code/binding_site_reactivities/plp_profiling.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# <a id='toc1_'></a>[Binding site reactivity (via Nano-DMS-MaP)](#toc0_)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Table of contents**<a id='toc0_'></a>    \n",
    "- [Binding site reactivity (via Nano-DMS-MaP)](#toc1_)    \n",
    "  - [Summary](#toc1_1_)    \n",
    "  - [Data Loading](#toc1_2_)    \n",
    "  - [Visualization of reactivity (gggenomes)](#toc1_3_)    \n",
    "  - [Correlation analysis](#toc1_4_)    \n",
    "    - [Correlation of binding site reactivity and PLP efficiency](#toc1_4_1_)    \n",
    "    - [Correlation of junction reactivity and PLP efficiency](#toc1_4_2_)    \n",
    "\n",
    "<!-- vscode-jupyter-toc-config\n",
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    "\t/vscode-jupyter-toc-config -->\n",
    "<!-- THIS CELL WILL BE REPLACED ON TOC UPDATE. DO NOT WRITE YOUR TEXT IN THIS CELL -->"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <a id='toc1_1_'></a>[Summary](#toc0_)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "source": [
    "The reactivity of binding sites is drastically reduced, when PLPs are bound.\n",
    "This indicates, that binding indeed happens in the expected locations.\n",
    "There is a correlation between binding site reactivity (without PLP) and PLP efficiency (defined here as the median number of spots per cell when only this specific PLP is used, [see the plp_individual results](../spot_analysis/plp_individual.ipynb)).\n",
    "A possible explanation is, that regions with higher reactivity are more easily accessible, which facilitates PLP binding."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "vscode": {
     "languageId": "r"
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   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "── \u001b[1mAttaching core tidyverse packages\u001b[22m ──────────────────────── tidyverse 2.0.0 ──\n",
      "\u001b[32m✔\u001b[39m \u001b[34mdplyr    \u001b[39m 1.1.4     \u001b[32m✔\u001b[39m \u001b[34mreadr    \u001b[39m 2.1.5\n",
      "\u001b[32m✔\u001b[39m \u001b[34mforcats  \u001b[39m 1.0.0     \u001b[32m✔\u001b[39m \u001b[34mstringr  \u001b[39m 1.5.1\n",
      "\u001b[32m✔\u001b[39m \u001b[34mggplot2  \u001b[39m 3.5.1     \u001b[32m✔\u001b[39m \u001b[34mtibble   \u001b[39m 3.2.1\n",
      "\u001b[32m✔\u001b[39m \u001b[34mlubridate\u001b[39m 1.9.3     \u001b[32m✔\u001b[39m \u001b[34mtidyr    \u001b[39m 1.3.1\n",
      "\u001b[32m✔\u001b[39m \u001b[34mpurrr    \u001b[39m 1.0.2     \n",
      "── \u001b[1mConflicts\u001b[22m ────────────────────────────────────────── tidyverse_conflicts() ──\n",
      "\u001b[31m✖\u001b[39m \u001b[34mdplyr\u001b[39m::\u001b[32mfilter()\u001b[39m masks \u001b[34mstats\u001b[39m::filter()\n",
      "\u001b[31m✖\u001b[39m \u001b[34mdplyr\u001b[39m::\u001b[32mlag()\u001b[39m    masks \u001b[34mstats\u001b[39m::lag()\n",
      "\u001b[36mℹ\u001b[39m Use the conflicted package (\u001b[3m\u001b[34m<http://conflicted.r-lib.org/>\u001b[39m\u001b[23m) to force all conflicts to become errors\n",
      "\n",
      "Attaching package: ‘gggenomes’\n",
      "\n",
      "\n",
      "The following object is masked from ‘package:dplyr’:\n",
      "\n",
      "    pick\n",
      "\n",
      "\n",
      "The following object is masked from ‘package:graphics’:\n",
      "\n",
      "    layout\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "library(tidyverse)\n",
    "library(RcppRoll)\n",
    "library(gggenomes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [],
   "source": [
    "options(repr.plot.res = 300, repr.plot.width=8, repr.plot.height=4)\n",
    "theme_set(theme_light())\n",
    "theme_update(text = element_text(family = \"Calibri\"), strip.text = element_text(colour = 'black'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <a id='toc1_2_'></a>[Data Loading](#toc0_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[1m\u001b[22mNew names:\n",
      "\u001b[36m•\u001b[39m `` -> `...1`\n",
      "\u001b[1mRows: \u001b[22m\u001b[34m6376\u001b[39m \u001b[1mColumns: \u001b[22m\u001b[34m4\u001b[39m\n",
      "\u001b[36m──\u001b[39m \u001b[1mColumn specification\u001b[22m \u001b[36m────────────────────────────────────────────────────────\u001b[39m\n",
      "\u001b[1mDelimiter:\u001b[22m \",\"\n",
      "\u001b[31mchr\u001b[39m (2): group, sequence\n",
      "\u001b[32mdbl\u001b[39m (2): ...1, reactivities\n",
      "\n",
      "\u001b[36mℹ\u001b[39m Use `spec()` to retrieve the full column specification for this data.\n",
      "\u001b[36mℹ\u001b[39m Specify the column types or set `show_col_types = FALSE` to quiet this message.\n"
     ]
    }
   ],
   "source": [
    "reactivities <- read_csv(\"data/nano-dms-map/supp-data2-dms_reactivities.csv\") %>%\n",
    "  select(-`...1`) %>%\n",
    "  group_by(group) %>%\n",
    "  mutate(pos=row_number()) %>%\n",
    "  ungroup() %>%\n",
    "  separate(group, into=c(\"group\", \"strain\", \"segment\"), sep=\"_\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [],
   "source": [
    "reactivities_by_segment <- function(reactivities, segment){\n",
    "  reactivities %>%\n",
    "    filter(segment == .env$segment) %>%\n",
    "    select(group, pos, reactivities) %>%\n",
    "    group_by(group) %>%\n",
    "    mutate(rm = roll_mean(reactivities, 20, fill=NA, na.rm=T))\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [],
   "source": [
    "reactivities_ha <- reactivities_by_segment(reactivities, \"HA\")\n",
    "reactivities_na <- reactivities_by_segment(reactivities, \"NA\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [],
   "source": [
    "reactivity_diff <- . %>%\n",
    "  filter(between(pos, 30, max(pos)-30)) %>% # filter out the first and last 30 positions\n",
    "  ungroup() %>%\n",
    "  select(-reactivities) %>%\n",
    "  pivot_wider(names_from=group, values_from=rm) %>%\n",
    "  mutate(diff=NoPLP-PLP)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [],
   "source": [
    "reactivities_ha_diff_w20 <- reactivity_diff(reactivities_ha)\n",
    "reactivities_na_diff_w20 <- reactivity_diff(reactivities_na)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[1mRows: \u001b[22m\u001b[34m20\u001b[39m \u001b[1mColumns: \u001b[22m\u001b[34m9\u001b[39m\n",
      "\u001b[36m──\u001b[39m \u001b[1mColumn specification\u001b[22m \u001b[36m────────────────────────────────────────────────────────\u001b[39m\n",
      "\u001b[1mDelimiter:\u001b[22m \"\\t\"\n",
      "\u001b[31mchr\u001b[39m (2): segment, sample_type\n",
      "\u001b[32mdbl\u001b[39m (7): plp, q25, median, q75, mean, sd, n_fovs\n",
      "\n",
      "\u001b[36mℹ\u001b[39m Use `spec()` to retrieve the full column specification for this data.\n",
      "\u001b[36mℹ\u001b[39m Specify the column types or set `show_col_types = FALSE` to quiet this message.\n",
      "\u001b[1mRows: \u001b[22m\u001b[34m20\u001b[39m \u001b[1mColumns: \u001b[22m\u001b[34m9\u001b[39m\n",
      "\u001b[36m──\u001b[39m \u001b[1mColumn specification\u001b[22m \u001b[36m────────────────────────────────────────────────────────\u001b[39m\n",
      "\u001b[1mDelimiter:\u001b[22m \"\\t\"\n",
      "\u001b[31mchr\u001b[39m (2): segment, sample_type\n",
      "\u001b[32mdbl\u001b[39m (7): plp, q25, median, q75, mean, sd, n_fovs\n",
      "\n",
      "\u001b[36mℹ\u001b[39m Use `spec()` to retrieve the full column specification for this data.\n",
      "\u001b[36mℹ\u001b[39m Specify the column types or set `show_col_types = FALSE` to quiet this message.\n"
     ]
    }
   ],
   "source": [
    "efficiency <- read_tsv(\"figures/fig2cd-plp_individual-spot_counts_NA-summary.tsv\", na=\"\") %>%\n",
    "  bind_rows(read_tsv(\"figures/supp-fig2cd-plp_individual-spot_counts_HA-summary.tsv\")) %>%\n",
    "  filter(sample_type==\"positive\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[1mRows: \u001b[22m\u001b[34m20\u001b[39m \u001b[1mColumns: \u001b[22m\u001b[34m9\u001b[39m\n",
      "\u001b[36m──\u001b[39m \u001b[1mColumn specification\u001b[22m \u001b[36m────────────────────────────────────────────────────────\u001b[39m\n",
      "\u001b[1mDelimiter:\u001b[22m \",\"\n",
      "\u001b[31mchr\u001b[39m (6): segment, vRNA_sequence, PLP_sequence, 5' Arm, 3' Arm, Junction posi...\n",
      "\u001b[32mdbl\u001b[39m (3): plp, start, end\n",
      "\n",
      "\u001b[36mℹ\u001b[39m Use `spec()` to retrieve the full column specification for this data.\n",
      "\u001b[36mℹ\u001b[39m Specify the column types or set `show_col_types = FALSE` to quiet this message.\n",
      "\u001b[1m\u001b[22mJoining with `by = join_by(segment, plp)`\n"
     ]
    }
   ],
   "source": [
    "plps <- read_csv(\"data/nano-dms-map/plp_binding_regions.csv\", na=\"\") %>%\n",
    "  left_join(efficiency) %>%\n",
    "  rename(\n",
    "    seq_id = segment,\n",
    "    efficiency = median\n",
    "  )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [],
   "source": [
    "segments = tibble(seq_id=c(\"NA\",\"HA\"), length=c(max(reactivities_na$pos), max(reactivities_ha$pos)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [],
   "source": [
    "reactivity_feat_na <- reactivities_na_diff_w20 %>% mutate(seq_id=\"NA\", start=pos, end=pos+1)\n",
    "reactivity_feat_ha <- reactivities_ha_diff_w20 %>% mutate(seq_id=\"HA\", start=pos, end=pos+1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <a id='toc1_3_'></a>[Visualization of reactivity (gggenomes)](#toc0_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Only saw `type=NA` in genes and will treat everything as `type=\"CDS\"`.\n",
      "Only saw `type=NA` in genes and will treat everything as `type=\"CDS\"`.\n",
      "wiggle bounds\n",
      "\u001b[36m•\u001b[39m mid:  -0.0534722222222223\n",
      "\u001b[36m•\u001b[39m low:  -0.125991071428571\n",
      "\u001b[36m•\u001b[39m high: 0.356321726190476\n",
      "wiggle bounds\n",
      "\u001b[36m•\u001b[39m mid:  0.559828125\n",
      "\u001b[36m•\u001b[39m low:  0.342234375\n",
      "\u001b[36m•\u001b[39m high: 0.73892375\n",
      "wiggle bounds\n",
      "\u001b[36m•\u001b[39m mid:  0.562614583333333\n",
      "\u001b[36m•\u001b[39m low:  0.222059375\n",
      "\u001b[36m•\u001b[39m high: 0.809041666666667\n"
     ]
    },
    {
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      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 600,
       "width": 1200
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "gggenomes(plps, seqs=segments, feats = reactivity_feat_na) %>%\n",
    "  pick_seqs(\"NA\") +\n",
    "  geom_seq() +\n",
    "  geom_gene(aes(fill=efficiency)) +\n",
    "  geom_wiggle(aes(z=diff), position=position_nudge(y=.2), height=.5) +\n",
    "  geom_wiggle(aes(z=NoPLP), position=position_nudge(y=-.3), height=.5, fill=\"orange\") +\n",
    "  geom_wiggle(aes(z=PLP), position=position_nudge(y=-.6), height=.5, fill=\"#52a752\") +\n",
    "  geom_gene_tag(aes(label=plp), angle=0, hjust=.5, nudge_y=.05, check_overlap = TRUE, size=2) +\n",
    "  annotate(\"text\", x = -80, y = 1.5, label = \"diff\") +\n",
    "  annotate(\"text\", x = -80, y = .7, label = \"noPLP\", color=\"orange\") +\n",
    "  annotate(\"text\", x = -80, y = .4, label = \"PLP\", color=\"#52a752\") +\n",
    "  NULL"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Only saw `type=NA` in genes and will treat everything as `type=\"CDS\"`.\n",
      "Only saw `type=NA` in genes and will treat everything as `type=\"CDS\"`.\n",
      "wiggle bounds\n",
      "\u001b[36m•\u001b[39m mid:  -0.0534722222222223\n",
      "\u001b[36m•\u001b[39m low:  -0.125991071428571\n",
      "\u001b[36m•\u001b[39m high: 0.356321726190476\n",
      "wiggle bounds\n",
      "\u001b[36m•\u001b[39m mid:  0.559828125\n",
      "\u001b[36m•\u001b[39m low:  0.342234375\n",
      "\u001b[36m•\u001b[39m high: 0.73892375\n",
      "wiggle bounds\n",
      "\u001b[36m•\u001b[39m mid:  0.562614583333333\n",
      "\u001b[36m•\u001b[39m low:  0.222059375\n",
      "\u001b[36m•\u001b[39m high: 0.809041666666667\n"
     ]
    }
   ],
   "source": [
    "ggsave(\"figures/fig3b-plp_reactivities-NA.svg\", width = 8, height = 4, dpi = 300)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Only saw `type=NA` in genes and will treat everything as `type=\"CDS\"`.\n",
      "Only saw `type=NA` in genes and will treat everything as `type=\"CDS\"`.\n",
      "wiggle bounds\n",
      "\u001b[36m•\u001b[39m mid:  -0.0156833333333334\n",
      "\u001b[36m•\u001b[39m low:  -0.18755969551282\n",
      "\u001b[36m•\u001b[39m high: 0.260084595959596\n",
      "wiggle bounds\n",
      "\u001b[36m•\u001b[39m mid:  0.424337662337662\n",
      "\u001b[36m•\u001b[39m low:  0.248932142857143\n",
      "\u001b[36m•\u001b[39m high: 0.624010912698413\n",
      "wiggle bounds\n",
      "\u001b[36m•\u001b[39m mid:  0.423823076923077\n",
      "\u001b[36m•\u001b[39m low:  0.1816625\n",
      "\u001b[36m•\u001b[39m high: 0.667758680555556\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 600,
       "width": 1200
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "gggenomes(plps, seqs=segments, feats = reactivity_feat_ha) %>%\n",
    "  pick_seqs(\"HA\") +\n",
    "  geom_seq() +\n",
    "  geom_gene(aes(fill=efficiency)) +\n",
    "  geom_wiggle(aes(z=diff), position=position_nudge(y=.2), height=.5) +\n",
    "  geom_wiggle(aes(z=NoPLP), position=position_nudge(y=-.3), height=.5, fill=\"orange\") +\n",
    "  geom_wiggle(aes(z=PLP), position=position_nudge(y=-.6), height=.5, fill=\"#52a752\") +\n",
    "  geom_gene_tag(aes(label=plp), angle=0, hjust=.5, nudge_y=.05, check_overlap = TRUE, size=2) +\n",
    "  annotate(\"text\", x = -80, y = 1.5, label = \"diff\") +\n",
    "  annotate(\"text\", x = -80, y = .7, label = \"noPLP\", color=\"orange\") +\n",
    "  annotate(\"text\", x = -80, y = .4, label = \"PLP\", color=\"#52a752\") +\n",
    "  NULL"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Only saw `type=NA` in genes and will treat everything as `type=\"CDS\"`.\n",
      "Only saw `type=NA` in genes and will treat everything as `type=\"CDS\"`.\n",
      "wiggle bounds\n",
      "\u001b[36m•\u001b[39m mid:  -0.0156833333333334\n",
      "\u001b[36m•\u001b[39m low:  -0.18755969551282\n",
      "\u001b[36m•\u001b[39m high: 0.260084595959596\n",
      "wiggle bounds\n",
      "\u001b[36m•\u001b[39m mid:  0.424337662337662\n",
      "\u001b[36m•\u001b[39m low:  0.248932142857143\n",
      "\u001b[36m•\u001b[39m high: 0.624010912698413\n",
      "wiggle bounds\n",
      "\u001b[36m•\u001b[39m mid:  0.423823076923077\n",
      "\u001b[36m•\u001b[39m low:  0.1816625\n",
      "\u001b[36m•\u001b[39m high: 0.667758680555556\n"
     ]
    }
   ],
   "source": [
    "ggsave(\"figures/supp-fig4a-plp_reactivities-HA.svg\", width = 8, height = 4, dpi = 300)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <a id='toc1_4_'></a>[Correlation analysis](#toc0_)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <a id='toc1_4_1_'></a>[Correlation of binding site reactivity and PLP efficiency](#toc0_)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "source": [
    "#### NA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Correlation computed with\n",
      "\u001b[36m•\u001b[39m Method: 'pearson'\n",
      "\u001b[36m•\u001b[39m Missing treated using: 'pairwise.complete.obs'\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A tibble: 3 × 2</caption>\n",
       "<thead>\n",
       "\t<tr><th scope=col>term</th><th scope=col>efficiency</th></tr>\n",
       "\t<tr><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>NoPLP</td><td> 0.4342581</td></tr>\n",
       "\t<tr><td>PLP  </td><td>-0.1630581</td></tr>\n",
       "\t<tr><td>diff </td><td> 0.4649112</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A tibble: 3 × 2\n",
       "\\begin{tabular}{ll}\n",
       " term & efficiency\\\\\n",
       " <chr> & <dbl>\\\\\n",
       "\\hline\n",
       "\t NoPLP &  0.4342581\\\\\n",
       "\t PLP   & -0.1630581\\\\\n",
       "\t diff  &  0.4649112\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A tibble: 3 × 2\n",
       "\n",
       "| term &lt;chr&gt; | efficiency &lt;dbl&gt; |\n",
       "|---|---|\n",
       "| NoPLP |  0.4342581 |\n",
       "| PLP   | -0.1630581 |\n",
       "| diff  |  0.4649112 |\n",
       "\n"
      ],
      "text/plain": [
       "  term  efficiency\n",
       "1 NoPLP  0.4342581\n",
       "2 PLP   -0.1630581\n",
       "3 diff   0.4649112"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "correlation_region_reactivity_na <- reactivities_na_diff_w20 %>%\n",
    "  left_join(filter(plps, seq_id==\"NA\"), join_by(between(pos, start, end))) %>%\n",
    "  filter(!is.na(plp)) %>%\n",
    "  group_by(plp,efficiency) %>%\n",
    "  summarize(across(NoPLP:diff, \\(x) mean(x, na.rm=TRUE)), .groups=\"drop\") %>%\n",
    "  corrr::correlate() %>%\n",
    "  corrr::focus(efficiency) %>%\n",
    "  filter(term!=\"plp\")\n",
    "\n",
    "correlation_region_reactivity_na"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[1m\u001b[22m`geom_smooth()` using formula = 'y ~ x'\n"
     ]
    },
    {
     "data": {
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      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 600,
       "width": 1200
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "reactivities_na_diff_w20 %>%\n",
    "  left_join(filter(plps, seq_id==\"NA\"), join_by(between(pos, start, end))) %>%\n",
    "  filter(!is.na(plp)) %>%\n",
    "  group_by(plp,efficiency) %>%\n",
    "  summarize(across(NoPLP:diff, \\(x) mean(x, na.rm=TRUE)), .groups=\"drop\") %>%\n",
    "  pivot_longer(NoPLP:diff,values_to=\"mean reactivity\") %>%\n",
    "  mutate(plp = as_factor(plp)) %>%\n",
    "  mutate(name = fct_relevel(name, \"NoPLP\", \"PLP\")) %>%\n",
    "  ggplot(aes(efficiency, `mean reactivity`)) +\n",
    "    geom_smooth(method=\"lm\", se=FALSE, color=\"darkgray\") +\n",
    "    geom_point(aes(color=plp)) +\n",
    "    facet_grid(.~name) +\n",
    "    geom_text(data=mutate(correlation_region_reactivity_na,name=term,x=20,y=0,efficiency=round(efficiency,2),name=fct_relevel(name,\"NoPLP\",\"PLP\")), aes(x=x,y=y,label=str_glue(\"Pearson's r={efficiency}\")), inherit.aes = FALSE) +\n",
    "    ylab(\"mean region reactivity (ws=20)\") +\n",
    "    xlab(\"PLP RCP/cell\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[1m\u001b[22m`geom_smooth()` using formula = 'y ~ x'\n"
     ]
    }
   ],
   "source": [
    "ggsave(\"figures/fig3c-plp_reactivity_efficiency_correlation-NA.svg\", width = 8, height = 4, dpi = 300)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### HA"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**TODO** PLP 6 and 8 are excluded - justify this decision"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Correlation computed with\n",
      "\u001b[36m•\u001b[39m Method: 'pearson'\n",
      "\u001b[36m•\u001b[39m Missing treated using: 'pairwise.complete.obs'\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A tibble: 3 × 2</caption>\n",
       "<thead>\n",
       "\t<tr><th scope=col>term</th><th scope=col>efficiency</th></tr>\n",
       "\t<tr><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>NoPLP</td><td> 0.4881367</td></tr>\n",
       "\t<tr><td>PLP  </td><td>-0.3934178</td></tr>\n",
       "\t<tr><td>diff </td><td> 0.6628707</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A tibble: 3 × 2\n",
       "\\begin{tabular}{ll}\n",
       " term & efficiency\\\\\n",
       " <chr> & <dbl>\\\\\n",
       "\\hline\n",
       "\t NoPLP &  0.4881367\\\\\n",
       "\t PLP   & -0.3934178\\\\\n",
       "\t diff  &  0.6628707\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A tibble: 3 × 2\n",
       "\n",
       "| term &lt;chr&gt; | efficiency &lt;dbl&gt; |\n",
       "|---|---|\n",
       "| NoPLP |  0.4881367 |\n",
       "| PLP   | -0.3934178 |\n",
       "| diff  |  0.6628707 |\n",
       "\n"
      ],
      "text/plain": [
       "  term  efficiency\n",
       "1 NoPLP  0.4881367\n",
       "2 PLP   -0.3934178\n",
       "3 diff   0.6628707"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "correlation_region_reactivity_ha <- reactivities_ha_diff_w20 %>%\n",
    "  left_join(filter(plps, seq_id==\"HA\"), join_by(between(pos, start, end))) %>%\n",
    "  filter(!is.na(plp), !(plp %in% c(6,8))) %>%\n",
    "  group_by(plp,efficiency) %>%\n",
    "  summarize(across(NoPLP:diff, \\(x) mean(x, na.rm=TRUE)), .groups=\"drop\") %>%\n",
    "  corrr::correlate() %>%\n",
    "  corrr::focus(efficiency) %>%\n",
    "  filter(term!=\"plp\")\n",
    "\n",
    "correlation_region_reactivity_ha"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[1m\u001b[22m`geom_smooth()` using formula = 'y ~ x'\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 600,
       "width": 1200
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "reactivities_ha_diff_w20 %>%\n",
    "  left_join(filter(plps, seq_id==\"HA\"), join_by(between(pos, start, end))) %>%\n",
    "  filter(!is.na(plp)) %>%\n",
    "  group_by(plp,efficiency) %>%\n",
    "  summarize(across(NoPLP:diff, \\(x) mean(x, na.rm=TRUE)), .groups=\"drop\") %>%\n",
    "  pivot_longer(NoPLP:diff,values_to=\"mean reactivity\") %>%\n",
    "  mutate(plp = as_factor(plp)) %>%\n",
    "  mutate(name = fct_relevel(name, \"NoPLP\", \"PLP\")) %>%\n",
    "  ggplot(aes(efficiency, `mean reactivity`)) +\n",
    "    geom_smooth(data=. %>% filter(!plp %in% c(6,8)), method=\"lm\", se=FALSE, color=\"darkgray\") +\n",
    "    geom_point(aes(color=plp)) +\n",
    "    facet_grid(.~name) +\n",
    "    geom_text(data=mutate(correlation_region_reactivity_ha,name=term,x=40,y=0,efficiency=round(efficiency,2),name=fct_relevel(name,\"NoPLP\",\"PLP\")), aes(x=x,y=y,label=str_glue(\"Pearson's r={efficiency}\")), inherit.aes = FALSE) +\n",
    "    ylab(\"mean region reactivity (ws=20)\") +\n",
    "    xlab(\"PLP RCP/cell\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[1m\u001b[22m`geom_smooth()` using formula = 'y ~ x'\n"
     ]
    }
   ],
   "source": [
    "ggsave(\"figures/supp-fig4b-plp_reactivity_efficiency_correlation-HA.svg\", width = 8, height = 4, dpi = 300)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <a id='toc1_4_2_'></a>[Correlation of junction reactivity and PLP efficiency](#toc0_)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### NA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [],
   "source": [
    "junctions_na <- plps %>%\n",
    "  filter(seq_id==\"NA\") %>%\n",
    "  select(plp, pos=`Junction position (nt)`, efficiency) %>% separate_rows(pos, sep=\"-\", convert=TRUE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[1m\u001b[22mJoining with `by = join_by(pos)`\n",
      "Correlation computed with\n",
      "\u001b[36m•\u001b[39m Method: 'pearson'\n",
      "\u001b[36m•\u001b[39m Missing treated using: 'pairwise.complete.obs'\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A tibble: 3 × 2</caption>\n",
       "<thead>\n",
       "\t<tr><th scope=col>term</th><th scope=col>efficiency</th></tr>\n",
       "\t<tr><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>NoPLP</td><td> 0.5790776</td></tr>\n",
       "\t<tr><td>PLP  </td><td>-0.2330223</td></tr>\n",
       "\t<tr><td>diff </td><td> 0.6040137</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A tibble: 3 × 2\n",
       "\\begin{tabular}{ll}\n",
       " term & efficiency\\\\\n",
       " <chr> & <dbl>\\\\\n",
       "\\hline\n",
       "\t NoPLP &  0.5790776\\\\\n",
       "\t PLP   & -0.2330223\\\\\n",
       "\t diff  &  0.6040137\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A tibble: 3 × 2\n",
       "\n",
       "| term &lt;chr&gt; | efficiency &lt;dbl&gt; |\n",
       "|---|---|\n",
       "| NoPLP |  0.5790776 |\n",
       "| PLP   | -0.2330223 |\n",
       "| diff  |  0.6040137 |\n",
       "\n"
      ],
      "text/plain": [
       "  term  efficiency\n",
       "1 NoPLP  0.5790776\n",
       "2 PLP   -0.2330223\n",
       "3 diff   0.6040137"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "correlation_junction_reactivity <- reactivities_na_diff_w20 %>%\n",
    "  left_join(junctions_na) %>%\n",
    "  filter(!is.na(plp)) %>%\n",
    "  group_by(plp,efficiency) %>%\n",
    "  summarize(across(NoPLP:diff, \\(x) mean(x, na.rm=TRUE)), .groups=\"drop\") %>%\n",
    "  corrr::correlate() %>%\n",
    "  corrr::focus(efficiency) %>%\n",
    "  filter(term!=\"plp\")\n",
    "\n",
    "correlation_junction_reactivity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[1m\u001b[22mJoining with `by = join_by(pos)`\n",
      "\u001b[1m\u001b[22m`geom_smooth()` using formula = 'y ~ x'\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 600,
       "width": 1200
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "reactivities_na_diff_w20 %>%\n",
    "  left_join(junctions_na) %>%\n",
    "  filter(!is.na(plp)) %>%\n",
    "  group_by(plp,efficiency) %>%\n",
    "  summarize(across(NoPLP:diff, \\(x) mean(x, na.rm=TRUE)), .groups=\"drop\") %>%\n",
    "  mutate(plp = as_factor(plp)) %>%\n",
    "  pivot_longer(NoPLP:diff,values_to=\"mean reactivity\") %>%\n",
    "  mutate(name = fct_relevel(name, \"NoPLP\", \"PLP\")) %>%\n",
    "  ggplot(aes(efficiency, `mean reactivity`)) +\n",
    "    geom_smooth(method=\"lm\", se=FALSE, color=\"darkgray\") +\n",
    "    geom_point(aes(color=plp)) +\n",
    "    facet_wrap(name~.) +\n",
    "    geom_text(data=mutate(correlation_junction_reactivity,name=term,x=20,y=0,efficiency=round(efficiency,2),name=fct_relevel(name,\"NoPLP\",\"PLP\")), aes(x=x,y=y,label=str_glue(\"Pearson's r={efficiency}\")), inherit.aes = FALSE) +\n",
    "    ylab(\"mean junction reactivity (ws=20)\") +\n",
    "    xlab(\"PLP RCP/cell\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[1m\u001b[22m`geom_smooth()` using formula = 'y ~ x'\n"
     ]
    }
   ],
   "source": [
    "ggsave(\"figures/supp-fig3a-plp_reactivity_efficiency_correlation-junction-NA.svg\", width = 8, height = 4, dpi = 300)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### HA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [],
   "source": [
    "junctions_ha <- plps %>%\n",
    "  filter(seq_id==\"HA\") %>%\n",
    "  select(plp, pos=`Junction position (nt)`, efficiency) %>% separate_rows(pos, sep=\"-\", convert=TRUE)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**TODO** PLP 6 and 8 are excluded - justify this decision (also this plot and the correlations do not match the ones in the manuscript)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[1m\u001b[22mJoining with `by = join_by(pos)`\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Correlation computed with\n",
      "\u001b[36m•\u001b[39m Method: 'pearson'\n",
      "\u001b[36m•\u001b[39m Missing treated using: 'pairwise.complete.obs'\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A tibble: 3 × 2</caption>\n",
       "<thead>\n",
       "\t<tr><th scope=col>term</th><th scope=col>efficiency</th></tr>\n",
       "\t<tr><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>NoPLP</td><td> 0.1312638</td></tr>\n",
       "\t<tr><td>PLP  </td><td>-0.4278051</td></tr>\n",
       "\t<tr><td>diff </td><td> 0.3001889</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A tibble: 3 × 2\n",
       "\\begin{tabular}{ll}\n",
       " term & efficiency\\\\\n",
       " <chr> & <dbl>\\\\\n",
       "\\hline\n",
       "\t NoPLP &  0.1312638\\\\\n",
       "\t PLP   & -0.4278051\\\\\n",
       "\t diff  &  0.3001889\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A tibble: 3 × 2\n",
       "\n",
       "| term &lt;chr&gt; | efficiency &lt;dbl&gt; |\n",
       "|---|---|\n",
       "| NoPLP |  0.1312638 |\n",
       "| PLP   | -0.4278051 |\n",
       "| diff  |  0.3001889 |\n",
       "\n"
      ],
      "text/plain": [
       "  term  efficiency\n",
       "1 NoPLP  0.1312638\n",
       "2 PLP   -0.4278051\n",
       "3 diff   0.3001889"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "correlation_junction_reactivity <- reactivities_ha_diff_w20 %>%\n",
    "  left_join(junctions_ha) %>%\n",
    "  filter(!is.na(plp), !plp %in% c(6,8)) %>%\n",
    "  group_by(plp,efficiency) %>%\n",
    "  summarize(across(NoPLP:diff, \\(x) mean(x, na.rm=TRUE)), .groups=\"drop\") %>%\n",
    "  corrr::correlate() %>%\n",
    "  corrr::focus(efficiency) %>%\n",
    "  filter(term!=\"plp\")\n",
    "\n",
    "correlation_junction_reactivity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[1m\u001b[22mJoining with `by = join_by(pos)`\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[1m\u001b[22m`geom_smooth()` using formula = 'y ~ x'\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 600,
       "width": 1200
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "reactivities_ha_diff_w20 %>%\n",
    "  left_join(junctions_ha) %>%\n",
    "  filter(!is.na(plp)) %>%\n",
    "  group_by(plp,efficiency) %>%\n",
    "  summarize(across(NoPLP:diff, \\(x) mean(x, na.rm=TRUE)), .groups=\"drop\") %>%\n",
    "  mutate(plp = as_factor(plp)) %>%\n",
    "  pivot_longer(NoPLP:diff,values_to=\"mean reactivity\") %>%\n",
    "  mutate(name = fct_relevel(name, \"NoPLP\", \"PLP\")) %>%\n",
    "  ggplot(aes(efficiency, `mean reactivity`)) +\n",
    "    geom_smooth(data=. %>% filter(!plp %in% c(6,8)), method=\"lm\", se=FALSE, color=\"darkgray\") +\n",
    "    geom_point(aes(color=plp)) +\n",
    "    facet_wrap(name~.) +\n",
    "    geom_text(data=mutate(correlation_junction_reactivity,name=term,x=40,y=0,efficiency=round(efficiency,2),name=fct_relevel(name,\"NoPLP\",\"PLP\")), aes(x=x,y=y,label=str_glue(\"Pearson's r={efficiency}\")), inherit.aes = FALSE) +\n",
    "    ylab(\"mean junction reactivity (ws=20)\") +\n",
    "    xlab(\"PLP RCP/cell\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[1m\u001b[22m`geom_smooth()` using formula = 'y ~ x'\n"
     ]
    }
   ],
   "source": [
    "ggsave(\"figures/supp-fig4c-plp_reactivity_efficiency_correlation-junction-HA.svg\", width = 8, height = 4, dpi = 300)"
   ]
  }
 ],
 "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": "4.4.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}