        \n",
       "15 Parental 2    3       Parental 2 w        "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dfAlloParentMarksHolo"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d5361b88",
   "metadata": {},
   "source": [
    "</div>\n",
    "\n",
    "<div class=\"verysmall\">"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aca29d6b",
   "metadata": {},
   "source": [
    "### Plotting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "1162b735",
   "metadata": {
    "attributes": {
     "classes": [],
     "echo": "TRUE,",
     "fig.height": "7,",
     "fig.width": "8,",
     "id": "",
     "message": "FALSE,dev='png'",
     "results": "\"hide\","
    }
   },
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 1100,
       "width": 1200
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "# svg(\"gish.svg\",width=8,height=7 )\n",
    "par(mar=c(0,0,0,0)) \n",
    "\n",
    "options(repr.plot.width = 12, repr.plot.height = 11, repr.plot.res = 200)\n",
    "suppressMessages(\n",
    "plotIdiograms(dfChrSize = parentalAndHybHoloChrSize,  # d.f. of chr. sizes\n",
    "              dfMarkPos = dfAlloParentMarksHolo,      # d.f. of marks' positions\n",
    "              chrColor  = \"gray\",          # chr. color\n",
    "              cenColor  = NULL,            # cen. color when GISH\n",
    "              \n",
    "              karHeight = 3,               # karyotype height without spacing\n",
    "              karHeiSpace=5,               # karyotype height including spacing\n",
    "              distTextChr = 0.8            # separation among chr. and text\n",
    "              \n",
    "              ,ruler=FALSE                 # no ruler\n",
    "              ,legend=\"\"                   # no legend\n",
    "              \n",
    "              ,xlimRightMod = 0            # xlim right arg. modif.\n",
    "              ,xModifier = 100              # separ. among chromatids\n",
    ")\n",
    ")\n",
    "# dev.off()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "263828b7",
   "metadata": {},
   "source": [
    "## GISH of *Citrus* as Yasuda et al. [-@Yasuda2010]\n",
    "\n",
    "For more details on the use of *Citrus* functions go to chapter *Citrus*\n",
    "\n",
    "Parental *C. schweinfurthii*: 14D + 4F (using Guerra nomenclature).\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "60445f00",
   "metadata": {
    "attributes": {
     "classes": [],
     "echo": "TRUE,",
     "fig.height": "7,",
     "fig.width": "8,",
     "id": "",
     "message": "FALSE,dev='png'",
     "results": "\"hide\","
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32mBy default 5S are plotted as dots, to change this behavior make your own dfMarkColor data.frame\u001b[39m\n",
      "\n"
     ]
    }
   ],
   "source": [
    "{\n",
    "#\n",
    "# c. schweinfurthii chr sizes d.f.\n",
    "#\n",
    "\n",
    "cschweinformula<-\"14D + 4F\"\n",
    "require(idiogramFISH)\n",
    "\n",
    "citrusschwein <- citrusSize(D=14,\n",
    "                            F=4 \n",
    "                            ,OTU=\"C. schweinfurthii\"\n",
    "                            ,longArm=1.2)\n",
    "\n",
    "#\n",
    "# c. schweinfurthii CMA and GISH marks\n",
    "#\n",
    "\n",
    "citrusschweinMarkPosDF <- citrusMarkPos(citrusschwein)\n",
    "\n",
    "#\n",
    "#   data.frame of genomic marks\n",
    "#\n",
    "citrusschweinMarkPosDF2 <- data.frame(chrName=c(paste0(\"D_\",1:7),paste0(\"F_\",1:2)),\n",
    "                                    chrRegion=\"w\"\n",
    "                                    ,markName=\"schweingenome\"\n",
    "                                    ,OTU=unique(citrusschwein$OTU)\n",
    ")\n",
    "\n",
    "#\n",
    "#   merge marks pos.\n",
    "#\n",
    "\n",
    "citrusschweinMarkPosDF <- dplyr::bind_rows(citrusschweinMarkPosDF2,citrusschweinMarkPosDF)\n",
    "\n",
    "#\n",
    "#   Inversion of some chr. (D marks up)\n",
    "#\n",
    "\n",
    "csSwap <- swapChrRegionDfSizeAndMarks(citrusschwein,citrusschweinMarkPosDF,c(paste0(\"D_\",1:14) ) )\n",
    "citrusschwein         <- csSwap$dfChrSize\n",
    "citrusschweinMarkPosDF<- csSwap$dfMarkPos\n",
    "\n",
    "#\n",
    "#   mark style\n",
    "#\n",
    "\n",
    "unique(citrusschweinMarkPosDF$markName)\n",
    "{\n",
    "  markStyleschweinDF   <- makedfMarkColorMycolors(\n",
    "    unique(citrusschweinMarkPosDF$markName), c(\"chartreuse3\",\"darkgoldenrod1\") )\n",
    "}\n",
    "\n",
    "#\n",
    "#   d.f. of notes\n",
    "#\n",
    "\n",
    "leftNotesschwein  <- data.frame(OTU=unique(citrusschwein$OTU), note= paste0(\"Female gamete: 7D + 2E\" ) )\n",
    "leftNotesschweinUp<- data.frame(OTU=unique(citrusschwein$OTU)\n",
    "                                , note= paste0(unique(citrusschwein$OTU),\" (\",cschweinformula,\")\" ) )\n",
    "notesschwein<- data.frame(OTU=unique(citrusschwein$OTU), note= \"Yasuda et al. (2010)\" )\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e8757dd5",
   "metadata": {},
   "source": [
    "Parental 'Nanpu' tangor\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "5b2a089d",
   "metadata": {
    "attributes": {
     "classes": [],
     "echo": "TRUE,",
     "fig.height": "7,",
     "fig.width": "8,",
     "id": "",
     "message": "FALSE,dev='png'",
     "results": "\"hide\","
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32mBy default 5S are plotted as dots, to change this behavior make your own dfMarkColor data.frame\u001b[39m\n",
      "\n"
     ]
    }
   ],
   "source": [
    "\n",
    "{\n",
    "  \n",
    "cnanpuformula<-\"1A + 4C + 5D + 8F\" # Guerra nom.\n",
    "\n",
    "#\n",
    "# 'Nanpu' tangor chr. sizes\n",
    "#\n",
    "\n",
    "citrusnanpu <- citrusSize(A=1,C=4,D=5,F=8 # \n",
    "                            ,OTU=\"nanpu tangor\"\n",
    "                            ,longArm=1.2)\n",
    "#\n",
    "# c. nanpu CMA marks\n",
    "#\n",
    "\n",
    "citrusnanpuMarkPosDF <- citrusMarkPos(citrusnanpu)\n",
    "\n",
    "#\n",
    "#   d.f. of genomic marks\n",
    "#\n",
    "\n",
    "citrusnanpuMarkPosDF2 <- data.frame(chrName = c(\"A\",\"C_1\",paste0(\"D_\",1:4), paste0(\"F_\",1:3) ),\n",
    "                                    chrRegion=\"w\"\n",
    "                                    ,markName=\"nanpugenome\"\n",
    "                                    ,OTU=unique(citrusnanpu$OTU)\n",
    ")\n",
    "\n",
    "#\n",
    "#   merge marks pos.\n",
    "#\n",
    "\n",
    "citrusnanpuMarkPosDF <- dplyr::bind_rows(citrusnanpuMarkPosDF2,citrusnanpuMarkPosDF)\n",
    "\n",
    "#\n",
    "#   mark style d.f.\n",
    "#\n",
    "\n",
    "unique(citrusnanpuMarkPosDF$markName)\n",
    "{\n",
    "  markStylenanpuDF   <- makedfMarkColorMycolors(\n",
    "    unique(citrusnanpuMarkPosDF$markName), c(\"chocolate\",\"darkgoldenrod1\") )\n",
    "}\n",
    "\n",
    "#\n",
    "#   invert some chr.\n",
    "#\n",
    "\n",
    "csSwap<-swapChrRegionDfSizeAndMarks(citrusnanpu,citrusnanpuMarkPosDF,c(paste0(\"D_\",1:5) ) )\n",
    "citrusnanpu          <- csSwap$dfChrSize\n",
    "citrusnanpuMarkPosDF <- csSwap$dfMarkPos\n",
    "\n",
    "#\n",
    "#   notes data.frames\n",
    "#\n",
    "\n",
    "leftNotesnanpu  <- data.frame(OTU=unique(citrusnanpu$OTU), note= paste0(\"Male gamete: 1A + 1C + 4D + 3E\" ) )\n",
    "leftNotesnanpuUp<- data.frame(OTU=unique(citrusnanpu$OTU), note= paste0(\"'Nanpu' tangor (\",cnanpuformula,\")\" ) )\n",
    "\n",
    "notesnanpu<- data.frame(OTU=unique(citrusnanpu$OTU), note= \"Yasuda et al. (2010)\" )\n",
    "\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2a8089ee",
   "metadata": {},
   "source": [
    "</div>\n",
    "\n",
    "Merge data.frames from parentals"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "c56d960e",
   "metadata": {
    "attributes": {
     "classes": [],
     "echo": "TRUE,",
     "fig.height": "7,",
     "fig.width": "8,",
     "id": "",
     "message": "FALSE,dev='png'",
     "results": "\"hide\","
    }
   },
   "outputs": [],
   "source": [
    "{ \n",
    "bothParentalsChr   <- dplyr::bind_rows(citrusnanpu, citrusschwein)\n",
    "\n",
    "bothParentalsMarks <- dplyr::bind_rows(citrusschweinMarkPosDF, citrusnanpuMarkPosDF)\n",
    "\n",
    "bothPmarkStyle     <- unique(dplyr::bind_rows(markStyleschweinDF, markStylenanpuDF) )\n",
    "\n",
    "bothPleftNotesUp   <- dplyr::bind_rows(leftNotesschweinUp,leftNotesnanpuUp)\n",
    "\n",
    "bothPleftNotes     <- dplyr::bind_rows(leftNotesschwein,leftNotesnanpu)\n",
    "}\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1b222997",
   "metadata": {},
   "source": [
    "data.frames of the hybrid"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "27d2c645",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32mBy default 5S are plotted as dots, to change this behavior make your own dfMarkColor data.frame\u001b[39m\n",
      "\n"
     ]
    }
   ],
   "source": [
    "{\n",
    "cschnanpuformula<-\"1A + 1C + 11D + 5F\"\n",
    "\n",
    "require(idiogramFISH)\n",
    "\n",
    "#\n",
    "#   hybrid chr. size\n",
    "#\n",
    "\n",
    "citrusschnanpu <- citrusSize(A=1,C=1,D=11,F=5 # \n",
    "                          ,OTU=\"schweinfurthii + nanpu\"\n",
    "                          ,longArm=1.2)\n",
    "#\n",
    "# hybrid CMA marks\n",
    "#\n",
    "\n",
    "citrusschnanpuMarkPosDF <- citrusMarkPos(citrusschnanpu)\n",
    "\n",
    "#\n",
    "#    invert some chr.\n",
    "#\n",
    "\n",
    "csSwap<-swapChrRegionDfSizeAndMarks(citrusschnanpu,citrusschnanpuMarkPosDF,c(paste0(\"D_\",1:11) ) )\n",
    "citrusschnanpu         <- csSwap$dfChrSize\n",
    "citrusschnanpuMarkPosDF<- csSwap$dfMarkPos\n",
    "\n",
    "#\n",
    "#   d.f. of gish marks\n",
    "#\n",
    "\n",
    "citrusschnanpuMarkPosDF2 <- data.frame(chrName=c(paste0(\"D_\",5:11), paste0(\"F_\",1:2) ),\n",
    "                                    chrRegion=\"w\"\n",
    "                                    ,markName=\"schweingenome\"\n",
    "                                    ,OTU=unique(citrusschnanpu$OTU)\n",
    ")\n",
    "\n",
    "citrusschnanpuMarkPosDF3 <- data.frame(chrName=c(\"A\",\"C\",paste0(\"D_\",1:4), paste0(\"F_\",3:5) ),\n",
    "                                       chrRegion=\"w\"\n",
    "                                       ,markName=\"nanpugenome\"\n",
    "                                       ,OTU=unique(citrusschnanpu$OTU)\n",
    ")\n",
    "\n",
    "#\n",
    "#   merge marks\n",
    "#\n",
    "\n",
    "citrusschnanpuMarkPosDF <- dplyr::bind_rows(citrusschnanpuMarkPosDF2,citrusschnanpuMarkPosDF3,citrusschnanpuMarkPosDF)\n",
    "\n",
    "#\n",
    "#   style of marks d.f.\n",
    "#\n",
    "\n",
    "unique(citrusschnanpuMarkPosDF$markName)\n",
    "{\n",
    "  markStyleschnanpuDF   <- makedfMarkColorMycolors(\n",
    "    unique(citrusschnanpuMarkPosDF$markName), c(\"chartreuse3\",\"chocolate\",\"darkgoldenrod1\") )\n",
    "}\n",
    "\n",
    "#\n",
    "#   notes for hybrid\n",
    "#\n",
    "                         # italics!       #  rest: \\\"                 to                           \\\"      \n",
    "name <-  paste0(\"italic('C. schweinfurthii'),      \\\" × 'Nanpu' tangor (CN3) (\", cschnanpuformula,\")\\\"\" ) \n",
    "# to parse italics, use parseStr2lang = TRUE\n",
    "\n",
    "leftNotesschnanpuUp <- data.frame(OTU=unique(citrusschnanpu$OTU), note= name  )\n",
    "notesschnanpu       <- data.frame(OTU=unique(citrusschnanpu$OTU), note= \"'Yasuda et al. (2010)'\" )\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f53e28ac",
   "metadata": {},
   "source": [
    "</div>\n",
    "\n",
    "Plot\n",
    "\n",
    "<div class=\"fold s\">"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "7313f6c9",
   "metadata": {
    "attributes": {
     "classes": [],
     "echo": "TRUE,",
     "fig.height": "7,",
     "fig.width": "12,",
     "id": "",
     "message": "FALSE,dev='png'",
     "results": "\"hide\","
    }
   },
   "outputs": [
    {
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FmzmpADS10EAgEZeQ4MDFy/fn1x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\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Dkfz8/D1+3a666qrLL7+8TA8KfYHOPffcU089tZQb0tPTR48eXeJH991337777lvK\n2JYtW15//fWB4MqVK3d3f8RfjFDSy8vL+7//Fmi/Ut29+OKLW7dujY306tWrVatWu7s//ofh\nm2++uWbNmkpJjt1YvXp1INKkSZNQMvmlue+++2bOnFl82ahRo7///e/xh+BFWcOGDQORQI0s\naWlpjz322ODBg/v163fiiSe2b99+r7326tChw4033rhs2bLY27Kzs1944YXu3buX4xHfffdd\nevIMGjQoSX90AAAAAAB+EZLyz9S33npriZOHvukcqS340AsSShT6Gu2RipFiVfm6RvzFUDGy\nbt26P/zhD7GRBx98sEaNGmHlUyL70RX3wAMPxLfH+sMf/pCdnZ34JPajAQAAAACAKNNQBkia\nunXr9u/fPzaSl5eXyMAFCxbMmzev+DI7O3vgwIHly2HJkiWxlxkZGf369UtwbOPGjQ855JDY\nyNq1a8uXRsCYMWNiL+vUqTNhwoTMzMzEh7du3To2MmfOnLlz5yYlt7S0tIULF37wwQexkbPO\nOqtnz56JjL377rvr1auX+LPCXaD69evff//9e7zthBNOiF+dY489NpGDhuK/bqUkGfEXI+Lp\nVVPjxo0LRM4///xS7j/77LMDBUnbt2+fNGlS8jNj9+IbyjRo0CCUTH5RZs+efccdd8RGHn/8\n8VK6L0VT/fr1AxEFfPE+/vjjF1988Y033vj444+/+eabn3/+Of6ewYMHf/3114n/nQEAAAAA\nAH4hwt3VjdoWvIqRclAxEqBipFqkVwVuv/322MN+evfu3adPnxDzKZH96IooKip68MEHb7jh\nhkD8yCOPvPLKK0NJCQAAAAAAoDJoKAMkU05OTuzlSy+9tG3btj2OmjhxYuzlKaecEn+CSoIK\nCgoaxujWrVuTJk0SH96mTZvyPbcUM2fO/OKLL2Ij11xzTYsWLRKfoVatWvG71y+++GISkktL\nS0tLe+aZZwKR3R1uFq9Zs2ZXXHFF4s8Kd4GuuOKK5s2b7/G2zMzM/fbbLxD8/e9/n5Gx51+a\nv/rVrwKRnTt3lnhnxF+MiKdXTf3www/Tp0+PjdSpU+ess84qZcjee+/do0ePQDA3NzfpuVGK\n+IYy5f4lRYK2bNly7rnnFhYWFkfOPffcwN8xqgUFfElx1VVXjR8/PsHTKQEAAAAA4Jcj9F3d\nSG3Bp4VdkFCi0Ndoj1SMBKgYSYt8elVg0aJFjz32WGzktttuCyuZUtiPLrfly5efeuqpo0aN\nKioqio03bNjwhRdeCJz8BAAAAAAAUK1pKAMk0+mnnx57+tCGDRvefPPNPY7Kz8+PvazIfzH+\nyiuvrIvx3nvvlWl4QUFBuR+9O2+//XYgcvnll5d1kvPOOy9Qm/Lxxx9XKK0Yr732WuzlgQce\n2LFjx8SHDxkyJPGbw12gU089NcE7999//9jLrKys3r17JzKwefPmderUSeTOiL8YEU+vmsrN\nzQ2Uiw0aNKhu3bqljxo6dGggMnPmzG+//TbJybF7sceO7VKmc/Yoh2uuuebf//538eW+++77\n6KOPhphPue21116ByObNm0PJpFp7/PHHW7du/ec//zmRNoUAAAAAAPDLEfqubqS24NPCLkgo\nUehrtEcqRuKpGIl4elXgrrvuij3+pEePHt26dQsxn92xH10ORUVFf//734844oj497xmzZoT\nJ05s3759KIkBAAAAAABUEg1lgGSqVavWgAEDYiN5eXmlD/nqq6++/vrrUmaoMjt37pw7d27S\np/3www9jL4866qj4s4z2qHHjxoGSncBZQOW2cePG+fPnx0YGDhxYphmOO+64li1bJiWZ0lV8\ngQ455JAE78zOzo693HfffeOLMBIcuzsRfzEinl41NW7cuEDk/PPP3+OowYMHZ2ZmxkaKior2\n+KOVJIr/9q+MWlKKvfTSS7EHIaanp48dO7ZBgwYhplRu8a+KbkTls3r16ptuuumII4746quv\nws4FAAAAAACiIvRd3UhtwVeQipFdVIykqRiJfHqVbeHChePHj4+N3HbbbWElUzr70WU1a9as\nzp07X3zxxatXrw58VLt27SlTpvTt2zeUxAAAAAAAACpP5p5vASiLYcOGxW6rT5kypaCgoJQT\nePLz82MvTzvttFD2touKiq655pr169cnd9rCwsJPPvkkNnLccceVb6pDDjlkzpw5xZcrVqzY\nuHFj/fr1K5RfWtqsWbOKiopiI506dSrrJB07dvzhhx8qmEnpkrJAzZo1q+KBuxPxFyPi6VVT\nX375ZaA6qnnz5ieffPIeBzZp0qR3795vvfVWbHD8+PE33XRTklNkN5o2bRqIrFu3LpRMfgmW\nL19+2WWXxUZ+85vf9OrVK6x8Kmjjxo2BSKNGjULJJMoeeeSR+++/Py0tbceOHRs3bly7du2X\nX3750UcfTZ48OXCA3sKFCzt37vz222+fcMIJZXpE48aNH3vssWQl3KpVq2RNBQAAAADAL0FS\n/pn60EMPDUSisKsbnS34ClIxUkzFSBIH7k7EX4yIp1cF7rzzzh07dhRfdunSpWfPniHmUwr7\n0YlbsWLFLbfcMnbs2MAPvV3222+/F154oRw/AHexHw0AAAAAAESZhjJAkvXt27dhw4bFZRxb\ntmx57bXXhg4durv7Aw1lcnJyKje//7Zp06avvvpq+vTpzzzzzOLFi5M+/zfffBM4Deaggw4q\n31R77713ILJq1aqKl1nElm7s0qFDh7JO0qFDh6lTp1YwkxIld4EyM8v5Wy8rK6uCjw6I+IsR\n8fSqqXHjxgUiw4cPr1GjRiJjc3JyAg1l5s2bN2/evMMPPzxp+bF7GspUmaKiogsvvHDNmjXF\nkQ4dOtx7770hplRBCvgS0aBBgwYNGuz637tOsDzxxBMvv/zyhx9++KGHHrr77ru3b99efPPm\nzZsHDBjw1Vdfxf9+KUWdOnWq+G+YAAAAAABQrJL+mToKu7rR2YIvHxUjKkYSoWIkUulVtgUL\nFkyYMCE2cuONN4aVzB7Zj05EYWHhww8/fPvtt8d/uXY5++yzn3rqqYp86exHAwAAAAAAUaah\nDJBk2dnZZ5111t/+9rfiSF5e3u4aysydO3fBggXFl3Xq1Onfv38lJbZixYp//etfixYtWrx4\n8eLFi5csWbJ48eIVK1ZU0uN2Wbt2bSAyatSoUaNGJWXyFStWHHDAARWcZOXKlYHIfvvtV9ZJ\n9t9//wqmkRbSAoUl4i9GxNOrjoqKinJzcwPBM844Y8OGDYkM79mzZ2ZmZmFhYWwwNzf3vvvu\nS1qK7F78iXPx3yMkxV/+8pd33nmn+DI7O3vcuHE1a9YMMaUKiv8eV8CXuHr16t122229e/fu\n27dvbNHq6tWrH3nkkTvvvDPE3AAAAAAAIHR2dctExUiJVIyEIuIvRsTTq2yjR4/euXNn8WXb\ntm1PP/30EPMpnf3oPfroo4+uvPLKefPmlfhpu3btHnnkkX79+lVxVgAAAAAAAFVJQxkg+XJy\ncmIbykydOnXjxo0lnjCTn58fe3n66afvtddeScxkwYIFL7744syZM2fNmrVmzZokzpygSm06\nsHnz5opPsm7dutjL9PT0cixBvXr1yvf00BcoLBF/MSKeXnX0/vvvL1u2LBDs2bNnRebMzc29\n995709PTKzIJiWjatGkg8tVXX4WSSWqbN2/eLbfcEhu56667jjzyyLDyqbg1a9YEfrVlZGQ0\naNAgrHyqqZNOOumZZ54555xzYoOPPfbYzTffXKdOnbCyAgAAAACA0NnV3aPQCxKiv0YqRkIR\n8Rcj4ulVqtWrVwfOCrrqqqsyMjLCyqd09qNLt379+ptuuunpp58uKiqK/7R+/fq33HLLtdde\nW6tWrarPDQAAAAAAoCppKAMkX69evZo1a7Zq1apdl9u2bXv55ZcvuOCC+DsDDWVycnKSlcOc\nOXNGjRo1Y8aMZE1YPpVaZvHzzz9XfJJAeVDdunXL0Z+iHOVBEVmgsET8xYh4etXRuHHjkj7n\n0qVLZ86c2bVr16TPTED8CWmffvpp0p+yYMGCZ555JjZSs2bNu+++O+kPiqZt27YNHz5827Zt\nxZGuXbtef/31IaZUcZ9//nkgcuihh2Zm+v9fZTZs2LCHHnpo1qxZxZE1a9bk5eVdfPHFIWYF\nAAAAAADhsqtbiogUJER/jVSMhCLiL0bE06tUTz311E8//VR8WbNmzUsuuSTEfEpnP7oUn3zy\nybBhw7799tv4j2rUqHHZZZfdcccde++9d9UnBgAAAAAAUPVsIAHJl5mZOXjw4CeeeKI4kpeX\nF99Q5vPPP//3v/9dfFm3bt1+/fpV/OkFBQUjRox49tlnd+7cmeCQdu3a9e7dOycnZ/To0W+/\n/XbFcyi2Y8eOJM4WsH379opPsnXr1tjLctQGpaWllakcIVILFJaIvxgRT6/a+emnn1544YXK\nmDk3NzfpDWV69uxZjrq9Hj16JHJb//79p0yZUtbJQ9ezZ89A5Isvvti6dWvt2rWT+JS33nrr\n/vvvj4107NgxWQ1lor+sCxYs+PLLL4svs7Oz77zzzmXLliUyNrakLy0traioKL4sLDs7u0WL\nFhVMsqziC/iOP/74JM4f/WVNovPPPz+2oUxaWtrXX38dVjIAAAAAABAFdnVLFKmChOivkYqR\nUET8xYh4epWnsLDwsccei40MHTq0adOmYeWzR/ajd+eBBx645ZZbSnzZTjvttPvvv//QQw+t\npEcDAAAAAABEkIYyQKXIycmJbSjzzjvvrFmzpkmTJrH35Ofnx16eccYZFf+P87dt2zZo0KBS\nKkhq1qx58MEHt2/f/oADDmjfvv3BBx982GGHNW7ceNenDzzwQ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aDzHEhccPlHbOiNLUOwc7z9ZoVLvoitw7G2Aw7M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\nduyBBx6wuciNGze6dLH+AvbCCy988MEHVrE4ta5duzZmzJjCwkLzx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/HuT4zKCiPD/pmh3nZDebXYCd+leDQ1LEL0SGe37v4CAKKQzoHT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\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      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 1800,
       "width": 3000
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "#\n",
    "#   plot of parentals only\n",
    "#\n",
    "\n",
    "{\n",
    "par(mar=rep(0,4), oma=rep(0,4) ) \n",
    "\n",
    "options(repr.plot.width = 20, repr.plot.height = 12, repr.plot.res = 300)\n",
    "suppressMessages(\n",
    "plotIdiograms(callPlot=T,\n",
    "              dfChrSize= bothParentalsChr,   # chr. size data.frame\n",
    "              dfMarkPos= bothParentalsMarks, # mark position data.frame \n",
    "              dfMarkColor=bothPmarkStyle,    # mark style d.f.\n",
    "              \n",
    "              orderChr = \"original\"   # order of chr. as in d.f.\n",
    "              \n",
    "              ,chrWidth = .5          # chr. width\n",
    "              ,chrSpacing=.5          # separ. among chr.\n",
    "              ,karHeight=4            # kar. height\n",
    "              ,karHeiSpace=5          # anchor height\n",
    "              \n",
    "              ,chromatids = FALSE     # don't use chromatids\n",
    "              ,chrColor= \"white\"      # chr. color\n",
    "              \n",
    "              ,ruler=FALSE            # don't use ruler\n",
    "              ,chrId=\"\"               # don't use chr. name\n",
    "              ,chrIndex = \"\"          # don't use chr. indices\n",
    "              ,morpho=\"\"              # don't use morphology\n",
    "              ,karIndex = FALSE       # don't use kar. indices\n",
    "              ,colorBorderMark=\"black\"# color of border of marks\n",
    "              ,addOTUName = F         # do not add OTU names\n",
    "              \n",
    "              ,lwd.chr = 1.6          # border width\n",
    "              ,lwd.marks=1            # border width marks\n",
    "              ,gishCenBorder=T        # cen. border of gish as mark color\n",
    "              ,hideCenLines=1.75      # hide cen. border\n",
    "              \n",
    "              ,legend=\"\"              # no legend for marks\n",
    "              \n",
    "              ,leftNotes  =  bothPleftNotes   # data.frame with left notes\n",
    "              ,leftNotesUp=  bothPleftNotesUp # data.frame with Up left notes\n",
    "              ,leftNoteFontUp =3      # italics\n",
    "              \n",
    "              ,leftNotesTextSize = 1.3     # font size of notes\n",
    "              ,leftNotesUpTextSize = 1.3   # font size of notes\n",
    "              \n",
    "              ,leftNotesPosX = 0      # horizontal pos. of left notes\n",
    "              ,leftNotesPosY = 0      # vertical pos. of left down notes\n",
    "              \n",
    "              ,leftNotesUpPosX = 0    # horizontal pos. of left up notes\n",
    "              ,leftNotesUpPosY = 2    # vertical pos. of left up notes\n",
    "              \n",
    "              ,verticalPlot=FALSE     # horizontal plot\n",
    "              ,karSpaceHor=3          # horizontal spacing among kar.\n",
    "              \n",
    "              ,karAnchorLeft = \"C. schweinfurthii\" # anchor to the left of\n",
    "              ,anchor=TRUE            # add anchor\n",
    "              \n",
    "              ,ylimBotMod = 1         # modify ylim bottom argument\n",
    "              ,ylimTopMod = 0         # modify ylim top argument\n",
    "              ,xlimLeftMod =0         # modify left xlim\n",
    "              ,xlimRightMod = 2       # modify right xlim\n",
    "              \n",
    ")\n",
    ")\n",
    "}\n",
    "\n",
    "#  add plot of hybrid over parents plot\n",
    "\n",
    "{\n",
    "suppressMessages(\n",
    "     plotIdiograms(callPlot=FALSE,                     # plot over previous plot\n",
    "                  dfChrSize= citrusschnanpu,          # chr. size data.frame\n",
    "                  dfMarkPos= citrusschnanpuMarkPosDF, # mark position data.frame \n",
    "                  dfMarkColor=markStyleschnanpuDF,    # mark style d.f.\n",
    "                  \n",
    "                  orderChr = \"original\",  # order of chr. as in d.f.\n",
    "                  \n",
    "                  chrWidth = .5,          # chr. width\n",
    "                  chrSpacing=.5,          # separ. among chr.\n",
    "                  karHeight=4             # kar. height \n",
    "                  ,chromatids = FALSE     # don't use chromatids\n",
    "                  ,chrColor= \"white\"      # chr. color\n",
    "                  \n",
    "                  ,ruler=FALSE            # don't use ruler\n",
    "                  ,chrId=\"\"               # don't use chr. name\n",
    "                  ,chrIndex = \"\"          # don't use chr. indices\n",
    "                  ,morpho=\"\"              # don't use morphology\n",
    "                  ,karIndex = FALSE       # don't use kar. indices\n",
    "                  ,colorBorderMark=\"black\"# color of border of marks\n",
    "                  ,addOTUName=F           # don't add OTU name\n",
    "                  \n",
    "                  ,lwd.chr = 1.6          # border width\n",
    "                  ,lwd.marks=1            # border width marks\n",
    "                  \n",
    "                  ,leftNotesUp = leftNotesschnanpuUp # up notes: name of hybrid\n",
    "                  ,parseStr2lang = TRUE   # for italics, see notes data.frame\n",
    "                  ,notesTextSize = 1.3    # font size of notes\n",
    "                  ,leftNotesUpTextSize = 1.3   # font size of notes\n",
    "              \n",
    "                  ,leftNotesPosX = 0      # horizontal pos. of notes\n",
    "                  ,leftNotesUpPosY = 2    # vertical pos. left up notes\n",
    "                  ,notes = notesschnanpu  # right notes - authors\n",
    "                  ,notesPosX=3            # notes hor. pos\n",
    "                  \n",
    "                  ,ylimBotMod = 1         # modify ylim bottom argument\n",
    "                  ,ylimTopMod = -5        # modify ylim top argument\n",
    "                  ,xlimLeftMod = 0        # modify left xlim\n",
    "                  ,xlimRightMod = 2       # modify right xlim\n",
    "                  \n",
    "                  ,gishCenBorder=T        # cen. border as mark color\n",
    "                  ,legend=\"\"              # no legend for marks\n",
    "                  ,hideCenLines=1.75      # hide cen. lines\n",
    "                  ,moveAllKarValueHor=9.5 # move kar. to right\n",
    "                  ,moveAllKarValueY =-10  # move kar. down\n",
    "    )\n",
    "    )\n",
    "  } # hybrid\n"
   ]
  }
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