{ "nbformat": 4, "nbformat_minor": 0, "metadata": { "kernelspec": { "name": "python3", "display_name": "Python 3" }, "colab": { "name": "ACM_BCB_2020_POSTER_KruskalWallisTest_ProteinGeneExpression_vs_ClinicalFeatures.ipynb", "provenance": [], "collapsed_sections": [] } }, "cells": [ { "cell_type": "markdown", "metadata": { "id": "SJcF-vtU7rpj", "colab_type": "text" }, "source": [ "# Poster Notebook: Kruskal Wallis test for associations between Protein/Gene Expression and Clinical Features\n", "```\n", "Created: 09-20-2020\n", "URL: https://github.com/isb-cgc/Community-Notebooks/blob/master/FeaturedNotebooks/ACM_BCB_2020_POSTER_KruskalWallisTest_ProteinGeneExpression_vs_ClinicalFeatures.ipynb\n", "Note: This notebook supports the POSTER : \"Multi-omics Data Integration in the Cloud: Analysis \n", "of Statistically Significant Associations Between Clinical and Molecular Features in Breast Cancer\" \n", "by K. Abdilleh, B. Aguilar, and R. Thomson , presented in the ACM Conference on Bioinformatics, \n", "Computational Biology, and Health Informatics, 2020.\n", "```\n", "***\n", "\n", "This Notebook computes statistically significant associations between Protein/Gene expression and clinical features of Breast cancer, using data available in TCGA BigQuery tables.\n", "\n", "The associations were computed using the Kruskal Wallis (KW) test, implemented as user defined function in Bigquery. Details of the KW test and its implementatin can be found in: https://github.com/jrossthomson/bigquery-utils/tree/master/udfs/statslib\n", "\n", "Violin plots are presented for the clinical features with the most significant associations with protein and gene expression." ] }, { "cell_type": "markdown", "metadata": { "id": "X53EqHduuXEf", "colab_type": "text" }, "source": [ "# Setup" ] }, { "cell_type": "code", "metadata": { "id": "TppLwn_uF4Y1", "colab_type": "code", "colab": { "base_uri": "https://localhost:8080/", "height": 51 }, "outputId": "56c2d50d-09c0-4643-841d-dcfc8ac2d005" }, "source": [ "import sys\n", "#! {sys.executable} -m pip install matplotlib seaborn\n", "#! {sys.executable} -m pip install google-cloud\n", "#! {sys.executable} -m pip install google-cloud\n", "#! {sys.executable} -m pip install google-auth\n", "print({sys.executable})\n", "from platform import python_version\n", "\n", "print(python_version())" ], "execution_count": 7, "outputs": [ { "output_type": "stream", "text": [ "{'/usr/bin/python3'}\n", "3.6.9\n" ], "name": "stdout" } ] }, { "cell_type": "markdown", "metadata": { "id": "_OeROlcGWi5-", "colab_type": "text" }, "source": [ "# Authentication\n" ] }, { "cell_type": "code", "metadata": { "id": "b-debebxHIWw", "colab_type": "code", "colab": {} }, "source": [ "import matplotlib.pyplot as plt\n", "import seaborn as sns\n", "import pandas_gbq\n", "from google.colab import auth\n", "import google.auth\n", "\n", "auth.authenticate_user()\n", "# Explicitly create a credentials object. This allows you to use the same\n", "# credentials for both the BigQuery and BigQuery Storage clients, avoiding\n", "# unnecessary API calls to fetch duplicate authentication tokens.\n", "\n", "credentials, your_project_id = google.auth.default(\n", " scopes=[\"https://www.googleapis.com/auth/cloud-platform\"]\n", ")\n", "\n" ], "execution_count": 8, "outputs": [] }, { "cell_type": "markdown", "metadata": { "id": "uPBtiq2QXAu6", "colab_type": "text" }, "source": [ "# Run Kruskal Wallis test over Proteins Expression, Gene expression, and Clinical data \n", "The code below uses the following three tables available in ISB-CGC :\n", "- Protein expression table: `isb-cgc.TCGA_hg19_data_v0.Protein_Expression`\n", "- Gene Expression table: `isb-cgc.TCGA_hg19_data_v0.RNAseq_Gene_Expression_UNC_RSEM`\n", "- Clinical data: `isb-cgc-bq.supplementary_tables.Abdilleh_etal_ACM_BCB_2020_TCGA_bioclin_v0_Clinical_UNPIVOT`\n", "\n", "The Kruskal Wallis test is implemented in a user defined function called `isb-cgc-bq.functions.kruskal_wallis_current`.\n", "\n", "The code below uses KW to compute significant (p-value < 0.001) associations between Protein expression and Clinical Features in Breat cancer patients. The output (protein names) are then used in a second KW test that identify significant associations between clinical features and both gene and protein expression.\n", "\n", "The final output is a table with protein/genes, clinical features, and p-values of the Kruskal Wallis tests.\n" ] }, { "cell_type": "code", "metadata": { "id": "-0m6TjJtF4Y9", "colab_type": "code", "colab": { "base_uri": "https://localhost:8080/", "height": 419 }, "outputId": "bdc6b2fa-f045-4313-9cf6-57303a722707" }, "source": [ "cancer_type = 'TCGA-BRCA' # https://gdc.cancer.gov/resources-tcga-users/tcga-code-tables/tcga-study-abbreviations\n", "significance_level = '0.001'\n", "project_id=\"\" # write your project id here\n", "sql = '''\n", "with the_proteins as (\n", " SELECT p.project_short_name as study, gene_name as g, c.feature.key as c, `isb-cgc-bq.functions.kruskal_wallis_current`(array_agg((c.feature.value,protein_expression))) as reso\n", " FROM `isb-cgc.TCGA_hg19_data_v0.Protein_Expression` p\n", " JOIN `isb-cgc-bq.supplementary_tables.Abdilleh_etal_ACM_BCB_2020_TCGA_bioclin_v0_Clinical_UNPIVOT` c\n", " ON c.case_barcode = substr(p.sample_barcode,0,12)\n", " WHERE 1=1 AND c.feature.value != \"null\" AND p.project_short_name = \"{0}\"\n", " GROUP BY study, g, c\n", " HAVING reso.DoF > 1 and reso.DoF < 10 #and reso.p <= {1}\n", " ORDER BY study, reso.p, c\n", ") # the_goods\n", ",\n", "the_goods as (\n", " SELECT HGNC_gene_symbol as g, c.feature.key as c, `isb-cgc-bq.functions.kruskal_wallis_current`(array_agg((c.feature.value,normalized_count))) as reso\n", " FROM `isb-cgc.TCGA_hg19_data_v0.RNAseq_Gene_Expression_UNC_RSEM` p\n", " JOIN `isb-cgc-bq.supplementary_tables.Abdilleh_etal_ACM_BCB_2020_TCGA_bioclin_v0_Clinical_UNPIVOT` c\n", " ON c.case_barcode = substr(p.sample_barcode,0,12)\n", " where 1=1\n", " and c.feature.value != \"null\"\n", " and HGNC_gene_symbol in ( SELECT gene_name FROM `isb-cgc.TCGA_hg19_data_v0.Protein_Expression` GROUP BY 1 )\n", " and p.project_short_name = \"{0}\"\n", " GROUP BY g, c\n", " HAVING reso.DoF > 1 and reso.DoF < 10 #and reso.p <= {1}\n", " ORDER BY reso.p \n", ") # the_goods\n", "select pr.g , pr.c, pr.reso.p as p_protein, ge.reso.p as p_gexp\n", "from the_proteins pr\n", "join the_goods ge\n", "on ge.g = pr.g and ge.c = pr.c \n", "where pr.reso.p < {1} and ge.reso.p < {1} \n", "ORDER BY p_protein ASC, p_gexp DESC\n", "'''.format( cancer_type, significance_level )\n", "df = pandas_gbq.read_gbq(sql, project_id=project_id)\n", "df" ], "execution_count": 9, "outputs": [ { "output_type": "execute_result", "data": { "text/html": [ "
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gcp_proteinp_gexp
0CDH1histological_type0.000000e+000.000000e+00
1ESR1histological_type9.214851e-153.888400e-10
2RPS6histological_type5.359047e-135.574927e-06
3SLC1A5histological_type1.292966e-121.439255e-04
4ASNSrace2.190137e-122.731149e-14
...............
71BCL2A1histological_type6.214180e-046.058064e-04
72CDH3histological_type7.010622e-043.432601e-08
73EIF4G1race7.433937e-047.275839e-05
74FN1histological_type9.041138e-048.573417e-06
75STAT3race9.066003e-041.864869e-09
\n", "

76 rows × 4 columns

\n", "
" ], "text/plain": [ " g c p_protein p_gexp\n", "0 CDH1 histological_type 0.000000e+00 0.000000e+00\n", "1 ESR1 histological_type 9.214851e-15 3.888400e-10\n", "2 RPS6 histological_type 5.359047e-13 5.574927e-06\n", "3 SLC1A5 histological_type 1.292966e-12 1.439255e-04\n", "4 ASNS race 2.190137e-12 2.731149e-14\n", ".. ... ... ... ...\n", "71 BCL2A1 histological_type 6.214180e-04 6.058064e-04\n", "72 CDH3 histological_type 7.010622e-04 3.432601e-08\n", "73 EIF4G1 race 7.433937e-04 7.275839e-05\n", "74 FN1 histological_type 9.041138e-04 8.573417e-06\n", "75 STAT3 race 9.066003e-04 1.864869e-09\n", "\n", "[76 rows x 4 columns]" ] }, "metadata": { "tags": [] }, "execution_count": 9 } ] }, { "cell_type": "markdown", "metadata": { "id": "mQsQu8tByVYZ", "colab_type": "text" }, "source": [ "# Plot Protein Expression vs Clinical feature\n", "The code below generates a violin plot using a user defined gene (g) expression and a user defined clinical feature (c).\n" ] }, { "cell_type": "code", "metadata": { "colab_type": "code", "id": "YGd9ifXln29d", "colab": { "base_uri": "https://localhost:8080/", "height": 422 }, "outputId": "f2c57755-bad6-42e4-dcc9-d2a2a52f6253" }, "source": [ "g = \"CDH1\" ## protein name \n", "c = \"histological_type\" # clinical feature\n", "\n", "sql = '''\n", "SELECT c.feature.value factor,protein_expression value\n", "FROM `isb-cgc.TCGA_hg19_data_v0.Protein_Expression` p\n", "JOIN `isb-cgc-bq.supplementary_tables.Abdilleh_etal_ACM_BCB_2020_TCGA_bioclin_v0_Clinical_UNPIVOT` c\n", "ON c.case_barcode = substr(p.sample_barcode,0,12) \n", "where c.feature.value != \"null\" AND p.project_short_name = \"{0}\"\n", "and c.feature.key = \"%s\"\n", "and gene_name = \"%s\"\n", "'''.format(cancer_type)\n", "\n", "p = 0.0000\n", "kw = pandas_gbq.read_gbq(sql%(c,g), project_id=project_id)\n", "order = kw.groupby(['factor']).count().sort_values('value',ascending=False).index\n", "\n", "\n", "axes = sns.catplot(x=\"factor\", y=\"value\", order=order,\n", " data=kw, kind=\"box\", palette=\"Set2\", aspect=2);\n", "axes.fig.suptitle(\"Protein Expression: %s vs %s: p=%f\"%(c,g,p))\n", "sns.violinplot(x=\"factor\", y=\"value\",data=kw, order=order,\n", " scale=\"count\", palette=\"Set2\", aspect=2)\n", "\n", "axes.fig.autofmt_xdate() # rotate values in x axis\n", "\n", "plt.show()\n", "plt.close()\n" ], "execution_count": 10, "outputs": [ { "output_type": "display_data", "data": { "image/png": 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\n", 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" ] }, "metadata": { "tags": [], "needs_background": "light" } } ] }, { "cell_type": "markdown", "metadata": { "id": "JuhbeOU8fcXp", "colab_type": "text" }, "source": [ "# Plot Gene Expression vs Clinical feature\n", "The code below generateS a violin plot using a user defined gene (g) expression and a user defined clinical feature (c)." ] }, { "cell_type": "code", "metadata": { "colab_type": "code", "id": "OkCMwjQUlmw9", "colab": { "base_uri": "https://localhost:8080/", "height": 422 }, "outputId": "ce8cb306-da57-49a9-8b03-c74bb8e06a70" }, "source": [ "g = \"CDH1\" # Gene name\n", "c = \"histological_type\"\n", "\n", "sql = '''\n", "SELECT c.feature.value factor,normalized_count value\n", "FROM `isb-cgc.TCGA_hg19_data_v0.RNAseq_Gene_Expression_UNC_RSEM` p\n", "JOIN `isb-cgc-bq.supplementary_tables.Abdilleh_etal_ACM_BCB_2020_TCGA_bioclin_v0_Clinical_UNPIVOT` c\n", "ON c.case_barcode = substr(p.sample_barcode,0,12) \n", "where c.feature.value != \"null\" AND p.project_short_name = \"{0}\"\n", "and c.feature.key = \"%s\"\n", "and HGNC_gene_symbol in ( SELECT gene_name FROM `isb-cgc.TCGA_hg19_data_v0.Protein_Expression` where gene_name = \"%s\" GROUP BY 1 )\n", "'''.format(cancer_type)\n", "\n", "p = 0.0\n", "kw = pandas_gbq.read_gbq(sql%(c,g), project_id=project_id)\n", "order = kw.groupby(['factor']).count().sort_values('value',ascending=False).index\n", "\n", "axes = sns.catplot(x=\"factor\", y=\"value\", order=order,\n", " data=kw, kind=\"box\", palette=\"Set2\", aspect=2);\n", "axes.fig.suptitle(\"Gene Expression: %s vs %s: p=%f\"%(c,g,p))\n", "sns.violinplot(x=\"factor\", y=\"value\",data=kw, order=order,\n", " scale=\"count\", palette=\"Set2\", aspect=2)\n", "axes.fig.autofmt_xdate() # rotate values in x axis\n", "\n", "plt.show()\n", "plt.close()\n" ], "execution_count": 11, "outputs": [ { "output_type": "display_data", "data": { "image/png": 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\n", 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