grst/test-bimodal.ipynb

## test-bimodal.ipynb
{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "import scirpy as ir\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "adata = ir.datasets.maynard2020()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "ir.tl.chain_qc(adata)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/sturm/anaconda3/envs/sctcrpy2/lib/python3.7/site-packages/anndata/_core/anndata.py:1094: FutureWarning: is_categorical is deprecated and will be removed in a future version.  Use is_categorical_dtype instead\n",
      "  if not is_categorical(df_full[k]):\n"
     ]
    }
   ],
   "source": [
    "adata = adata[(adata.obs[\"receptor_type\"] == \"BCR\") & (adata.obs[\"IR_VJ_1_cdr3\"] != \"None\"), :].copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 351/351 [00:00<00:00, 1210.23it/s]\n",
      "100%|██████████| 823686/823686 [00:16<00:00, 49198.87it/s]\n",
      "100%|██████████| 3193369/3193369 [00:14<00:00, 222296.24it/s]\n"
     ]
    }
   ],
   "source": [
    "ir.pp.ir_neighbors(adata, sequence=\"aa\", metric=\"levenshtein\", cutoff=255, receptor_arms=\"VJ\", dual_ir=\"primary_only\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 351/351 [00:05<00:00, 58.92it/s]\n",
      "100%|██████████| 823686/823686 [00:16<00:00, 50988.46it/s]\n",
      "100%|██████████| 3193369/3193369 [00:14<00:00, 214821.90it/s]\n"
     ]
    }
   ],
   "source": [
    "ir.pp.ir_neighbors(adata, sequence=\"aa\", metric=\"alignment\", cutoff=255, receptor_arms=\"VJ\", dual_ir=\"primary_only\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Levenshtein"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "dists = adata.uns[\"ir_neighbors_aa_levenshtein\"][\"distances\"].data - 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(dists, kde_kws={\"bw\": .5})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Alignment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "dists = adata.uns[\"ir_neighbors_aa_alignment\"][\"distances\"].data - 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(dists, kde_kws={\"bw\": 2})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### zoom in on [0, 10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(dists[dists < 10])"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [conda env:sctcrpy2]",
   "language": "python",
   "name": "conda-env-sctcrpy2-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}