R_affy.ipynb

R_affy.ipynb

{
  "cells": [
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "# R affy"
    },
    {
      "metadata": {
        "ExecuteTime": {
          "start_time": "2016-06-03T10:56:50.464473",
          "end_time": "2016-06-03T10:56:51.501356"
        },
        "trusted": true,
        "collapsed": false
      },
      "cell_type": "code",
      "source": "import rpy2.ipython\n%load_ext rpy2.ipython\nimport warnings; warnings.filterwarnings(\"ignore\")",
      "execution_count": 1,
      "outputs": []
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "# R dependencies"
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "**for installation, it was done manually in a seperate terminal window. So, some pain**\n\nInstall/upgrade bioconductor\n\n```R\nsource(\"http://bioconductor.org/biocLite.R\")\nbiocLite()\n```\n\n```R\n## try http:// if https:// URLs are not supported\nsource(\"http://bioconductor.org/biocLite.R\")\nbiocLite(\"affy\")\nbiocLite(\"limma\")\nbiocLite(\"GEOquery\")\nbiocLite(\"oligo\")\nbiocLite(\"hgu133plus2.db\")\nbiocLite(\"annotate\")\nbiocLite(\"topGO\")\nbiocLite(\"genefilter\")\ninstall.packages(\"gplots\")\ninstall.packages(\"ggplot2\")\ninstall.packages(\"wesanderson\")\n```"
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "# check current work directory"
    },
    {
      "metadata": {
        "ExecuteTime": {
          "start_time": "2016-06-03T10:57:23.775112",
          "end_time": "2016-06-03T10:57:23.786421"
        },
        "trusted": true,
        "collapsed": false
      },
      "cell_type": "code",
      "source": "import os.path; os.getcwd()",
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": "'/home/lewis/git/gist/Rnorm'"
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "# Retrieve dataset"
    },
    {
      "metadata": {
        "ExecuteTime": {
          "start_time": "2016-06-03T10:56:52.335606",
          "end_time": "2016-06-03T10:56:52.387288"
        },
        "trusted": true,
        "collapsed": false
      },
      "cell_type": "code",
      "source": "# Assign GSE ascension number for download\n%R gse.asc <- \"GSE33580\"\n%R print(gse.asc)",
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "[1] \"GSE33580\"\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "**GEO Platform (GPL)**\n> These files describe a particular type of microarray. They are annotation files.\n\n**GEO Sample (GSM)**\n> Files that contain all the data from the use of a single chip. For each gene there will be multiple scores including the main one, held in the VALUE column.\n\n**GEO Series (GSE)**\n> Lists of GSM files that together form a single experiment.\n\n**GEO Dataset (GDS)**\n> These are curated files that hold a summarised combination of a GSE file and its GSM files. They contain normalised expression levels for each gene from each sample (i.e. just the VALUE field from the GSM file)."
    },
    {
      "metadata": {
        "ExecuteTime": {
          "start_time": "2016-06-03T10:54:51.744780",
          "end_time": "2016-06-03T10:54:51.762445"
        },
        "trusted": true,
        "collapsed": false
      },
      "cell_type": "code",
      "source": "%%R\nlibrary(GEOquery)",
      "execution_count": 6,
      "outputs": []
    },
    {
      "metadata": {
        "ExecuteTime": {
          "start_time": "2016-06-03T15:55:00.655Z"
        },
        "trusted": true,
        "collapsed": true
      },
      "cell_type": "code",
      "source": "%%R\ngse <- getGEO(gse.asc)",
      "execution_count": null,
      "outputs": []
    },
    {
      "metadata": {
        "ExecuteTime": {
          "start_time": "2016-06-03T15:55:08.255Z"
        },
        "trusted": true,
        "collapsed": true
      },
      "cell_type": "code",
      "source": "%R filePaths = getGEOSuppFiles(gse.asc, baseDir=tmppath)",
      "execution_count": null,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true,
        "collapsed": true
      },
      "cell_type": "code",
      "source": "",
      "execution_count": null,
      "outputs": []
    }
  ],
  "metadata": {
    "kernelspec": {
      "name": "pythonpathkernel",
      "display_name": "pythonpath (python)",
      "language": "python"
    },
    "language_info": {
      "version": "3.5.1",
      "name": "python",
      "pygments_lexer": "ipython3",
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "nbconvert_exporter": "python",
      "file_extension": ".py",
      "mimetype": "text/x-python"
    },
    "toc": {
      "toc_window_display": false,
      "toc_number_sections": true,
      "toc_cell": false,
      "toc_threshold": 6
    },
    "latex_envs": {
      "eqNumInitial": 0,
      "current_citInitial": 1,
      "bibliofile": "biblio.bib",
      "eqLabelWithNumbers": true,
      "cite_by": "apalike"
    },
    "gist": {
      "id": "",
      "data": {
        "description": "R_affy.ipynb",
        "public": true
      }
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}