{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Monocle 2" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "ExecuteTime": { "end_time": "2019-05-24T00:35:12.348384Z", "start_time": "2019-05-24T00:35:09.024490Z" } }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "findfont: Font family ['Raleway'] not found. Falling back to DejaVu Sans.\n", "findfont: Font family ['Lato'] not found. Falling back to DejaVu Sans.\n" ] } ], "source": [ "# load modules\n", "import os\n", "import numpy as np\n", "import pandas as pd\n", "import pickle\n", "\n", "# Plotting imports\n", "import matplotlib\n", "import matplotlib.pyplot as plt\n", "\n", "import palantir\n", "import scanpy as sc" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "ExecuteTime": { "end_time": "2019-05-24T00:35:12.360834Z", "start_time": "2019-05-24T00:35:12.356698Z" } }, "outputs": [], "source": [ "%matplotlib inline" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Download data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Anndata objects with all the data and metadata are publically avaiable at: https://s3.amazonaws.com/dp-lab-data-public/palantir/human_cd34_bm_rep[1-3].h5ad. This notebook use replicate 1 (https://s3.amazonaws.com/dp-lab-data-public/palantir/human_cd34_bm_rep1.h5ad) for illustration. \n", "\n", "Description of the anndata object is available at https://s3.amazonaws.com/dp-lab-data-public/palantir/readme" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Load data" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "ExecuteTime": { "end_time": "2019-05-24T00:35:13.494273Z", "start_time": "2019-05-24T00:35:12.363343Z" } }, "outputs": [], "source": [ "# Load the AnnData object\n", "ad = sc.read('annadata/human_cd34_bm_rep1.h5ad')\n", "colors = pd.Series(ad.uns['cluster_colors'])\n", "ct_colors = pd.Series(ad.uns['ct_colors'])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Monocle 2" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "ExecuteTime": { "end_time": "2019-05-24T00:35:13.508932Z", "start_time": "2019-05-24T00:35:13.496634Z" } }, "outputs": [], "source": [ "boundary_clusters = pd.Series([])\n", "boundary_clusters['HSC'] = 0\n", "boundary_clusters['Mono'] = 3\n", "boundary_clusters['Mega'] = 9\n", "boundary_clusters['CLP'] = 5\n", "boundary_clusters['Ery'] = 8\n", "boundary_clusters['DC'] = 7" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "ExecuteTime": { "end_time": "2019-05-24T00:35:13.561723Z", "start_time": "2019-05-24T00:35:13.511077Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "HSC\n", "281\n", "Mono\n", "274\n", "Mega\n", "250\n", "CLP\n", "250\n", "Ery\n", "584\n", "DC\n", "100\n" ] } ], "source": [ "# Gene subsets to be used for Monocle 2\n", "statistic = pd.DataFrame(ad.varm['mast_diff_res_statistic'], \n", " index=ad.var_names, columns=ad.uns['mast_diff_res_columns'])\n", "\n", "gene_subsets = dict()\n", "for ct in boundary_clusters.index:\n", " print(ct)\n", " others = boundary_clusters.index.difference([ct])\n", " index = 'Cluster{}'.format(boundary_clusters[ct])\n", "\n", " genes = statistic.index[(statistic.loc[:, index] > 0.1) &\n", " (statistic.iloc[:, boundary_clusters[others]].max(axis=1) < 0.25)]\n", " genes = statistic.loc[genes, index].sort_values().index[::-1]\n", "\n", " if ct == 'DC':\n", " genes = genes[:100]\n", " if ct == 'Mega' or ct == 'CLP':\n", " genes = genes[:250]\n", "\n", " print(len(genes))\n", " gene_subsets[ct] = list(genes)\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We export data and use the Monocle2 R Script to compute the results. The exporting code is shown below" ] }, { "cell_type": "markdown", "metadata": { "ExecuteTime": { "end_time": "2018-10-14T15:40:30.806410Z", "start_time": "2018-10-14T15:40:30.793806Z" } }, "source": [ "```\n", "# Export data \n", "monocle_dir = 'monocle2/'\n", "os.makedirs(monocle_dir, exist_ok=True)\n", "\n", "# Genes\n", "genes = np.unique(np.concatenate(list(gene_subsets.values())))\n", "# Expression matrix\n", "counts = pd.DataFrame(ad.raw.X.todense(), index=ad.obs_names, columns=ad.var_names)\n", "pd.DataFrame(counts).to_csv(f'{monocle_dir}/counts.csv')\n", "pd.DataFrame(genes).to_csv(f'{monocle_dir}/genes.csv')\n", "```" ] }, { "cell_type": "markdown", "metadata": { "ExecuteTime": { "end_time": "2018-06-25T22:09:29.367967Z", "start_time": "2018-06-25T22:07:36.016475Z" } }, "source": [ "R snippet used is shown below was saved as ```monocle_wrapper.R```" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "```\n", "library(monocle, quiet=TRUE)\n", "\n", "args <- commandArgs(trailingOnly = TRUE)\n", "out_dir <- args[1]\n", "\n", "\n", "print('Loading data...')\n", "umi_matrix <- read.csv(sprintf(\"%s/counts.csv\", out_dir), row.names=1)\n", "\n", "# Annoated dataframes\n", "pd = data.frame(cell_names = rownames(umi_matrix))\n", "rownames(pd) = rownames(umi_matrix)\n", "fd = data.frame(gene_short_name = colnames(umi_matrix))\n", "rownames(fd) = colnames(umi_matrix)\n", "\n", "HSMM <- newCellDataSet(as(t(umi_matrix), \"sparseMatrix\"),\n", " phenoData = AnnotatedDataFrame(pd), \n", " featureData = AnnotatedDataFrame(fd), \n", " expressionFamily=negbinomial.size())\n", "\n", "# Size factors and dispersion\n", "print('Size factors and dispersion')\n", "HSMM <- estimateSizeFactors(HSMM)\n", "HSMM <- estimateDispersions(HSMM)\n", "\n", "\n", "# Differentially expressed genes from clusters\n", "print('Ordering genes...')\n", "ordering_genes <- read.csv(sprintf(\"%s/genes.csv\", out_dir), stringsAsFactors=FALSE)[,2]\n", "HSMM_subset <- setOrderingFilter(HSMM, ordering_genes)\n", "\n", "\n", "print('Dimensionality reduction...')\n", "HSMM_subset <- reduceDimension(HSMM_subset, max_components = 2,\n", " method = 'DDRTree')\n", "\n", "\n", "HSMM_subset <- orderCells(HSMM_subset)\n", "# early_cell = 'Run5_205922701598003'\n", "early_cell = 'GSM2743164_rep1_tmouse_1068'\n", "# Rerun with early state\n", "HSMM_subset <- orderCells(HSMM_subset, root_state = pData(HSMM_subset)[early_cell, 'State'])\n", "\n", "\n", "save(HSMM_subset, file=sprintf(\"%s/HSMM_subset.rda\", out_dir))\n", "write.csv(pData(HSMM_subset), sprintf(\"%s/phenodata.csv\", out_dir), quote=FALSE)\n", "write.csv(reducedDimS(HSMM_subset), sprintf(\"%s/red_dims.csv\", out_dir), quote=FALSE)\n", "\n", "```" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The above script was invoked as shown below" ] }, { "cell_type": "markdown", "metadata": { "ExecuteTime": { "end_time": "2019-05-23T20:00:46.045583Z", "start_time": "2019-05-23T20:00:46.040542Z" } }, "source": [ "```\n", "import subprocess\n", "\n", "ss_path = 'monocle2/monocle_wrapper.R'\n", "args = f'Rscript {ss_path} {monocle_dir}'\n", "print('Running Monocle2 using: {}\\n'.format(args))\n", "with subprocess.Popen(args,\n", " stdout=None, stderr=subprocess.PIPE,\n", " shell=True) as p:\n", " out, err = p.communicate()\n", "\n", "```" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The results from the above run is available at ```results/monocle2```" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Load results " ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "ExecuteTime": { "end_time": "2019-05-24T00:35:14.273596Z", "start_time": "2019-05-24T00:35:13.563840Z" } }, "outputs": [], "source": [ "pdata = pd.read_csv('results/monocle2/phenodata.csv', index_col=0)\n", "rdims = pd.read_csv('results/monocle2/red_dims.csv', index_col=0).T\n", "rdims.columns = ['x', 'y']" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### States" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "ExecuteTime": { "end_time": "2019-05-24T00:35:14.786487Z", "start_time": "2019-05-24T00:35:14.275918Z" } }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=[5, 5])\n", "states = pdata.State.unique()\n", "s_colors = matplotlib.colormaps[\"hls\"](range(len(states)))\n", "s_colors = pd.Series([matplotlib.colors.rgb2hex(rgba) for rgba in s_colors], index = states)\n", "plt.scatter(rdims.loc[:, 'x'], rdims.loc[:, 'y'], s=5, \n", " color=s_colors[pdata.State])\n", "ax = plt.gca()\n", "ax.set_axis_off()" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "ExecuteTime": { "end_time": "2019-05-24T00:35:15.291230Z", "start_time": "2019-05-24T00:35:14.788909Z" } }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=[5, 5])\n", "plt.scatter(rdims.loc[:, 'x'], rdims.loc[:, 'y'], s=5, \n", " color=colors[ad.obs['clusters']])\n", "ax = plt.gca()\n", "ax.set_axis_off()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Gene expression" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "ExecuteTime": { "end_time": "2019-05-24T00:35:15.297337Z", "start_time": "2019-05-24T00:35:15.293468Z" } }, "outputs": [], "source": [ "imputed_data = pd.DataFrame(ad.obsm['MAGIC_imputed_data'], \n", " index=ad.obs_names, columns=ad.var_names)" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "ExecuteTime": { "end_time": "2019-05-24T00:35:17.464793Z", "start_time": "2019-05-24T00:35:15.299798Z" } }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "genes = ['CD34', 'MPO', 'CD79B', 'GATA1', 'CSF1R', 'ITGA2B']\n", "labels = ['CD34', 'MPO', 'CD79B', 'GATA1', 'CSF1R', 'CD41']\n", "\n", "fig = palantir.plot.FigureGrid(6, 3)\n", "for gene, label, ax in zip(genes, labels, fig):\n", " ax.scatter(rdims.loc[:, 'x'], rdims.loc[:, 'y'], \n", " s=5, cmap=matplotlib.cm.Spectral_r, c=imputed_data.loc[rdims.index, gene])\n", " ax.set_axis_off()\n", " ax.set_title(label)\n" ] } ], "metadata": { "hide_input": false, "kernelspec": { "display_name": "palantir_v1", "language": "python", "name": "palantir_v1" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.11.4" }, "nav_menu": {}, "toc": { "base_numbering": 1, "nav_menu": {}, "number_sections": true, "sideBar": true, "skip_h1_title": false, "title_cell": "Table of Contents", "title_sidebar": "Contents", "toc_cell": false, "toc_position": { "height": "calc(100% - 180px)", "left": "10px", "top": "150px", "width": "253px" }, "toc_section_display": "block", "toc_window_display": true }, "toc_position": { "height": "1170px", "left": "0px", "right": "1068px", "top": "106px", "width": "212px" }, "varInspector": { "cols": { "lenName": 16, "lenType": 16, "lenVar": 40 }, "kernels_config": { "python": { "delete_cmd_postfix": "", "delete_cmd_prefix": "del ", "library": "var_list.py", "varRefreshCmd": "print(var_dic_list())" }, "r": { "delete_cmd_postfix": ") ", "delete_cmd_prefix": "rm(", "library": "var_list.r", "varRefreshCmd": "cat(var_dic_list()) " } }, "position": { "height": "477px", "left": "5px", "right": "1139px", "top": "442px", "width": "254px" }, "types_to_exclude": [ "module", "function", "builtin_function_or_method", "instance", "_Feature" ], "window_display": false }, "widgets": { "application/vnd.jupyter.widget-state+json": { "state": {}, "version_major": 2, "version_minor": 0 } } }, "nbformat": 4, "nbformat_minor": 4 }