{ "metadata": { "name": "", "signature": "sha256:6c6511db1115a88c6ea75a28813a27d4b9a2eaa28d3dc66f178554ea622a0f6b" }, "nbformat": 3, "nbformat_minor": 0, "worksheets": [ { "cells": [ { "cell_type": "heading", "level": 1, "metadata": {}, "source": [ "Hidden patients and hidden genes: Understanding cancer data with matrix factorization" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Biotechnological innovations in the last decade have enabled systematic large-scale cancer genome studies. Cancer projects such as The Cancer Genome Atlas (TCGA) and The International Cancer Genome Consortium (ICGC) coordinate the generation of catalogues of tumors from over 50 different cancer types that are of clinical importance across the globe. These catalogues contain comprehensive data of more than 25,000 cancer genomes at a high, often at a single nucleotide, resolution level. The genomes of individual cancers are accompanied by the analyses of transcriptome, epigenome and sequence variation. Furthermore, where possible, measurements are provided for matched tumor and non-tumor tissue to distinguish inherited from oncogenic variation. \n", "\n", "Diversity and abundance of data provided by the cancer projects challenge computer scientists of all kinds to develop innovative software, hardware and analytic solutions for data analysis. The hope is that with the computationally and statistically stronger approaches we will be able to reveal biological features that drive cancer development, define cancer types relevant for prognosis and, ultimately, enable the development of new cancer therapies. \n", "\n", "Here, we analyze a transcriptome data set on breast cancer obtained from the ICGC. The analysis relies on a popular class of data mining techniques, called nonnegative matrix factorization, to find groups of patients with similar expression profiles and groups of genes with similar activation levels across patients. " ] }, { "cell_type": "code", "collapsed": false, "input": [ "%matplotlib inline\n", "\n", "from collections import defaultdict, Counter\n", "import urllib\n", "\n", "import numpy as np\n", "from matplotlib import pyplot as plt\n", "import matplotlib.gridspec as gridspec\n", "from sklearn import preprocessing\n", "import scipy.cluster.hierarchy as sch\n", "\n", "import nimfa" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 2 }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "Obtaining data from the International Cancer Genome Consortium (ICGC)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We start by downloading data from the ICGC Data Portal (https://dcc.icgc.org/projects). In addition to its data repository role, the ICGC Data Portal also provides tools for visualizing and querying the data, for example, a distribution of somatic mutations in patient's genomes across cancer types. In this column we use publicly available data, however, we note that researchers have to apply for access to controlled data. " ] }, { "cell_type": "code", "collapsed": false, "input": [ "clinical_fname = 'clinical.BRCA-US.tsv.gz'\n", "urllib.request.urlretrieve('https://dcc.icgc.org/api/v1/download?' \\\n", " 'fn=/release_18/Projects/BRCA-US/' \\\n", " 'clinical.BRCA-US.tsv.gz', clinical_fname);\n", "\n", "expression_fname = 'protein_expression.BRCA-US.tsv.gz'\n", "urllib.request.urlretrieve('https://dcc.icgc.org/api/v1/download?' \\\n", " 'fn=/release_18/Projects/BRCA-US/' \\\n", " 'protein_expression.BRCA-US.tsv.gz', expression_fname);" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 3 }, { "cell_type": "markdown", "metadata": {}, "source": [ "Once the download has completed, we have two new files on our local disk. The first file, `clinical.BRCA-US.tsv.gz`, contains basic clinical information, such as patient and specimen identifiers and categorization of specimens into tumor and non-tumor types. The second file, `protein_expression.BRCA-US.tsv.gz`, is a protein expression data set of breast cancer patients (`BRCA` is a standard acronym used by the cancer projects to indicate data related to breast cancer). Each row in the expression file contains normalized expression value of a particular protein in a given specimen of a specific patient. \n", "\n", "we read data columns that correspond to patient and specimen identifiers and expression measurements into two `numpy` arrays, `C` and `E`." ] }, { "cell_type": "code", "collapsed": false, "input": [ "C = np.genfromtxt(clinical_fname, delimiter='\\t', dtype='object', \n", " skip_header=1, usecols=(0, 17, 19))" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 12 }, { "cell_type": "code", "collapsed": false, "input": [ "E = np.genfromtxt(expression_fname, delimiter='\\t', dtype='object', \n", " skip_header=1, usecols=(0, 2, 7, 10))" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 13 }, { "cell_type": "code", "collapsed": false, "input": [ "donors = set(E[:, 0])\n", "genes = set(E[:, 2])\n", "print(len(donors))\n", "print(len(genes))" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "298\n", "115\n" ] } ], "prompt_number": 14 }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "Data preprocessing" ] }, { "cell_type": "code", "collapsed": false, "input": [ "spec2gene = defaultdict(set)\n", "for spec_id, gene in E[:, 1:3]:\n", " spec2gene[spec_id].add(gene)\n", "\n", "donor2spec = defaultdict(set)\n", "for donor, spec_id in E[:, :2]:\n", " donor2spec[donor].add(spec_id)\n", "\n", "# how many specimens are there per donor?\n", "tmp = [len(v) for v in donor2spec.values()]\n", "print(Counter(tmp))\n", "\n", "# protein expression data is available only for tumor data (no matched normal tissue)\n", "spec2spec_type = {C[idx, 1]: C[idx, 2] for idx, spec in enumerate(C[:, 1]) if spec in spec2gene}\n", "print(set(spec2spec_type.values()))" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "Counter({1: 298})\n", "{b'Primary tumour - solid tissue'}\n" ] } ], "prompt_number": 15 }, { "cell_type": "code", "collapsed": false, "input": [ "data = np.zeros((len(donors), len(genes)))\n", "\n", "donor2id = {donor.decode('UTF-8'): idx for idx, donor in enumerate(donors)}\n", "id2donor = dict(zip(donor2id.values(), donor2id.keys()))\n", "\n", "gene2id = {gene.decode('UTF-8'): idx for idx, gene in enumerate(genes)}\n", "id2gene = dict(zip(gene2id.values(), gene2id.keys()))\n", "\n", "for donor, gene, val in E[:, [0, 2, 3]]:\n", " data[donor2id[donor.decode('UTF-8')], gene2id[gene.decode('UTF-8')]] = float(val)" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 16 }, { "cell_type": "code", "collapsed": false, "input": [ "# level of sparsity\n", "print(np.sum(data != 0)/data.size)\n", "\n", "# negative elements\n", "print(np.sum(data < 0))\n", "\n", "# remove negative elements\n", "data = data - np.min(data)\n", "\n", "# normalize data\n", "data = preprocessing.Normalizer().fit_transform(data)" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "1.0\n", "17147\n" ] } ], "prompt_number": 17 }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "Clustering of genes" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Next, we perform cluster analysis to identify groups of genes with similar behavior across patients. The hypothesis is that genomes of all cancers accumulate somatic and epigenetic marks that affect protein-coding or regulatory components of genes. These marks in turn silence or overexpress genes, which results in notable changes of protein expression levels in tumor tissue. By finding genes that are consistently silenced or overexpressed in cancer, we might narrow down candidate genes and provide focus for downstream analysis. " ] }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "Nonnegative matrix factorization" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Nonnegative matrix factorization (NMF) is typically concerned with the decomposition of a nonnegative data matrix into two low-dimensional (latent) data matrices, such that their matrix product provides a good surrogate of the original data matrix. \n", "\n", "There are a few important concepts to understand in order to fully appreciate the NMF. First, since not only input data matrix is nonnegative, but also the latent matrices contain solely nonnegative values, NMF is able to learn a parts-based data representation. For example, if we apply NMF to a database of facial images, then the latent components (vectors) of the matrices estimated by the NMF correspond to parts of faces. If we applied NMF to a text corpus, then the latent components would encode semantic features of text. Second, high generalization power of NMF is due to its ability to compress large input data matrix and represent it with latent matrices, which have substantially fewer dimensions. Technically, the dimensionality of latent matrices is known as factorization rank. In this sense, NMF might be a good example where less can be more. \n", "\n", "Many variants of nonnegative matrix factorization have been developed in recent years. These augment the objective function with different types of regularization imposed on the latent matrices, provide various generalizations of the notion of a good matrix surrogate, and extend factorization of a single data matrix to simultaneous decomposition of multiple matrices. \n", "\n", "We consider **Nimfa**, an open-source Python library for NMF, to factorize our matrix of protein expression measurements. Nimfa implements over a dozen of nonnegative matrix factorization algorithms, initialization techniques and provides quality scoring.\n", "\n", " Zitnik, Marinka, and Blaz Zupan. Nimfa: A Python library for nonnegative matrix factorization. The Journal of Machine Learning Research 13, 1:849-853, 2012.\n", "\n", "In our example, we run one of the most widely used NMF variants. This variant estimates the NMF model by iteratively improving current estimates of the latent matrices until a local minimum is attained, measured as Kullback-Leibler divergence between the input matrix and its estimated matrix surrogate. " ] }, { "cell_type": "code", "collapsed": false, "input": [ "rank = 10\n", "nmf = nimfa.Nmf(data, rank=rank, seed='random_vcol', max_iter=100, \n", " update='divergence', objective='div', n_run=50, track_factor=True)\n", "nmf_fit = nmf()" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 19 }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "Plot dendrogram along with the heatmap" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Next, we use the estimated NMF model to cluster genes into groups. Whereas the latent components obtained from an image database correspond to parts of faces, the latent components of a protein expression data set represent subpopulations of patients and gene subsets. Conveniently, we refer to these latent components as *hidden patients* and *hidden genes*.\n", "\n", "We now use the memberships of genes to hidden genes as a means to group genes together. Notice that above we ran the NMF algorithm 50 times (`n_run = 50`). To obtain a stable gene clustering we examine gene-hidden gene memberships from all factorization runs and average gene membership indicators to obtain a *consensus clustering*. \n", "\n", "Once we obtain the consensus clustering we can visualize it in a heatmap with the rows reordered to make the groups explicit. " ] }, { "cell_type": "code", "collapsed": false, "input": [ "def clean_axis(ax):\n", " ax.get_xaxis().set_ticks([])\n", " ax.get_yaxis().set_ticks([])\n", " for sp in ax.spines.values():\n", " sp.set_visible(False)\n", "\n", "fig = plt.figure(figsize=(13.9, 10))\n", "heatmapGS = gridspec.GridSpec(1, 2, wspace=.01, hspace=0., width_ratios=[0.25,1])\n", "\n", "C = 1 - nmf_fit.fit.consensus()\n", "Y = sch.linkage(C, method='average')\n", "\n", "denAX = fig.add_subplot(heatmapGS[0,0])\n", "denD = sch.dendrogram(Y, orientation='right', link_color_func=lambda k: 'black')\n", "clean_axis(denAX)\n", "\n", "heatmapAX = fig.add_subplot(heatmapGS[0,1])\n", "D = C[denD['leaves'], :][:, denD['leaves']]\n", "axi = heatmapAX.imshow(D, interpolation='nearest', aspect='equal', origin='lower', cmap='RdBu') \n", "clean_axis(heatmapAX)\n", "\n", "cb = fig.colorbar(axi, fraction=0.046, pad=0.04, aspect=10) \n", "cb.set_label('Distance', fontsize=20)" ], "language": "python", "metadata": {}, "outputs": [ { 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M2X7SaojtU5Itz33pB67p+su+Cm3WzMcRrUvCmDS+ZBLnL1hTQZ4dmw+xxTXu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\nt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"text": [ "" ] } ], "prompt_number": 66 }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "Clustering of patients" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Similarly, we can stratify cancer patients into groups by considering memberships of patients to the respective latent components (i.e., hidden patients)." ] }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "Nonnegative matrix factorization" ] }, { "cell_type": "code", "collapsed": false, "input": [ "rank = 10\n", "nmf = nimfa.Nmf(data.T, rank=rank, seed='random_vcol', max_iter=200, \n", " update='euclidean', objective='conn', conn_change=40, \n", " n_run=50, track_factor=True)\n", "nmf_fit = nmf()" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 67 }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "Plot dendrogram along with the heatmap" ] }, { "cell_type": "code", "collapsed": false, "input": [ "def clean_axis(ax):\n", " ax.get_xaxis().set_ticks([])\n", " ax.get_yaxis().set_ticks([])\n", " for sp in ax.spines.values():\n", " sp.set_visible(False)\n", "\n", "fig = plt.figure(figsize=(13.9, 10))\n", "heatmapGS = gridspec.GridSpec(1, 2, wspace=.01, hspace=0., width_ratios=[0.25,1])\n", "\n", "C = 1 - nmf_fit.fit.consensus()\n", "Y = sch.linkage(C, method='average')\n", "\n", "denAX = fig.add_subplot(heatmapGS[0,0])\n", "denD = sch.dendrogram(Y, orientation='right', link_color_func=lambda k: 'black')\n", "clean_axis(denAX)\n", "\n", "heatmapAX = fig.add_subplot(heatmapGS[0,1])\n", "D = C[denD['leaves'], :][:, denD['leaves']]\n", "axi = heatmapAX.imshow(D, interpolation='nearest', aspect='equal', origin='lower', cmap='RdBu') \n", "clean_axis(heatmapAX)\n", "\n", "cb = fig.colorbar(axi, fraction=0.046, pad=0.04, aspect=10) \n", "cb.set_label('Distance', fontsize=20)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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KK2L2x01Pl/y45tYhjmdSi/N9P76998LHSG+5C4O+ztZCPM/tdYA3Vtx6aMsM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\nKQiCkwHcEIbh2ebz1wEgDMPvpe1vtv/3MAxP2hf1TYNngDws+lIjNEAndR4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pe9O4xX3u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vOo1UmHXGoo0A2trETGXcgoMkptDD8HgKIpiT7SBa6ELnCaPfFGLYuiVVo3E4ewKKz3Qw1Q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\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SWGYu4uzti8qEgNP5cvkidjoL+uM33RRbhwNvFkLls+ImZ1AyMtiLsYn4VN1/9Gax196/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\nMAzDMAzDMK4bbABkGIZhGIZhGMZ1w/8PMvn5WFXjdNIAAAAASUVORK5CYII=\n", "text": [ "" ] } ], "prompt_number": 69 }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "Hidden patients and hidden genes" ] }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "Latent dimensionality selection" ] }, { "cell_type": "code", "collapsed": false, "input": [ "rank_cands = range(3, 30, 5)\n", "snmf = nimfa.Snmf(data, seed='random_vcol', max_iter=100)\n", "summary = snmf.estimate_rank(rank_range=rank_cands, n_run=10, what='all')" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 27 }, { "cell_type": "code", "collapsed": false, "input": [ "summary[3].keys()" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 28, "text": [ "dict_keys(['euclidean', 'dispersion', 'cophenetic', 'rss', 'residuals', 'kl', 'connectivity', 'select_features', 'sparseness', 'n_run', 'n_iter', 'rank', 'consensus', 'evar', 'score_features', 'predict_samples', 'predict_features'])" ] } ], "prompt_number": 28 }, { "cell_type": "code", "collapsed": false, "input": [ "rss = [summary[rank]['rss'] for rank in rank_cands]\n", "coph = [summary[rank]['cophenetic'] for rank in rank_cands]\n", "disp = [summary[rank]['dispersion'] for rank in rank_cands]\n", "spar = [summary[rank]['sparseness'] for rank in rank_cands]\n", "spar_w, spar_h = zip(*spar)\n", "evar = [summary[rank]['evar'] for rank in rank_cands]\n", "\n", "plt.plot(rank_cands, rss, 'o-', label='RSS', linewidth=2)\n", "plt.plot(rank_cands, coph, 'o-', label='Cophenetic correlation', linewidth=2)\n", "plt.plot(rank_cands, disp,'o-', label='Dispersion', linewidth=2)\n", "plt.plot(rank_cands, spar_w, 'o-', label='Sparsity (Basis)', linewidth=2)\n", "plt.plot(rank_cands, spar_h, 'o-', label='Sparsity (Mixture)', linewidth=2)\n", "plt.plot(rank_cands, evar, 'o-', label='Explained variance', linewidth=2)\n", "plt.legend(loc='upper center', bbox_to_anchor=(0.5, -0.05), ncol=3, numpoints=1);" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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yZ5/hxT177HZz58xwlbl8Gfj4Y1VbcPiwSjObgeHDVW1Bhw6aZIN8EGsGtMFg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\nd1fyO/n666/xl7/8xaYpzR1ERVG3EEIyKifyXs2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EiBGws7PDwYMHsWXLFqZoTREYGGix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\n", "text": [ "" ] } ], "prompt_number": 29 }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "A hidden gene" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Recall that a *hidden gene* corresponds to a latent component (a vector) in the low-dimensional matrices estimated by the NMF. We would like to know, which genes are most strongly associated with a particular hidden gene." ] }, { "cell_type": "heading", "level": 4, "metadata": {}, "source": [ "Nonnegative matrix factorization" ] }, { "cell_type": "code", "collapsed": false, "input": [ "# SNMF/L: for sparse W (where \u2018l\u2019 denotes the sparseness imposed on the left factor)\n", "# SNMF/R: for sparse H (where \u2018r\u2019 denotes the sparseness imposed on the right factor)\n", "rank = 13\n", "snmf = nimfa.Snmf(data.T, rank=rank, seed='random_vcol', version='l', max_iter=200)\n", "snmf_fit = snmf()" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 82 }, { "cell_type": "heading", "level": 4, "metadata": {}, "source": [ "Genes associated with a hidden gene" ] }, { "cell_type": "code", "collapsed": false, "input": [ "W = snmf_fit.fit.basis()\n", "\n", "c = 0\n", "k = 10\n", "\n", "topk = np.argsort(np.asarray(W[:, c]).flatten())[-k:]\n", "val = W[topk, c]\n", "\n", "plt.barh(np.arange(k) + .5, val, align=\"center\")\n", "labels = [id2gene[idx] for idx in topk]\n", "plt.yticks(np.arange(k) + .5, labels)\n", "plt.xlabel(\"Weight\")\n", "plt.ylabel(\"Gene\");" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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O5ZIEI5ogSbDTOpEEx3KLxL8Dfw5cRRkcUyQJRkTEk9pYBsbsAGzr/AsTERGTzFiS4LXA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\nEoyIiMZKEoyIiMb6/85oJNAWPccLAAAAAElFTkSuQmCC\n", "text": [ "" ] } ], "prompt_number": 91 }, { "cell_type": "heading", "level": 4, "metadata": {}, "source": [ "The functional content of a hidden gene" ] }, { "cell_type": "code", "collapsed": false, "input": [ "print('\\n'.join(labels))" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "PARK7\n", "ACACA\n", "KIT\n", "ACACA ACACB\n", "SRC\n", "MAPK1 MAPK3\n", "ANXA1\n", "COL6A1\n", "BCL2\n", "CAV1\n" ] } ], "prompt_number": 92 }, { "cell_type": "markdown", "metadata": {}, "source": [ "Go to the website http://geneontology.org and perform the enrichment analysis. This tells you whether members of the gene set share functional roles in the cell, participate together in biological processes, and if the strength of gene-gene association is stronger than what would be expected if genes were picked randomly. " ] }, { "cell_type": "heading", "level": 4, "metadata": {}, "source": [ "Gene scoring and selection" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "A detailed explanation of gene scoring and selection is provided in\n", "\n", " Kim, Hyunsoo, and Haesun Park. Sparse non-negative matrix factorizations via alternating non-negativity-constrained least squares for microarray data analysis. Bioinformatics 23, 12:1495-1502, 2007." ] }, { "cell_type": "code", "collapsed": false, "input": [ "gs = snmf_fit.fit.score_features()" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 96 }, { "cell_type": "code", "collapsed": false, "input": [ "gss = snmf_fit.fit.select_features()\n", "gene_set = [id2gene[idx] for idx in np.nonzero(gss)[0]]" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 97 }, { "cell_type": "code", "collapsed": false, "input": [ "print('\\n'.join(gene_set))" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "ANXA1\n", "GATA3\n", "FN1\n", "MAPK1 MAPK3\n", "PRKAA1\n", "GSK3A GSK3B\n", "ACACA ACACB\n", "CDH1\n", "PDCD4\n", "STAT5A\n", "HSPA1A\n", "CAV1\n", "COL6A1\n", "AR\n", "IGFBP2\n", "SCD1\n", "CTNNB1\n", "CASP7\n", "PGR\n", "ACACA\n", "BCL2\n", "CLDN7\n", "CCNB1\n", "SERPINE1\n", "KIT\n" ] } ], "prompt_number": 98 }, { "cell_type": "markdown", "metadata": {}, "source": [ "Go to the website http://geneontology.org and perform the enrichment analysis. This tells you whether members of the gene set share functional roles in the cell, participate together in biological processes, and if the strength of gene-gene association is stronger than what would be expected if genes were picked randomly. " ] }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "A hidden patient" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Recall that a *hidden patient* is a latent component (a vector) of the low-dimensional matrices estimated by the NMF. We would like to know, which patient are most strongly associated with a particular hidden patient." ] }, { "cell_type": "heading", "level": 4, "metadata": {}, "source": [ "Nonnegative matrix factorization" ] }, { "cell_type": "code", "collapsed": false, "input": [ "# SNMF/L: for sparse W (where \u2018l\u2019 denotes the sparseness imposed on the left factor)\n", "# SNMF/R: for sparse H (where \u2018r\u2019 denotes the sparseness imposed on the right factor)\n", "rank = 13\n", "snmf = nimfa.Snmf(data.T, rank=rank, seed='random_vcol', version='r', max_iter=200)\n", "snmf_fit = snmf()" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 88 }, { "cell_type": "heading", "level": 4, "metadata": {}, "source": [ "Patients associated with a hidden patient" ] }, { "cell_type": "code", "collapsed": false, "input": [ "H = snmf_fit.fit.coef().T\n", "\n", "c = 0\n", "k = 30\n", "\n", "topk = np.argsort(np.asarray(H[:, c]).flatten())[-k:]\n", "val = H[topk, c]\n", "\n", "plt.barh(np.arange(k) + .5, val, color=\"yellow\", align=\"center\")\n", "labels = [id2donor[idx] for idx in topk]\n", "plt.yticks(np.arange(k) + .5, labels)\n", "plt.xlabel(\"Weight\")\n", "plt.ylabel(\"Donor\");" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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