diff --git a/R/figures/Figure5.ipynb b/R/figures/Figure5.ipynb new file mode 100644 index 0000000..7993cae --- /dev/null +++ b/R/figures/Figure5.ipynb @@ -0,0 +1,1491 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "acac2c18-5b33-47c1-87e8-cf876b9acef7", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Downloading GitHub repo philippmuench/HaplotypeDeconstructor@HEAD\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cli (3.2.0 -> 3.3.0 ) [CRAN]\n", + "tibble (3.1.6 -> 3.1.7 ) [CRAN]\n", + "scales (1.1.1 -> 1.2.0 ) [CRAN]\n", + "registry (NA -> 0.5-1 ) [CRAN]\n", + "Rtsne (0.15 -> 0.16 ) [CRAN]\n", + "V8 (NA -> 4.1.0 ) [CRAN]\n", + "dplyr (1.0.8 -> 1.0.9 ) [CRAN]\n", + "BiocManager (1.30.16 -> 1.30.17) [CRAN]\n", + "ggplot2 (3.3.5 -> 3.3.6 ) [CRAN]\n", + "gridBase (NA -> 0.4-7 ) [CRAN]\n", + "rngtools (NA -> 1.5.2 ) [CRAN]\n", + "pkgmaker (NA -> 0.32.2 ) [CRAN]\n", + "randomcoloR (NA -> 1.1.0.1) [CRAN]\n", + "NMF (NA -> 0.24.0 ) [CRAN]\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Skipping 2 packages not available: Biobase, ComplexHeatmap\n", + "\n", + "Installing 14 packages: cli, tibble, scales, registry, Rtsne, V8, dplyr, BiocManager, ggplot2, gridBase, rngtools, pkgmaker, randomcoloR, NMF\n", + "\n", + "Updating HTML index of packages in '.Library'\n", + "\n", + "Making 'packages.html' ...\n", + " done\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[32m✔\u001b[39m \u001b[90mchecking for file ‘/tmp/Rtmp81BIlq/remotes256063230c3d72/philippmuench-HaplotypeDeconstructor-f8b5b79/DESCRIPTION’\u001b[39m\u001b[36m\u001b[39m\n", + "\u001b[90m─\u001b[39m\u001b[90m \u001b[39m\u001b[90mpreparing ‘HaplotypeDeconstructor’:\u001b[39m\u001b[36m\u001b[39m\n", + "\u001b[32m✔\u001b[39m \u001b[90mchecking DESCRIPTION meta-information\u001b[39m\u001b[36m\u001b[39m\n", + "\u001b[90m─\u001b[39m\u001b[90m \u001b[39m\u001b[90mchecking for LF line-endings in source and make files and shell scripts\u001b[39m\u001b[36m\u001b[39m\n", + "\u001b[90m─\u001b[39m\u001b[90m \u001b[39m\u001b[90mchecking for empty or unneeded directories\u001b[39m\u001b[36m\u001b[39m\n", + " NB: this package now depends on R (>= 3.5.0)\n", + " WARNING: Added dependency on R >= 3.5.0 because serialized objects in\n", + " serialize/load version 3 cannot be read in older versions of R.\n", + " File(s) containing such objects:\n", + " ‘HaplotypeDeconstructor/data-raw/omm_ab.rds’\n", + " ‘HaplotypeDeconstructor/data-raw/omm_claudia_new.rds’\n", + " ‘HaplotypeDeconstructor/data-raw/reseq.rds’\n", + "\u001b[90m─\u001b[39m\u001b[90m \u001b[39m\u001b[90mbuilding ‘HaplotypeDeconstructor_0.1.0.tar.gz’\u001b[39m\u001b[36m\u001b[39m\n", + " \n", + "\r" + ] + } + ], + "source": [ + "devtools::install_github(\"philippmuench/HaplotypeDeconstructor\")" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "e85fc253-dd57-434a-9bf3-4596facfb4c2", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "Attaching package: ‘HaplotypeDeconstructor’\n", + "\n", + "\n", + "The following object is masked _by_ ‘.GlobalEnv’:\n", + "\n", + " omm\n", + "\n", + "\n", + "========================================\n", + "circlize version 0.4.14\n", + "CRAN page: https://cran.r-project.org/package=circlize\n", + "Github page: https://github.com/jokergoo/circlize\n", + "Documentation: https://jokergoo.github.io/circlize_book/book/\n", + "\n", + "If you use it in published research, please cite:\n", + "Gu, Z. circlize implements and enhances circular visualization\n", + " in R. Bioinformatics 2014.\n", + "\n", + "This message can be suppressed by:\n", + " suppressPackageStartupMessages(library(circlize))\n", + "========================================\n", + "\n", + "\n", + "Loading required package: grid\n", + "\n", + "========================================\n", + "ComplexHeatmap version 2.10.0\n", + "Bioconductor page: http://bioconductor.org/packages/ComplexHeatmap/\n", + "Github page: https://github.com/jokergoo/ComplexHeatmap\n", + "Documentation: http://jokergoo.github.io/ComplexHeatmap-reference\n", + "\n", + "If you use it in published research, please cite:\n", + "Gu, Z. Complex heatmaps reveal patterns and correlations in multidimensional \n", + " genomic data. Bioinformatics 2016.\n", + "\n", + "The new InteractiveComplexHeatmap package can directly export static \n", + "complex heatmaps into an interactive Shiny app with zero effort. Have a try!\n", + "\n", + "This message can be suppressed by:\n", + " suppressPackageStartupMessages(library(ComplexHeatmap))\n", + "========================================\n", + "\n", + "\n", + "\n", + "Attaching package: ‘dplyr’\n", + "\n", + "\n", + "The following objects are masked from ‘package:data.table’:\n", + "\n", + " between, first, last\n", + "\n", + "\n", + "The following object is masked from ‘package:Biobase’:\n", + "\n", + " combine\n", + "\n", + "\n", + "The following objects are masked from ‘package:BiocGenerics’:\n", + "\n", + " combine, intersect, setdiff, union\n", + "\n", + "\n", + "The following objects are masked from ‘package:stats’:\n", + "\n", + " filter, lag\n", + "\n", + "\n", + "The following objects are masked from ‘package:base’:\n", + "\n", + " intersect, setdiff, setequal, union\n", + "\n", + "\n", + "------------------------------------------------------------------------------\n", + "\n", + "You have loaded plyr after dplyr - this is likely to cause problems.\n", + "If you need functions from both plyr and dplyr, please load plyr first, then dplyr:\n", + "library(plyr); library(dplyr)\n", + "\n", + "------------------------------------------------------------------------------\n", + "\n", + "\n", + "Attaching package: ‘plyr’\n", + "\n", + "\n", + "The following objects are masked from ‘package:dplyr’:\n", + "\n", + " arrange, count, desc, failwith, id, mutate, rename, summarise,\n", + " summarize\n", + "\n", + "\n", + "\n", + " ***** *** vcfR *** *****\n", + " This is vcfR 1.12.0 \n", + " browseVignettes('vcfR') # Documentation\n", + " citation('vcfR') # Citation\n", + " ***** ***** ***** *****\n", + "\n", + "\n", + "Loading required package: pkgmaker\n", + "\n", + "Loading required package: registry\n", + "\n", + "Loading required package: rngtools\n", + "\n", + "Loading required package: cluster\n", + "\n", + "NMF - BioConductor layer [OK] | Shared memory capabilities [NO: synchronicity] | Cores 47/48\n", + "\n", + " To enable shared memory capabilities, try: install.extras('\n", + "NMF\n", + "')\n", + "\n", + "\n", + "Attaching package: ‘matrixStats’\n", + "\n", + "\n", + "The following object is masked from ‘package:plyr’:\n", + "\n", + " count\n", + "\n", + "\n", + "The following object is masked from ‘package:dplyr’:\n", + "\n", + " count\n", + "\n", + "\n", + "The following objects are masked from ‘package:Biobase’:\n", + "\n", + " anyMissing, rowMedians\n", + "\n", + "\n" + ] + } + ], + "source": [ + "library(HaplotypeDeconstructor)\n", + "library(circlize)\n", + "library(tidyr)\n", + "library(data.table)\n", + "library(ComplexHeatmap)\n", + "library(circlize)\n", + "library(dplyr)\n", + "library(plyr)\n", + "library(HaplotypeDeconstructor)\n", + "library(vcfR)\n", + "library(NMF)\n", + "library(ggplot2)\n", + "library(fastICA)\n", + "library(matrixStats)\n", + "library(OligoMMR2)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "9404dd1a-b79b-4e02-a3d9-449124ee76b1", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "
  1. 'Akkermansia_muciniphila_YL44'
  2. 'Bacteroides_caecimuris_I48'
  3. 'Blautia_coccoides_YL58'
  4. 'Clostridium_innocuum_I46'
  5. 'Enterocloster_clostridioformis_YL32'
  6. 'Flavonifractor_plautii_YL31'
  7. 'Limosilactobacillus_reuteri_I49'
  8. 'Muribaculum_intestinale_YL27'
  9. 'Turicimonas_muris_YL45'
\n" + ], + "text/latex": [ + "\\begin{enumerate*}\n", + "\\item 'Akkermansia\\_muciniphila\\_YL44'\n", + "\\item 'Bacteroides\\_caecimuris\\_I48'\n", + "\\item 'Blautia\\_coccoides\\_YL58'\n", + "\\item 'Clostridium\\_innocuum\\_I46'\n", + "\\item 'Enterocloster\\_clostridioformis\\_YL32'\n", + "\\item 'Flavonifractor\\_plautii\\_YL31'\n", + "\\item 'Limosilactobacillus\\_reuteri\\_I49'\n", + "\\item 'Muribaculum\\_intestinale\\_YL27'\n", + "\\item 'Turicimonas\\_muris\\_YL45'\n", + "\\end{enumerate*}\n" + ], + "text/markdown": [ + "1. 'Akkermansia_muciniphila_YL44'\n", + "2. 'Bacteroides_caecimuris_I48'\n", + "3. 'Blautia_coccoides_YL58'\n", + "4. 'Clostridium_innocuum_I46'\n", + "5. 'Enterocloster_clostridioformis_YL32'\n", + "6. 'Flavonifractor_plautii_YL31'\n", + "7. 'Limosilactobacillus_reuteri_I49'\n", + "8. 'Muribaculum_intestinale_YL27'\n", + "9. 'Turicimonas_muris_YL45'\n", + "\n", + "\n" + ], + "text/plain": [ + "[1] \"Akkermansia_muciniphila_YL44\" \"Bacteroides_caecimuris_I48\" \n", + "[3] \"Blautia_coccoides_YL58\" \"Clostridium_innocuum_I46\" \n", + "[5] \"Enterocloster_clostridioformis_YL32\" \"Flavonifractor_plautii_YL31\" \n", + "[7] \"Limosilactobacillus_reuteri_I49\" \"Muribaculum_intestinale_YL27\" \n", + "[9] \"Turicimonas_muris_YL45\" " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "wgs_data <- readRDS(\"../../datasets/omm_wgs_imputed_wide_filtered.rds\")\n", + "unique(wgs_data$chr)" + ] + }, + { + "cell_type": "markdown", + "id": "a5d8752f-9c18-4d3a-acc8-79473f3ea263", + "metadata": {}, + "source": [ + "## Akkermansia_muciniphila_YL44" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "id": "0b32f941-1570-472a-b955-9a175f3ce288", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "
  1. 26
  2. 135
\n" + ], + "text/latex": [ + "\\begin{enumerate*}\n", + "\\item 26\n", + "\\item 135\n", + "\\end{enumerate*}\n" + ], + "text/markdown": [ + "1. 26\n", + "2. 135\n", + "\n", + "\n" + ], + "text/plain": [ + "[1] 26 135" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "26" + ], + "text/latex": [ + "26" + ], + "text/markdown": [ + "26" + ], + "text/plain": [ + "[1] 26" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "bug <- \"Akkermansia_muciniphila_YL44\"\n", + "dat <- wgs_data[which(wgs_data$chr == bug), ]\n", + "dim(dat)\n", + "nrow(dat)\n", + "omm <- dat[, grep(\"16\", colnames(dat), invert = F)]\n", + "annot <- dat[, grep(\"16\", colnames(dat), invert = T)]\n", + "omm[is.na(omm)] <- 0\n", + "rownames(omm) <- paste0(annot$chr, \"-\",annot$POS, \"-\", annot$REF,\"-\", annot$ALT)\n", + "omm <- data.matrix(omm)\n", + "omm <- omm[,colSds(omm) > 0]\n", + "gof <- assessNumberHaplotyes(omm, 2:10)\n", + "gof_agg <- aggregate(data = gof, ExplainedVariance ~NumberHaplotyes, FUN = mean)\n", + "num <- min(gof_agg[which(gof_agg$ExplainedVariance > 0.8),]$NumberHaplotyes)" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "id": "6e39ed50-7767-4a9d-b6c9-253257f4ef2e", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Warning message:\n", + "“`fun.y` is deprecated. Use `fun` instead.”\n", + "Scale for 'y' is already present. Adding another scale for 'y', which will\n", + "replace the existing scale.\n", + "\n" + ] + }, + { + "data": { + "image/png": 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5tN/vAHSUy0DhwYe//95quuktatZckSvWMBAAD8AlvszqWoSPr2lT17RMRTM5if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\nVIJiBwAAoBIUOwAAAJX4P5+OCDpRXfgGAAAAAElFTkSuQmCC", + "text/plain": [ + "plot without title" + ] + }, + "metadata": { + "image/png": { + "height": 420, + "width": 420 + } + }, + "output_type": "display_data" + } + ], + "source": [ + "p <- plotNumberHaplotyes(gof)\n", + "p <- p + ylim(c(0, 1)) + geom_vline(xintercept = num, linetype = 2)\n", + "p" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "105a454e-4ca9-46a8-9ce3-75da94a70198", + "metadata": {}, + "outputs": [], + "source": [ + "decomposed <- findHaplotypes(data.matrix(omm), num)\n", + "contrib <- HaplotypeDeconstructor::HaplotypeEvar(decomposed)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2ca0d01e-7a56-447d-b0fb-a9fb09d07925", + "metadata": {}, + "outputs": [], + "source": [ + "contrib$combined_variance <- NULL\n", + "contrib$day <- as.integer(substr(contrib$sample, 6,8))\n", + "contrib$mouse <- as.integer(substr(contrib$sample, 1,4)) \n", + "contrib$group <- translateMouseIdToTreatmentGroup(contrib$mouse)\n", + "s2 <- reshape2::melt(contrib, id.vars = c(\"sample\", \"day\", \"mouse\", \"group\"))\n", + "set.seed(42)\n", + "palette <- randomcoloR::distinctColorPalette(num+1)\n", + "palette[1] <- \"grey80\"\n", + "group_order = c(\"Control\",\"Ciprofloxacin\",\n", + " \"Tetracyclin\", \"Vancomycin\")\n", + "mouse_order = c(\"1683\",\"1681\",\"1684\",\n", + " \"1688\", \"1686\", \"1690\",\n", + " \"1692\", \"1693\", \"1694\",\n", + " \"1699\", \"1698\", \"1697\")\n", + " \n", + "s2 <- arrange(transform(s2, group = factor(group,levels = group_order)), group)\n", + "s2 <- arrange(transform(s2, mouse = factor(mouse,levels = mouse_order)), mouse)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c0fcc6b7-9fdb-4d98-987c-77b436032e1a", + "metadata": {}, + "outputs": [], + "source": [ + "p <- ggplot(s2, aes(x = day, y = value, fill = variable))\n", + "p <- p + geom_bar(size = 0, color = \"black\", stat = \"identity\",\n", + " position = \"stack\")\n", + "p <- p + xlab(\"time (day)\") + ylab(\"explained variance by haplotype [%]\")\n", + "p <- p + theme_bw() + theme(panel.border = element_blank(),\n", + " panel.grid.major = element_blank(),\n", + " panel.grid.minor = element_blank(),\n", + " axis.line = element_line(color = \"black\"))\n", + "p <- p + theme_pmuench(base_size = 9) + facet_wrap(~group + mouse, nrow = 4)\n", + "p <- p + scale_fill_manual(values = palette) \n", + "p <- p + theme(aspect.ratio = .5, strip.background = element_blank(), strip.placement = \"outside\")\n", + "p <- p + theme(panel.background = element_rect(fill = \"white\", colour = 'black'))\n", + "p <- p + geom_vline(xintercept = c(4, 18, 53, 67), \n", + " linetype = 1, color = \"black\", alpha = 1)\n", + "p" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5adb0014-9d23-4c85-a301-922a7242cd77", + "metadata": {}, + "outputs": [], + "source": [ + "s2 <- s2[which(s2$mouse %in% c(\"1683\", \"1688\", \"1692\", \"1699\")),]\n", + "p <- ggplot(s2, aes(x = day, y = value, fill = variable))\n", + "p <- p + geom_bar(size = 0, color = \"black\", stat = \"identity\",\n", + " position = \"stack\")\n", + "p <- p + xlab(\"time (day)\") + ylab(\"explained variance by haplotype [%]\")\n", + "p <- p + theme_bw() + theme(panel.border = element_blank(),\n", + " panel.grid.major = element_blank(),\n", + " panel.grid.minor = element_blank(),\n", + " axis.line = element_line(color = \"black\"))\n", + "p <- p + theme_pmuench(base_size = 9) + facet_wrap(~group + mouse, nrow = 4)\n", + "p <- p + scale_fill_manual(values = palette) \n", + "p <- p + theme(aspect.ratio = .5, strip.background = element_blank(), strip.placement = \"outside\")\n", + "p <- p + theme(panel.background = element_rect(fill = \"white\", colour = 'black'))\n", + "p <- p + geom_vline(xintercept = c(4, 18, 53, 67), \n", + " linetype = 1, color = \"black\", alpha = .2)\n", + "p" + ] + }, + { + "cell_type": "markdown", + "id": "a186ea83-ad1b-48a8-93e4-c492f83389f9", + "metadata": {}, + "source": [ + "pdf(\"nmf_amuc_1.pdf\", width = 4, height = 8)\n", + "print(p)\n", + "dev.off()" + ] + }, + { + "cell_type": "markdown", + "id": "2f1ebe93-787f-4dbe-b2b7-23c40f0d6d90", + "metadata": {}, + "source": [ + "## Turicimonas_muris_YL45" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "id": "633e589f-12df-41e7-be31-d499bb8def7d", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "
  1. 45
  2. 135
\n" + ], + "text/latex": [ + "\\begin{enumerate*}\n", + "\\item 45\n", + "\\item 135\n", + "\\end{enumerate*}\n" + ], + "text/markdown": [ + "1. 45\n", + "2. 135\n", + "\n", + "\n" + ], + "text/plain": [ + "[1] 45 135" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "45" + ], + "text/latex": [ + "45" + ], + "text/markdown": [ + "45" + ], + "text/plain": [ + "[1] 45" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "bug <- \"Turicimonas_muris_YL45\"\n", + "dat <- wgs_data[which(wgs_data$chr == bug), ]\n", + "dim(dat)\n", + "nrow(dat)\n", + "omm <- dat[, grep(\"16\", colnames(dat), invert = F)]\n", + "annot <- dat[, grep(\"16\", colnames(dat), invert = T)]\n", + "omm[is.na(omm)] <- 0\n", + "rownames(omm) <- paste0(annot$chr, \"-\",annot$POS, \"-\", annot$REF,\"-\", annot$ALT)\n", + "omm <- data.matrix(omm)\n", + "omm <- omm[,colSds(omm) > 0]\n", + "gof <- assessNumberHaplotyes(omm, 2:10)\n", + "gof_agg <- aggregate(data = gof, ExplainedVariance ~NumberHaplotyes, FUN = mean)\n", + "num <- min(gof_agg[which(gof_agg$ExplainedVariance > 0.8),]$NumberHaplotyes)" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "id": "0a932029-4034-4f4f-8a7c-959c1ccfe3bf", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Warning message:\n", + "“`fun.y` is deprecated. Use `fun` instead.”\n", + "Scale for 'y' is already present. Adding another scale for 'y', which will\n", + "replace the existing scale.\n", + "\n" + ] + }, + { + "data": { + "image/png": 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ODiM3bsWJfLZXQKAAB8UewAv+Xk5CiK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\nAKAIih0AAIAiKHYAAACKoNgBAAAo4v8A6NYNI9ehkGAAAAAASUVORK5CYII=", + "text/plain": [ + "plot without title" + ] + }, + "metadata": { + "image/png": { + "height": 420, + "width": 420 + } + }, + "output_type": "display_data" + } + ], + "source": [ + "p <- plotNumberHaplotyes(gof)\n", + "p <- p + ylim(c(0, 1)) + geom_vline(xintercept = num, linetype = 2)\n", + "p" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "id": "d8da6138-614b-4c06-b42b-dc0eb2d121e0", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Processing Sample1\n", + "\n", + "Processing Sample2\n", + "\n", + "Processing Sample3\n", + "\n", + "Processing Sample4\n", + "\n", + "Processing Sample5\n", + "\n", + "Processing Sample6\n", + "\n", + "Processing Sample7\n", + "\n", + "Processing Sample8\n", + "\n", + "Processing Sample9\n", + "\n", + "Processing Sample10\n", + "\n", + "Processing Sample11\n", + "\n", + "Processing Sample12\n", + "\n", + "Processing Sample13\n", + "\n", + "Processing Sample14\n", + "\n", + "Processing 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Sample72\n", + "\n", + "Processing Sample73\n", + "\n", + "Processing Sample74\n", + "\n", + "Processing Sample75\n", + "\n", + "Processing Sample76\n", + "\n", + "Processing Sample77\n", + "\n", + "Processing Sample78\n", + "\n", + "Processing Sample79\n", + "\n", + "Processing Sample80\n", + "\n", + "Processing Sample81\n", + "\n", + "Processing Sample82\n", + "\n", + "Processing Sample83\n", + "\n", + "Processing Sample84\n", + "\n", + "Processing Sample85\n", + "\n", + "Processing Sample86\n", + "\n", + "Processing Sample87\n", + "\n", + "Processing Sample88\n", + "\n", + "Processing Sample89\n", + "\n", + "Processing Sample90\n", + "\n", + "Processing Sample91\n", + "\n", + "Processing Sample92\n", + "\n", + "Processing Sample93\n", + "\n", + "Processing Sample94\n", + "\n", + "Processing Sample95\n", + "\n", + "Processing Sample96\n", + "\n" + ] + } + ], + "source": [ + "decomposed <- findHaplotypes(data.matrix(omm), num)\n", + "contrib <- HaplotypeDeconstructor::HaplotypeEvar(decomposed)" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "id": "22888125-4335-44c5-be90-b24e688f193e", + "metadata": {}, + "outputs": [], + "source": [ + "contrib$combined_variance <- NULL\n", + "contrib$day <- as.integer(substr(contrib$sample, 6,8))\n", + "contrib$mouse <- as.integer(substr(contrib$sample, 1,4)) \n", + "contrib$group <- translateMouseIdToTreatmentGroup(contrib$mouse)\n", + "s2 <- reshape2::melt(contrib, id.vars = c(\"sample\", \"day\", \"mouse\", \"group\"))\n", + "set.seed(42)\n", + "palette <- randomcoloR::distinctColorPalette(num+1)\n", + "palette[1] <- \"grey80\"\n", + "group_order = c(\"Control\",\"Ciprofloxacin\",\n", + " \"Tetracyclin\", \"Vancomycin\")\n", + "mouse_order = c(\"1683\",\"1681\",\"1684\",\n", + " \"1688\", \"1686\", \"1690\",\n", + " \"1692\", \"1693\", \"1694\",\n", + " \"1699\", \"1698\", \"1697\")\n", + " \n", + "s2 <- arrange(transform(s2, group = factor(group,levels = group_order)), group)\n", + "s2 <- arrange(transform(s2, mouse = factor(mouse,levels = mouse_order)), mouse)" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "id": "b00c1011-7678-489a-be0d-342c83e144a9", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Warning message:\n", + "“`panel.margin` is deprecated. Please use `panel.spacing` property instead”\n", + "Warning message:\n", + "“`legend.margin` must be specified using `margin()`. For the old behavior use legend.spacing”\n" + ] + }, + { + "data": { + "image/png": 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CHCwsJ0/ZxCPcw96BHTD9Algp3urFy5UvX/xac89eo2c+ZMpVJZVFRkYWHRr18/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\nghB2AABBCDsAgCD+ALn+fQYu1R8cAAAAAElFTkSuQmCC", + "text/plain": [ + "plot without title" + ] + }, + "metadata": { + "image/png": { + "height": 420, + "width": 420 + } + }, + "output_type": "display_data" + } + ], + "source": [ + "p <- ggplot(s2, aes(x = day, y = value, fill = variable))\n", + "p <- p + geom_bar(size = 0, color = \"black\", stat = \"identity\",\n", + " position = \"stack\")\n", + "p <- p + xlab(\"time (day)\") + ylab(\"explained variance by haplotype [%]\")\n", + "p <- p + theme_bw() + theme(panel.border = element_blank(),\n", + " panel.grid.major = element_blank(),\n", + " panel.grid.minor = element_blank(),\n", + " axis.line = element_line(color = \"black\"))\n", + "p <- p + theme_pmuench(base_size = 9) + facet_wrap(~group + mouse, nrow = 4)\n", + "p <- p + scale_fill_manual(values = palette) \n", + "p <- p + theme(aspect.ratio = .5, strip.background = element_blank(), strip.placement = \"outside\")\n", + "p <- p + theme(panel.background = element_rect(fill = \"white\", colour = 'black'))\n", + "p <- p + geom_vline(xintercept = c(4, 18, 53, 67), \n", + " linetype = 1, color = \"black\", alpha = 1)\n", + "p" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "id": "f662d19a-5342-4039-9489-fa119770260e", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Warning message:\n", + "“`panel.margin` is deprecated. Please use `panel.spacing` property instead”\n", + "Warning message:\n", + "“`legend.margin` must be specified using `margin()`. For the old behavior use legend.spacing”\n" + ] + }, + { + "data": { + "image/png": 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g729va2s7Pz9fU9f/78/v37S0pK5s+f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+ "text/plain": [ + "plot without title" + ] + }, + "metadata": { + "image/png": { + "height": 420, + "width": 420 + } + }, + "output_type": "display_data" + } + ], + "source": [ + "s2 <- s2[which(s2$mouse %in% c(\"1683\", \"1688\", \"1692\", \"1699\")),]\n", + "p <- ggplot(s2, aes(x = day, y = value, fill = variable))\n", + "p <- p + geom_bar(size = 0, color = \"black\", stat = \"identity\",\n", + " position = \"stack\")\n", + "p <- p + xlab(\"time (day)\") + ylab(\"explained variance by haplotype [%]\")\n", + "p <- p + theme_bw() + theme(panel.border = element_blank(),\n", + " panel.grid.major = element_blank(),\n", + " panel.grid.minor = element_blank(),\n", + " axis.line = element_line(color = \"black\"))\n", + "p <- p + theme_pmuench(base_size = 9) + facet_wrap(~group + mouse, nrow = 4)\n", + "p <- p + scale_fill_manual(values = palette) \n", + "p <- p + theme(aspect.ratio = .5, strip.background = element_blank(), strip.placement = \"outside\")\n", + "p <- p + theme(panel.background = element_rect(fill = \"white\", colour = 'black'))\n", + "p <- p + geom_vline(xintercept = c(4, 18, 53, 67), \n", + " linetype = 1, color = \"black\", alpha = .2)\n", + "p" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "id": "46e74f0e-f0c0-452e-b400-d09ddf57943c", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "png: 2" + ], + "text/latex": [ + "\\textbf{png:} 2" + ], + "text/markdown": [ + "**png:** 2" + ], + "text/plain": [ + "png \n", + " 2 " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "pdf(\"Figure_5_c.pdf\", width = 4, height = 8)\n", + "print(p)\n", + "dev.off()" + ] + }, + { + "cell_type": "markdown", + "id": "f89d8def-40e9-41cc-83b8-0c2151538e68", + "metadata": {}, + "source": [ + "## Muribaculum intestinale YL27" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "id": "97fa09cc-c1e7-4c2f-b953-ad23b11ea28c", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "
  1. 39
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\n" + ], + "text/latex": [ + "\\begin{enumerate*}\n", + "\\item 39\n", + "\\item 135\n", + "\\end{enumerate*}\n" + ], + "text/markdown": [ + "1. 39\n", + "2. 135\n", + "\n", + "\n" + ], + "text/plain": [ + "[1] 39 135" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "39" + ], + "text/latex": [ + "39" + ], + "text/markdown": [ + "39" + ], + "text/plain": [ + "[1] 39" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "bug <- \"Muribaculum_intestinale_YL27\"\n", + "dat <- wgs_data[which(wgs_data$chr == bug), ]\n", + "dim(dat)\n", + "nrow(dat)\n", + "omm <- dat[, grep(\"16\", colnames(dat), invert = F)]\n", + "annot <- dat[, grep(\"16\", colnames(dat), invert = T)]\n", + "omm[is.na(omm)] <- 0\n", + "rownames(omm) <- paste0(annot$chr, \"-\",annot$POS, \"-\", annot$REF,\"-\", annot$ALT)\n", + "omm <- data.matrix(omm)\n", + "omm <- omm[,colSds(omm) > 0]\n", + "gof <- assessNumberHaplotyes(omm, 2:10)\n", + "gof_agg <- aggregate(data = gof, ExplainedVariance ~NumberHaplotyes, FUN = mean)\n", + "num <- min(gof_agg[which(gof_agg$ExplainedVariance > 0.8),]$NumberHaplotyes)" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "id": "53271c67-b1dc-43cd-b8a3-9a8782c5a4ee", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Warning message:\n", + "“`fun.y` is deprecated. Use `fun` instead.”\n", + "Scale for 'y' is already present. Adding another scale for 'y', which will\n", + "replace the existing scale.\n", + "\n" + ] + }, + { + "data": { + "image/png": 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AAAwB8pKaJVq1pftdnEww/XY5qfUOwA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\nAABJRU5ErkJggg==", + "text/plain": [ + "plot without title" + ] + }, + "metadata": { + "image/png": { + "height": 420, + "width": 420 + } + }, + "output_type": "display_data" + } + ], + "source": [ + "p <- plotNumberHaplotyes(gof)\n", + "p <- p + ylim(c(0, 1)) + geom_vline(xintercept = num, linetype = 2)\n", + "p" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "id": "778a3e94-606c-4f7d-a614-5fe274dd9efa", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Processing Sample1\n", + "\n", + "Processing Sample2\n", + "\n", + "Processing Sample3\n", + "\n", + "Processing Sample4\n", + "\n", + "Processing Sample5\n", + "\n", + "Processing Sample6\n", + "\n", + "Processing Sample7\n", + "\n", + "Processing Sample8\n", + "\n", + "Processing Sample9\n", + "\n", + "Processing Sample10\n", + "\n", + "Processing Sample11\n", + "\n", + "Processing Sample12\n", + "\n", + "Processing Sample13\n", + "\n", + "Processing Sample14\n", + "\n", + "Processing 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as.integer(substr(contrib$sample, 6,8))\n", + "contrib$mouse <- as.integer(substr(contrib$sample, 1,4)) \n", + "contrib$group <- translateMouseIdToTreatmentGroup(contrib$mouse)\n", + "s2 <- reshape2::melt(contrib, id.vars = c(\"sample\", \"day\", \"mouse\", \"group\"))\n", + "set.seed(42)\n", + "palette <- randomcoloR::distinctColorPalette(num+1)\n", + "palette[1] <- \"grey80\"\n", + "group_order = c(\"Control\",\"Ciprofloxacin\",\n", + " \"Tetracyclin\", \"Vancomycin\")\n", + "mouse_order = c(\"1683\",\"1681\",\"1684\",\n", + " \"1688\", \"1686\", \"1690\",\n", + " \"1692\", \"1693\", \"1694\",\n", + " \"1699\", \"1698\", \"1697\")\n", + " \n", + "s2 <- arrange(transform(s2, group = factor(group,levels = group_order)), group)\n", + "s2 <- arrange(transform(s2, mouse = factor(mouse,levels = mouse_order)), mouse)" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "id": "2444a2c6-072b-48ee-9c1c-97d4e72b1464", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Warning message:\n", + "“`panel.margin` is deprecated. Please use `panel.spacing` property instead”\n", + "Warning message:\n", + "“`legend.margin` must be specified using `margin()`. For the old behavior use legend.spacing”\n" + ] + }, + { + "data": { + "image/png": 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2diYmJiYlJWVmZnZ2diYpKZmWlhYbF3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\nEbvGxkY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+ "text/plain": [ + "plot without title" + ] + }, + "metadata": { + "image/png": { + "height": 420, + "width": 420 + } + }, + "output_type": "display_data" + } + ], + "source": [ + "p <- ggplot(s2, aes(x = day, y = value, fill = variable))\n", + "p <- p + geom_bar(size = 0, color = \"black\", stat = \"identity\",\n", + " position = \"stack\")\n", + "p <- p + xlab(\"time (day)\") + ylab(\"explained variance by haplotype [%]\")\n", + "p <- p + theme_bw() + theme(panel.border = element_blank(),\n", + " panel.grid.major = element_blank(),\n", + " panel.grid.minor = element_blank(),\n", + " axis.line = element_line(color = \"black\"))\n", + "p <- p + theme_pmuench(base_size = 9) + facet_wrap(~group + mouse, nrow = 4)\n", + "p <- p + scale_fill_manual(values = palette) \n", + "p <- p + theme(aspect.ratio = .5, strip.background = element_blank(), strip.placement = \"outside\")\n", + "p <- p + theme(panel.background = element_rect(fill = \"white\", colour = 'black'))\n", + "p <- p + geom_vline(xintercept = c(4, 18, 53, 67), \n", + " linetype = 1, color = \"black\", alpha = 1)\n", + "p" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "id": "cc9cc6a6-f09f-4aeb-87f9-4f1dded52d71", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Warning message:\n", + "“`panel.margin` is deprecated. Please use `panel.spacing` property instead”\n", + "Warning message:\n", + "“`legend.margin` must be specified using `margin()`. For the old behavior use legend.spacing”\n" + ] + }, + { + "data": { + "image/png": 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yMjo6CgoIsXL2ZkZJiYmBQVFWnHFBYW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+ "text/plain": [ + "plot without title" + ] + }, + "metadata": { + "image/png": { + "height": 420, + "width": 420 + } + }, + "output_type": "display_data" + } + ], + "source": [ + "s2 <- s2[which(s2$mouse %in% c(\"1683\", \"1688\", \"1692\", \"1699\")),]\n", + "p <- ggplot(s2, aes(x = day, y = value, fill = variable))\n", + "p <- p + geom_bar(size = 0, color = \"black\", stat = \"identity\",\n", + " position = \"stack\")\n", + "p <- p + xlab(\"time (day)\") + ylab(\"explained variance by haplotype [%]\")\n", + "p <- p + theme_bw() + theme(panel.border = element_blank(),\n", + " panel.grid.major = element_blank(),\n", + " panel.grid.minor = element_blank(),\n", + " axis.line = element_line(color = \"black\"))\n", + "p <- p + theme_pmuench(base_size = 9) + facet_wrap(~group + mouse, nrow = 4)\n", + "p <- p + scale_fill_manual(values = palette) \n", + "p <- p + theme(aspect.ratio = .5, strip.background = element_blank(), strip.placement = \"outside\")\n", + "p <- p + theme(panel.background = element_rect(fill = \"white\", colour = 'black'))\n", + "p <- p + geom_vline(xintercept = c(4, 18, 53, 67), \n", + " linetype = 1, color = \"black\", alpha = .2)\n", + "p" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "id": "901780a4-d795-4b2a-bcab-287d97ca1804", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "text/html": [ + "png: 2" + ], + "text/latex": [ + "\\textbf{png:} 2" + ], + "text/markdown": [ + "**png:** 2" + ], + "text/plain": [ + "png \n", + " 2 " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "pdf(\"Figure_5_b.pdf\", width = 4, height = 8)\n", + "print(p)\n", + "dev.off()" + ] + } + ], + "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": "4.1.3" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +}