[6e90e5]: / code_final / Th1_2_17_proportion.ipynb

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{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "handy-framework",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Attaching SeuratObject\n",
      "\n",
      "Loading required package: reticulate\n",
      "\n"
     ]
    }
   ],
   "source": [
    "library(ggplot2)\n",
    "#library(DESeq2)\n",
    "library(Seurat)\n",
    "#library(SeuratDisk)\n",
    "library(sceasy)\n",
    "library(reticulate)\n",
    "library(magrittr)\n",
    "library(anndata)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "round-dover",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message in asMethod(object):\n",
      "“sparse->dense coercion: allocating vector of size 15.4 GiB”\n"
     ]
    }
   ],
   "source": [
    "h5ad_file <- \"./CTCL/object_revision/all_tumourcell_raw_20240707.h5ad\"\n",
    "sdata <- read_h5ad(h5ad_file)\n",
    "sdata <- CreateSeuratObject(counts = t(as.matrix(sdata$X)), meta.data = sdata$obs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "recreational-yellow",
   "metadata": {},
   "outputs": [],
   "source": [
    "table(sdata$donor)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "human-apparel",
   "metadata": {},
   "outputs": [],
   "source": [
    "cc_mat <- c()\n",
    "col <- c()\n",
    "for (donor in unique(sdata$donor)) {\n",
    "    sdata_sub <- subset(sdata, cells = colnames(sdata)[which(sdata$donor == donor)])\n",
    "    mat <- sdata_sub@assays$RNA@counts\n",
    "    Th1 <- sum(mat['TBX21',]>0 & mat['GATA3',] == 0 & mat['RORC',] == 0)\n",
    "    Th2 <- sum(mat['GATA3',]>0 & mat['TBX21',] == 0 & mat['RORC',] == 0)\n",
    "    Th17 <- sum(mat['RORC',]>0 & mat['TBX21',] == 0 & mat['GATA3',] == 0)\n",
    "    Th1_Th2 <- sum(mat['TBX21',]>0 & mat['GATA3',] > 0 & mat['RORC',] == 0)\n",
    "    Th2_Th17 <- sum(mat['GATA3',]>0 & mat['TBX21',] == 0 & mat['RORC',] > 0)\n",
    "    Th1_Th17 <- sum(mat['TBX21',]>0 & mat['GATA3',] == 0 & mat['RORC',] > 0)\n",
    "    Th1_Th2_Th17 <- sum(mat['TBX21',]>0 & mat['GATA3',] > 0 & mat['RORC',] > 0)\n",
    "    cc <- c(Th1, Th2, Th17, Th1_Th2, Th2_Th17, Th1_Th17, Th1_Th2_Th17)\n",
    "    cc_mat <- cbind(cc_mat, cc)\n",
    "    col <- c(col, donor)\n",
    "}\n",
    "colnames(cc_mat) <- col\n",
    "rownames(cc_mat) <- c('Th1', 'Th2', 'Th17', 'Th1_Th2',\n",
    "                      'Th2_Th17', 'Th1_Th17', 'Th1_Th2_Th17')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "informal-machinery",
   "metadata": {},
   "outputs": [],
   "source": [
    "#cc_mat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "returning-matthew",
   "metadata": {},
   "outputs": [],
   "source": [
    "cc_mat_per <- expss::prop_col(cc_mat)\n",
    "cc_mat_per"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "alpine-festival",
   "metadata": {},
   "outputs": [],
   "source": [
    "cc_mat_per_round <- round(cc_mat_per,2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "applied-cycle",
   "metadata": {},
   "outputs": [],
   "source": [
    "hec_new <- reshape2::melt(t(cc_mat_per_round),value.name = \"prop\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "vocal-sigma",
   "metadata": {},
   "outputs": [],
   "source": [
    "hec_new$Var1 <- factor(hec_new$Var1, levels = c('CTCL2','CTCL6','CTCL7','P107','P138','CTCL9','CTCL16','CTCL3','CTCL4',\n",
    "                                                'CTCL8','MF15','MF22','PT50','CTCL10','P65','P90',\n",
    "                                                'MF14','MF26',\n",
    "                                                'CTCL1','CTCL5','MF17','MF21','MF27','MF30','PT56','PT35','PT55','PT53','PT47','PT52','CTCL13',\n",
    "                                                'P84','P73','MF312','MF28','CTCL12','CTCL18','MF309','MF311','PT11')) ### sort as stage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "demanding-glory",
   "metadata": {},
   "outputs": [],
   "source": [
    "#pdf('./Th1_Th2_Th17.pdf',w = 8, h = 9)\n",
    "ggplot(hec_new,aes(x=Var2,y=Var1,fill=prop))+geom_tile()+\n",
    "  geom_text(aes(fill = hec_new$prop, label = round(hec_new$prop, 2)))+\n",
    "  scale_fill_gradient2(high = \"black\", \n",
    "                       mid = \"grey60\", \n",
    "                       low = \"white\", \n",
    "                       midpoint = 0.7) + \n",
    "  theme(panel.grid.major.x=element_blank(), #no gridlines\n",
    "        panel.grid.minor.x=element_blank(), \n",
    "        panel.grid.major.y=element_blank(), \n",
    "        panel.grid.minor.y=element_blank(),\n",
    "        panel.background=element_rect(fill=\"white\"), # background=white\n",
    "        axis.text.x = element_text(angle=90, hjust = 1,vjust=1,size = 12,face = \"bold\"),\n",
    "        plot.title = element_text(size=20,face=\"bold\"),\n",
    "        axis.text.y = element_text(size = 12,face = \"bold\")) + \n",
    "  ggtitle(\"heatmap Plot\")+\n",
    "  theme(legend.title=element_text(face=\"bold\", size=14)) + \n",
    "  scale_x_discrete(name=\"\") +\n",
    "  scale_y_discrete(name=\"\") +\n",
    "  labs(fill=\"heatmap legend\")\n",
    "#dev.off()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "lesbian-richards",
   "metadata": {},
   "outputs": [],
   "source": [
    "cc_mat_per_1 <- cc_mat_per %>% t() %>% as.data.frame() %>%\n",
    "                dplyr::mutate(Stage = \"Late\")\n",
    "### cc_mat_per no round"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "interstate-professor",
   "metadata": {},
   "outputs": [],
   "source": [
    "cc_mat_per_1[c('MF14','MF15','P90',\n",
    "             'P65', 'MF22', 'MF26', 'CTCL8','CTCL4',\n",
    "             'CTCL3', 'P138','P107','CTCL7',\n",
    "             'CTCL6', 'CTCL2','PT50',\n",
    "              'CTCL9','CTCL16','CTCL10'), 'Stage'] <- \"Early\"\n",
    "cc_mat_per_1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "composite-taste",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message in geom_violin(width = 0.8, outlier.colour = \"white\", outlier.size = 0.5, :\n",
      "“\u001b[1m\u001b[22mIgnoring unknown parameters: `outlier.colour` and `outlier.size`”\n"
     ]
    },
    {
     "data": {
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pQg1A1hqaioiIiyJ00L0YZXKrUmJjZu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\nVgu9PnUaAAAAAElFTkSuQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#pdf('./figures/Th1_Th2_Th17_boxplot.pdf',w = 4, h = 7)\n",
    "set.seed(123)\n",
    "ggplot(data=cc_mat_per_1, aes(x=Stage, y=Th2, fill=Stage))+\n",
    "  geom_violin(width=0.8, outlier.colour = \"white\", outlier.size = 0.5, alpha=0.5)+\n",
    "  ggbeeswarm::geom_quasirandom(method = \"pseudorandom\", dodge.width=0.2, size=2, shape=19, alpha=0.5) +\n",
    "  scale_fill_manual(values = c(\"#A1C15F\",\"#97B2DD\")) +\n",
    "  geom_boxplot(width=0.2,color=\"black\",outlier.alpha = 0.4)+\n",
    "  #geom_boxplot(notch=T, width=0.1, fill=NA, outlier.shape=NA, size=0.3) +\n",
    "  #geom_point(aes(group=samp_loc),position=position_jitter(width = 0.1,height = 0),alpha=0.7,shape=19, color=\"grey60\")+\n",
    "  #geom_violin(width=2,color=\"black\")+\n",
    "  #geom_errorbar(data=bb, mapping = aes(x=tissue, y=mtb.median, ymin = mtb.median-mtb.sd, \n",
    "  #                                   ymax=mtb.median+mtb.sd),\n",
    "  #            size=0.5, color=\"red\",width=0)+\n",
    "  #geom_point(data=bb,mapping =aes(x=tissue, y=mtb.median),\n",
    "  #           size=9,color=\"red\",shape=\"_\") +\n",
    "  #coord_cartesian(ylim = c(0,210))+\n",
    "  theme_bw()\n",
    "#dev.off()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "academic-swedish",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\n",
       "\tWilcoxon rank sum exact test\n",
       "\n",
       "data:  c1 and c2\n",
       "W = 66, p-value = 0.0003192\n",
       "alternative hypothesis: true location shift is not equal to 0\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "c1 <- cc_mat_per_1$Th2[which(cc_mat_per_1$Stage == \"Early\")]\n",
    "c2 <- cc_mat_per_1$Th2[which(cc_mat_per_1$Stage == \"Late\")]\n",
    "wilcox.test(c1,c2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "harmful-letter",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "4.0.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}