{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Hands-On Tidyverse - with count data\n", "\n", "## Setup" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Registered S3 methods overwritten by 'ggplot2':\n", " method from \n", " [.quosures rlang\n", " c.quosures rlang\n", " print.quosures rlang\n", "── \u001b[1mAttaching packages\u001b[22m ─────────────────────────────────────── tidyverse 1.2.1 ──\n", "\u001b[32m✔\u001b[39m \u001b[34mggplot2\u001b[39m 3.1.1 \u001b[32m✔\u001b[39m \u001b[34mpurrr \u001b[39m 0.3.2\n", "\u001b[32m✔\u001b[39m \u001b[34mtibble \u001b[39m 2.1.2 \u001b[32m✔\u001b[39m \u001b[34mdplyr \u001b[39m 0.8.1\n", "\u001b[32m✔\u001b[39m \u001b[34mtidyr \u001b[39m 0.8.3 \u001b[32m✔\u001b[39m \u001b[34mstringr\u001b[39m 1.4.0\n", "\u001b[32m✔\u001b[39m \u001b[34mreadr \u001b[39m 1.3.1 \u001b[32m✔\u001b[39m \u001b[34mforcats\u001b[39m 0.4.0\n", "── \u001b[1mConflicts\u001b[22m ────────────────────────────────────────── tidyverse_conflicts() ──\n", "\u001b[31m✖\u001b[39m \u001b[34mdplyr\u001b[39m::\u001b[32mfilter()\u001b[39m masks \u001b[34mstats\u001b[39m::filter()\n", "\u001b[31m✖\u001b[39m \u001b[34mdplyr\u001b[39m::\u001b[32mlag()\u001b[39m masks \u001b[34mstats\u001b[39m::lag()\n", "\n", "Attaching package: ‘foreach’\n", "\n", "The following objects are masked from ‘package:purrr’:\n", "\n", " accumulate, when\n", "\n", "Loading required package: S4Vectors\n", "Loading required package: stats4\n", "Loading required package: BiocGenerics\n", "Loading required package: parallel\n", "\n", "Attaching package: ‘BiocGenerics’\n", "\n", "The following objects are masked from ‘package:parallel’:\n", "\n", " clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,\n", " clusterExport, clusterMap, parApply, parCapply, parLapply,\n", " parLapplyLB, parRapply, parSapply, parSapplyLB\n", "\n", "The following objects are masked from ‘package:dplyr’:\n", "\n", " combine, intersect, setdiff, union\n", "\n", "The following objects are masked from ‘package:stats’:\n", "\n", " IQR, mad, sd, var, xtabs\n", "\n", "The following objects are masked from ‘package:base’:\n", "\n", " anyDuplicated, append, as.data.frame, basename, cbind, colnames,\n", " dirname, do.call, duplicated, eval, evalq, Filter, Find, get, grep,\n", " grepl, intersect, is.unsorted, lapply, Map, mapply, match, mget,\n", " order, paste, pmax, pmax.int, pmin, pmin.int, Position, rank,\n", " rbind, Reduce, rownames, sapply, setdiff, sort, table, tapply,\n", " union, unique, unsplit, which, which.max, which.min\n", "\n", "\n", "Attaching package: ‘S4Vectors’\n", "\n", "The following objects are masked from ‘package:dplyr’:\n", "\n", " first, rename\n", "\n", "The following object is masked from ‘package:tidyr’:\n", "\n", " expand\n", "\n", "The following object is masked from ‘package:base’:\n", "\n", " expand.grid\n", "\n", "Loading required package: IRanges\n", "\n", "Attaching package: ‘IRanges’\n", "\n", "The following objects are masked from ‘package:dplyr’:\n", "\n", " collapse, desc, slice\n", "\n", "The following object is masked from ‘package:purrr’:\n", "\n", " reduce\n", "\n", "Loading required package: GenomicRanges\n", "Loading required package: GenomeInfoDb\n", "Loading required package: SummarizedExperiment\n", "Loading required package: Biobase\n", "Welcome to Bioconductor\n", "\n", " Vignettes contain introductory material; view with\n", " 'browseVignettes()'. To cite Bioconductor, see\n", " 'citation(\"Biobase\")', and for packages 'citation(\"pkgname\")'.\n", "\n", "Loading required package: DelayedArray\n", "Loading required package: matrixStats\n", "\n", "Attaching package: ‘matrixStats’\n", "\n", "The following objects are masked from ‘package:Biobase’:\n", "\n", " anyMissing, rowMedians\n", "\n", "The following object is masked from ‘package:dplyr’:\n", "\n", " count\n", "\n", "Loading required package: BiocParallel\n", "\n", "Attaching package: ‘DelayedArray’\n", "\n", "The following objects are masked from ‘package:matrixStats’:\n", "\n", " colMaxs, colMins, colRanges, rowMaxs, rowMins, rowRanges\n", "\n", "The following object is masked from ‘package:purrr’:\n", "\n", " simplify\n", "\n", "The following objects are masked from ‘package:base’:\n", "\n", " aperm, apply, rowsum\n", "\n", "\n", "Attaching package: ‘limma’\n", "\n", "The following object is masked from ‘package:DESeq2’:\n", "\n", " plotMA\n", "\n", "The following object is masked from ‘package:BiocGenerics’:\n", "\n", " plotMA\n", "\n", "\n", "Attaching package: ‘gridExtra’\n", "\n", "The following object is masked from ‘package:Biobase’:\n", "\n", " combine\n", "\n", "The following object is masked from ‘package:BiocGenerics’:\n", "\n", " combine\n", "\n", "The following object is masked from ‘package:dplyr’:\n", "\n", " combine\n", "\n", "\n", "---------------------\n", "Welcome to dendextend version 1.12.0\n", "Type citation('dendextend') for how to cite the package.\n", "\n", "Type browseVignettes(package = 'dendextend') for the package vignette.\n", "The github page is: https://github.com/talgalili/dendextend/\n", "\n", "Suggestions and bug-reports can be submitted at: https://github.com/talgalili/dendextend/issues\n", "Or contact: \n", "\n", "\tTo suppress this message use: suppressPackageStartupMessages(library(dendextend))\n", "---------------------\n", "\n", "\n", "Attaching package: ‘dendextend’\n", "\n", "The following object is masked from ‘package:stats’:\n", "\n", " cutree\n", "\n", "\n", "Attaching package: ‘plotly’\n", "\n", "The following object is masked from ‘package:IRanges’:\n", "\n", " slice\n", "\n", "The following object is masked from ‘package:S4Vectors’:\n", "\n", " rename\n", "\n", "The following object is masked from ‘package:ggplot2’:\n", "\n", " last_plot\n", "\n", "The following object is masked from ‘package:stats’:\n", "\n", " filter\n", "\n", "The following object is masked from ‘package:graphics’:\n", "\n", " layout\n", "\n" ] } ], "source": [ "# Load required packages\n", "library(tidyverse)\n", "library(foreach)\n", "library(stringr)\n", "library(haven)\n", "\n", "library(DESeq2)\n", "library(tools)\n", "library(limma)\n", "library(qvalue)\n", "\n", "library(ggplot2)\n", "library(RColorBrewer)\n", "library(gridExtra)\n", "library(dendextend)\n", "\n", "library(plotly)" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "# set directories\n", "DATDIR <- \"/data/hts2018_pilot/star_counts\"\n", "CURDIR <- \"/home/jovyan/work/scratch/analysis_output\"\n", "OUTDIR <- file.path(CURDIR, \"out\")\n", "IMGDIR <- file.path(CURDIR, \"img\")\n", "\n", "# Metadata (metadtfile)\n", "METADTFILE <- \"/home/jovyan/work/HTS2018-notebooks/josh/info/2018_pilot_metadata_anon.tsv\"" ] }, { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "## Reading in count data\n", "\n", "The gene counts from the pilot data from the 2018 course are in the directory /data/hts2018_pilot/start_counts.\n", "\n", "Let's have a look at them:" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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    149. \n", "\t
  149. '36_RZ_J_S32_L001_ReadsPerGene.out.tab'
    150. \n", "\t
  150. '36_RZ_J_S32_L002_ReadsPerGene.out.tab'
    151. \n", "\t
  151. '36_RZ_J_S32_L003_ReadsPerGene.out.tab'
    152. \n", "\t
  152. '36_RZ_J_S32_L004_ReadsPerGene.out.tab'
    153. \n", "\t
  153. '38_MA_P_S40_L001_ReadsPerGene.out.tab'
    154. \n", "\t
  154. '38_MA_P_S40_L002_ReadsPerGene.out.tab'
    155. \n", "\t
  155. '38_MA_P_S40_L003_ReadsPerGene.out.tab'
    156. \n", "\t
  156. '38_MA_P_S40_L004_ReadsPerGene.out.tab'
    157. \n", "\t
  157. '38_RZ_P_S48_L001_ReadsPerGene.out.tab'
    158. \n", "\t
  158. '38_RZ_P_S48_L002_ReadsPerGene.out.tab'
    159. \n", "\t
  159. '38_RZ_P_S48_L003_ReadsPerGene.out.tab'
    160. \n", "\t
  160. '38_RZ_P_S48_L004_ReadsPerGene.out.tab'
    161. \n", "\t
  161. '4_MA_P_S35_L001_ReadsPerGene.out.tab'
    162. \n", "\t
  162. '4_MA_P_S35_L002_ReadsPerGene.out.tab'
    163. \n", "\t
  163. '4_MA_P_S35_L003_ReadsPerGene.out.tab'
    164. \n", "\t
  164. '4_MA_P_S35_L004_ReadsPerGene.out.tab'
    165. \n", "\t
  165. '4_RZ_P_S43_L001_ReadsPerGene.out.tab'
    166. \n", "\t
  166. '4_RZ_P_S43_L002_ReadsPerGene.out.tab'
    167. \n", "\t
  167. '4_RZ_P_S43_L003_ReadsPerGene.out.tab'
    168. \n", "\t
  168. '4_RZ_P_S43_L004_ReadsPerGene.out.tab'
    169. \n", "\t
  169. '4_TOT_P_S51_L001_ReadsPerGene.out.tab'
    170. \n", "\t
  170. '4_TOT_P_S51_L002_ReadsPerGene.out.tab'
    171. \n", "\t
  171. '4_TOT_P_S51_L003_ReadsPerGene.out.tab'
    172. \n", "\t
  172. '4_TOT_P_S51_L004_ReadsPerGene.out.tab'
    173. \n", "\t
  173. '40_MA_J_S25_L001_ReadsPerGene.out.tab'
    174. \n", "\t
  174. '40_MA_J_S25_L002_ReadsPerGene.out.tab'
    175. \n", "\t
  175. '40_MA_J_S25_L003_ReadsPerGene.out.tab'
    176. \n", "\t
  176. '40_MA_J_S25_L004_ReadsPerGene.out.tab'
    177. \n", "\t
  177. '40_RZ_J_S33_L001_ReadsPerGene.out.tab'
    178. \n", "\t
  178. '40_RZ_J_S33_L002_ReadsPerGene.out.tab'
    179. \n", "\t
  179. '40_RZ_J_S33_L003_ReadsPerGene.out.tab'
    180. \n", "\t
  180. '40_RZ_J_S33_L004_ReadsPerGene.out.tab'
    181. \n", "\t
  181. '45_MA_P_S41_L001_ReadsPerGene.out.tab'
    182. \n", "\t
  182. '45_MA_P_S41_L002_ReadsPerGene.out.tab'
    183. \n", "\t
  183. '45_MA_P_S41_L003_ReadsPerGene.out.tab'
    184. \n", "\t
  184. '45_MA_P_S41_L004_ReadsPerGene.out.tab'
    185. \n", "\t
  185. '45_RZ_P_S49_L001_ReadsPerGene.out.tab'
    186. \n", "\t
  186. '45_RZ_P_S49_L002_ReadsPerGene.out.tab'
    187. \n", "\t
  187. '45_RZ_P_S49_L003_ReadsPerGene.out.tab'
    188. \n", "\t
  188. '45_RZ_P_S49_L004_ReadsPerGene.out.tab'
    189. \n", "\t
  189. '47_MA_P_S42_L001_ReadsPerGene.out.tab'
    190. \n", "\t
  190. '47_MA_P_S42_L002_ReadsPerGene.out.tab'
    191. \n", "\t
  191. '47_MA_P_S42_L003_ReadsPerGene.out.tab'
    192. \n", "\t
  192. '47_MA_P_S42_L004_ReadsPerGene.out.tab'
    193. \n", "\t
  193. '47_RZ_P_S50_L001_ReadsPerGene.out.tab'
    194. \n", "\t
  194. '47_RZ_P_S50_L002_ReadsPerGene.out.tab'
    195. \n", "\t
  195. '47_RZ_P_S50_L003_ReadsPerGene.out.tab'
    196. \n", "\t
  196. '47_RZ_P_S50_L004_ReadsPerGene.out.tab'
    197. \n", "\t
  197. '9_MA_C_S2_L001_ReadsPerGene.out.tab'
    198. \n", "\t
  198. '9_MA_C_S2_L002_ReadsPerGene.out.tab'
    199. \n", "\t
  199. '9_MA_C_S2_L003_ReadsPerGene.out.tab'
    200. \n", "\t
  200. '9_MA_C_S2_L004_ReadsPerGene.out.tab'
    201. \n", "\t
  201. '9_RZ_C_S10_L001_ReadsPerGene.out.tab'
    202. \n", "\t
  202. '9_RZ_C_S10_L002_ReadsPerGene.out.tab'
    203. \n", "\t
  203. '9_RZ_C_S10_L003_ReadsPerGene.out.tab'
    204. \n", "\t
  204. '9_RZ_C_S10_L004_ReadsPerGene.out.tab'
    205. \n", "
\n" ], "text/latex": [ "\\begin{enumerate*}\n", "\\item '1\\_MA\\_J\\_S18\\_L001\\_ReadsPerGene.out.tab'\n", "\\item '1\\_MA\\_J\\_S18\\_L002\\_ReadsPerGene.out.tab'\n", "\\item '1\\_MA\\_J\\_S18\\_L003\\_ReadsPerGene.out.tab'\n", "\\item '1\\_MA\\_J\\_S18\\_L004\\_ReadsPerGene.out.tab'\n", "\\item '1\\_RZ\\_J\\_S26\\_L001\\_ReadsPerGene.out.tab'\n", "\\item '1\\_RZ\\_J\\_S26\\_L002\\_ReadsPerGene.out.tab'\n", "\\item '1\\_RZ\\_J\\_S26\\_L003\\_ReadsPerGene.out.tab'\n", "\\item '1\\_RZ\\_J\\_S26\\_L004\\_ReadsPerGene.out.tab'\n", "\\item '10\\_MA\\_C\\_S3\\_L001\\_ReadsPerGene.out.tab'\n", "\\item '10\\_MA\\_C\\_S3\\_L002\\_ReadsPerGene.out.tab'\n", "\\item '10\\_MA\\_C\\_S3\\_L003\\_ReadsPerGene.out.tab'\n", "\\item '10\\_MA\\_C\\_S3\\_L004\\_ReadsPerGene.out.tab'\n", "\\item '10\\_RZ\\_C\\_S11\\_L001\\_ReadsPerGene.out.tab'\n", "\\item '10\\_RZ\\_C\\_S11\\_L002\\_ReadsPerGene.out.tab'\n", "\\item '10\\_RZ\\_C\\_S11\\_L003\\_ReadsPerGene.out.tab'\n", "\\item '10\\_RZ\\_C\\_S11\\_L004\\_ReadsPerGene.out.tab'\n", "\\item '11\\_MA\\_J\\_S20\\_L001\\_ReadsPerGene.out.tab'\n", "\\item '11\\_MA\\_J\\_S20\\_L002\\_ReadsPerGene.out.tab'\n", "\\item '11\\_MA\\_J\\_S20\\_L003\\_ReadsPerGene.out.tab'\n", "\\item '11\\_MA\\_J\\_S20\\_L004\\_ReadsPerGene.out.tab'\n", "\\item '11\\_RZ\\_J\\_S28\\_L001\\_ReadsPerGene.out.tab'\n", "\\item '11\\_RZ\\_J\\_S28\\_L002\\_ReadsPerGene.out.tab'\n", "\\item '11\\_RZ\\_J\\_S28\\_L003\\_ReadsPerGene.out.tab'\n", "\\item '11\\_RZ\\_J\\_S28\\_L004\\_ReadsPerGene.out.tab'\n", "\\item '12\\_MA\\_P\\_S36\\_L001\\_ReadsPerGene.out.tab'\n", "\\item '12\\_MA\\_P\\_S36\\_L002\\_ReadsPerGene.out.tab'\n", "\\item '12\\_MA\\_P\\_S36\\_L003\\_ReadsPerGene.out.tab'\n", "\\item '12\\_MA\\_P\\_S36\\_L004\\_ReadsPerGene.out.tab'\n", "\\item '12\\_RZ\\_P\\_S44\\_L001\\_ReadsPerGene.out.tab'\n", "\\item '12\\_RZ\\_P\\_S44\\_L002\\_ReadsPerGene.out.tab'\n", "\\item '12\\_RZ\\_P\\_S44\\_L003\\_ReadsPerGene.out.tab'\n", "\\item '12\\_RZ\\_P\\_S44\\_L004\\_ReadsPerGene.out.tab'\n", "\\item '13\\_MA\\_J\\_S21\\_L001\\_ReadsPerGene.out.tab'\n", "\\item '13\\_MA\\_J\\_S21\\_L002\\_ReadsPerGene.out.tab'\n", "\\item '13\\_MA\\_J\\_S21\\_L003\\_ReadsPerGene.out.tab'\n", "\\item '13\\_MA\\_J\\_S21\\_L004\\_ReadsPerGene.out.tab'\n", "\\item '13\\_RZ\\_J\\_S29\\_L001\\_ReadsPerGene.out.tab'\n", "\\item '13\\_RZ\\_J\\_S29\\_L002\\_ReadsPerGene.out.tab'\n", "\\item '13\\_RZ\\_J\\_S29\\_L003\\_ReadsPerGene.out.tab'\n", "\\item '13\\_RZ\\_J\\_S29\\_L004\\_ReadsPerGene.out.tab'\n", "\\item '14\\_MA\\_C\\_S4\\_L001\\_ReadsPerGene.out.tab'\n", "\\item '14\\_MA\\_C\\_S4\\_L002\\_ReadsPerGene.out.tab'\n", "\\item '14\\_MA\\_C\\_S4\\_L003\\_ReadsPerGene.out.tab'\n", "\\item '14\\_MA\\_C\\_S4\\_L004\\_ReadsPerGene.out.tab'\n", "\\item '14\\_RZ\\_C\\_S12\\_L001\\_ReadsPerGene.out.tab'\n", "\\item '14\\_RZ\\_C\\_S12\\_L002\\_ReadsPerGene.out.tab'\n", "\\item '14\\_RZ\\_C\\_S12\\_L003\\_ReadsPerGene.out.tab'\n", "\\item '14\\_RZ\\_C\\_S12\\_L004\\_ReadsPerGene.out.tab'\n", "\\item '15\\_MA\\_C\\_S5\\_L001\\_ReadsPerGene.out.tab'\n", "\\item '15\\_MA\\_C\\_S5\\_L002\\_ReadsPerGene.out.tab'\n", "\\item '15\\_MA\\_C\\_S5\\_L003\\_ReadsPerGene.out.tab'\n", "\\item '15\\_MA\\_C\\_S5\\_L004\\_ReadsPerGene.out.tab'\n", "\\item '15\\_RZ\\_C\\_S13\\_L001\\_ReadsPerGene.out.tab'\n", "\\item '15\\_RZ\\_C\\_S13\\_L002\\_ReadsPerGene.out.tab'\n", "\\item '15\\_RZ\\_C\\_S13\\_L003\\_ReadsPerGene.out.tab'\n", "\\item '15\\_RZ\\_C\\_S13\\_L004\\_ReadsPerGene.out.tab'\n", "\\item '16\\_MA\\_P\\_S37\\_L001\\_ReadsPerGene.out.tab'\n", "\\item '16\\_MA\\_P\\_S37\\_L002\\_ReadsPerGene.out.tab'\n", "\\item '16\\_MA\\_P\\_S37\\_L003\\_ReadsPerGene.out.tab'\n", "\\item '16\\_MA\\_P\\_S37\\_L004\\_ReadsPerGene.out.tab'\n", "\\item '16\\_RZ\\_P\\_S45\\_L001\\_ReadsPerGene.out.tab'\n", "\\item '16\\_RZ\\_P\\_S45\\_L002\\_ReadsPerGene.out.tab'\n", "\\item '16\\_RZ\\_P\\_S45\\_L003\\_ReadsPerGene.out.tab'\n", "\\item '16\\_RZ\\_P\\_S45\\_L004\\_ReadsPerGene.out.tab'\n", "\\item '2\\_MA\\_C\\_S1\\_L001\\_ReadsPerGene.out.tab'\n", "\\item '2\\_MA\\_C\\_S1\\_L002\\_ReadsPerGene.out.tab'\n", "\\item '2\\_MA\\_C\\_S1\\_L003\\_ReadsPerGene.out.tab'\n", "\\item '2\\_MA\\_C\\_S1\\_L004\\_ReadsPerGene.out.tab'\n", "\\item '2\\_RZ\\_C\\_S9\\_L001\\_ReadsPerGene.out.tab'\n", "\\item '2\\_RZ\\_C\\_S9\\_L002\\_ReadsPerGene.out.tab'\n", "\\item '2\\_RZ\\_C\\_S9\\_L003\\_ReadsPerGene.out.tab'\n", "\\item '2\\_RZ\\_C\\_S9\\_L004\\_ReadsPerGene.out.tab'\n", "\\item '2\\_TOT\\_C\\_S17\\_L001\\_ReadsPerGene.out.tab'\n", "\\item '2\\_TOT\\_C\\_S17\\_L002\\_ReadsPerGene.out.tab'\n", "\\item '2\\_TOT\\_C\\_S17\\_L003\\_ReadsPerGene.out.tab'\n", "\\item '2\\_TOT\\_C\\_S17\\_L004\\_ReadsPerGene.out.tab'\n", "\\item '21\\_MA\\_C\\_S6\\_L001\\_ReadsPerGene.out.tab'\n", "\\item '21\\_MA\\_C\\_S6\\_L002\\_ReadsPerGene.out.tab'\n", "\\item '21\\_MA\\_C\\_S6\\_L003\\_ReadsPerGene.out.tab'\n", "\\item '21\\_MA\\_C\\_S6\\_L004\\_ReadsPerGene.out.tab'\n", "\\item '21\\_RZ\\_C\\_S14\\_L001\\_ReadsPerGene.out.tab'\n", "\\item '21\\_RZ\\_C\\_S14\\_L002\\_ReadsPerGene.out.tab'\n", "\\item '21\\_RZ\\_C\\_S14\\_L003\\_ReadsPerGene.out.tab'\n", "\\item '21\\_RZ\\_C\\_S14\\_L004\\_ReadsPerGene.out.tab'\n", "\\item '22\\_MA\\_C\\_S7\\_L001\\_ReadsPerGene.out.tab'\n", "\\item '22\\_MA\\_C\\_S7\\_L002\\_ReadsPerGene.out.tab'\n", "\\item '22\\_MA\\_C\\_S7\\_L003\\_ReadsPerGene.out.tab'\n", "\\item '22\\_MA\\_C\\_S7\\_L004\\_ReadsPerGene.out.tab'\n", "\\item '22\\_RZ\\_C\\_S15\\_L001\\_ReadsPerGene.out.tab'\n", "\\item '22\\_RZ\\_C\\_S15\\_L002\\_ReadsPerGene.out.tab'\n", "\\item '22\\_RZ\\_C\\_S15\\_L003\\_ReadsPerGene.out.tab'\n", "\\item '22\\_RZ\\_C\\_S15\\_L004\\_ReadsPerGene.out.tab'\n", "\\item '23\\_MA\\_J\\_S22\\_L001\\_ReadsPerGene.out.tab'\n", "\\item '23\\_MA\\_J\\_S22\\_L002\\_ReadsPerGene.out.tab'\n", "\\item '23\\_MA\\_J\\_S22\\_L003\\_ReadsPerGene.out.tab'\n", "\\item 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'35\\_RZ\\_P\\_S47\\_L004\\_ReadsPerGene.out.tab'\n", "\\item '36\\_MA\\_J\\_S24\\_L001\\_ReadsPerGene.out.tab'\n", "\\item '36\\_MA\\_J\\_S24\\_L002\\_ReadsPerGene.out.tab'\n", "\\item '36\\_MA\\_J\\_S24\\_L003\\_ReadsPerGene.out.tab'\n", "\\item '36\\_MA\\_J\\_S24\\_L004\\_ReadsPerGene.out.tab'\n", "\\item '36\\_RZ\\_J\\_S32\\_L001\\_ReadsPerGene.out.tab'\n", "\\item '36\\_RZ\\_J\\_S32\\_L002\\_ReadsPerGene.out.tab'\n", "\\item '36\\_RZ\\_J\\_S32\\_L003\\_ReadsPerGene.out.tab'\n", "\\item '36\\_RZ\\_J\\_S32\\_L004\\_ReadsPerGene.out.tab'\n", "\\item '38\\_MA\\_P\\_S40\\_L001\\_ReadsPerGene.out.tab'\n", "\\item '38\\_MA\\_P\\_S40\\_L002\\_ReadsPerGene.out.tab'\n", "\\item '38\\_MA\\_P\\_S40\\_L003\\_ReadsPerGene.out.tab'\n", "\\item '38\\_MA\\_P\\_S40\\_L004\\_ReadsPerGene.out.tab'\n", "\\item '38\\_RZ\\_P\\_S48\\_L001\\_ReadsPerGene.out.tab'\n", "\\item '38\\_RZ\\_P\\_S48\\_L002\\_ReadsPerGene.out.tab'\n", "\\item '38\\_RZ\\_P\\_S48\\_L003\\_ReadsPerGene.out.tab'\n", "\\item '38\\_RZ\\_P\\_S48\\_L004\\_ReadsPerGene.out.tab'\n", "\\item '4\\_MA\\_P\\_S35\\_L001\\_ReadsPerGene.out.tab'\n", "\\item '4\\_MA\\_P\\_S35\\_L002\\_ReadsPerGene.out.tab'\n", "\\item '4\\_MA\\_P\\_S35\\_L003\\_ReadsPerGene.out.tab'\n", "\\item '4\\_MA\\_P\\_S35\\_L004\\_ReadsPerGene.out.tab'\n", "\\item '4\\_RZ\\_P\\_S43\\_L001\\_ReadsPerGene.out.tab'\n", "\\item '4\\_RZ\\_P\\_S43\\_L002\\_ReadsPerGene.out.tab'\n", "\\item '4\\_RZ\\_P\\_S43\\_L003\\_ReadsPerGene.out.tab'\n", "\\item '4\\_RZ\\_P\\_S43\\_L004\\_ReadsPerGene.out.tab'\n", "\\item '4\\_TOT\\_P\\_S51\\_L001\\_ReadsPerGene.out.tab'\n", "\\item '4\\_TOT\\_P\\_S51\\_L002\\_ReadsPerGene.out.tab'\n", "\\item '4\\_TOT\\_P\\_S51\\_L003\\_ReadsPerGene.out.tab'\n", "\\item '4\\_TOT\\_P\\_S51\\_L004\\_ReadsPerGene.out.tab'\n", "\\item '40\\_MA\\_J\\_S25\\_L001\\_ReadsPerGene.out.tab'\n", "\\item '40\\_MA\\_J\\_S25\\_L002\\_ReadsPerGene.out.tab'\n", "\\item '40\\_MA\\_J\\_S25\\_L003\\_ReadsPerGene.out.tab'\n", "\\item '40\\_MA\\_J\\_S25\\_L004\\_ReadsPerGene.out.tab'\n", "\\item '40\\_RZ\\_J\\_S33\\_L001\\_ReadsPerGene.out.tab'\n", "\\item '40\\_RZ\\_J\\_S33\\_L002\\_ReadsPerGene.out.tab'\n", "\\item '40\\_RZ\\_J\\_S33\\_L003\\_ReadsPerGene.out.tab'\n", "\\item '40\\_RZ\\_J\\_S33\\_L004\\_ReadsPerGene.out.tab'\n", "\\item '45\\_MA\\_P\\_S41\\_L001\\_ReadsPerGene.out.tab'\n", "\\item '45\\_MA\\_P\\_S41\\_L002\\_ReadsPerGene.out.tab'\n", "\\item '45\\_MA\\_P\\_S41\\_L003\\_ReadsPerGene.out.tab'\n", "\\item '45\\_MA\\_P\\_S41\\_L004\\_ReadsPerGene.out.tab'\n", "\\item '45\\_RZ\\_P\\_S49\\_L001\\_ReadsPerGene.out.tab'\n", "\\item '45\\_RZ\\_P\\_S49\\_L002\\_ReadsPerGene.out.tab'\n", "\\item '45\\_RZ\\_P\\_S49\\_L003\\_ReadsPerGene.out.tab'\n", "\\item '45\\_RZ\\_P\\_S49\\_L004\\_ReadsPerGene.out.tab'\n", "\\item '47\\_MA\\_P\\_S42\\_L001\\_ReadsPerGene.out.tab'\n", "\\item '47\\_MA\\_P\\_S42\\_L002\\_ReadsPerGene.out.tab'\n", "\\item '47\\_MA\\_P\\_S42\\_L003\\_ReadsPerGene.out.tab'\n", "\\item '47\\_MA\\_P\\_S42\\_L004\\_ReadsPerGene.out.tab'\n", "\\item '47\\_RZ\\_P\\_S50\\_L001\\_ReadsPerGene.out.tab'\n", "\\item '47\\_RZ\\_P\\_S50\\_L002\\_ReadsPerGene.out.tab'\n", "\\item '47\\_RZ\\_P\\_S50\\_L003\\_ReadsPerGene.out.tab'\n", "\\item '47\\_RZ\\_P\\_S50\\_L004\\_ReadsPerGene.out.tab'\n", "\\item '9\\_MA\\_C\\_S2\\_L001\\_ReadsPerGene.out.tab'\n", "\\item '9\\_MA\\_C\\_S2\\_L002\\_ReadsPerGene.out.tab'\n", "\\item '9\\_MA\\_C\\_S2\\_L003\\_ReadsPerGene.out.tab'\n", "\\item '9\\_MA\\_C\\_S2\\_L004\\_ReadsPerGene.out.tab'\n", "\\item '9\\_RZ\\_C\\_S10\\_L001\\_ReadsPerGene.out.tab'\n", "\\item '9\\_RZ\\_C\\_S10\\_L002\\_ReadsPerGene.out.tab'\n", "\\item '9\\_RZ\\_C\\_S10\\_L003\\_ReadsPerGene.out.tab'\n", "\\item '9\\_RZ\\_C\\_S10\\_L004\\_ReadsPerGene.out.tab'\n", "\\end{enumerate*}\n" ], "text/markdown": [ "1. '1_MA_J_S18_L001_ReadsPerGene.out.tab'\n", "2. '1_MA_J_S18_L002_ReadsPerGene.out.tab'\n", "3. '1_MA_J_S18_L003_ReadsPerGene.out.tab'\n", "4. '1_MA_J_S18_L004_ReadsPerGene.out.tab'\n", "5. '1_RZ_J_S26_L001_ReadsPerGene.out.tab'\n", "6. '1_RZ_J_S26_L002_ReadsPerGene.out.tab'\n", "7. '1_RZ_J_S26_L003_ReadsPerGene.out.tab'\n", "8. '1_RZ_J_S26_L004_ReadsPerGene.out.tab'\n", "9. '10_MA_C_S3_L001_ReadsPerGene.out.tab'\n", "10. '10_MA_C_S3_L002_ReadsPerGene.out.tab'\n", "11. '10_MA_C_S3_L003_ReadsPerGene.out.tab'\n", "12. '10_MA_C_S3_L004_ReadsPerGene.out.tab'\n", "13. '10_RZ_C_S11_L001_ReadsPerGene.out.tab'\n", "14. '10_RZ_C_S11_L002_ReadsPerGene.out.tab'\n", "15. '10_RZ_C_S11_L003_ReadsPerGene.out.tab'\n", "16. '10_RZ_C_S11_L004_ReadsPerGene.out.tab'\n", "17. '11_MA_J_S20_L001_ReadsPerGene.out.tab'\n", "18. '11_MA_J_S20_L002_ReadsPerGene.out.tab'\n", "19. '11_MA_J_S20_L003_ReadsPerGene.out.tab'\n", "20. '11_MA_J_S20_L004_ReadsPerGene.out.tab'\n", "21. '11_RZ_J_S28_L001_ReadsPerGene.out.tab'\n", "22. '11_RZ_J_S28_L002_ReadsPerGene.out.tab'\n", "23. '11_RZ_J_S28_L003_ReadsPerGene.out.tab'\n", "24. '11_RZ_J_S28_L004_ReadsPerGene.out.tab'\n", "25. '12_MA_P_S36_L001_ReadsPerGene.out.tab'\n", "26. '12_MA_P_S36_L002_ReadsPerGene.out.tab'\n", "27. '12_MA_P_S36_L003_ReadsPerGene.out.tab'\n", "28. '12_MA_P_S36_L004_ReadsPerGene.out.tab'\n", "29. '12_RZ_P_S44_L001_ReadsPerGene.out.tab'\n", "30. '12_RZ_P_S44_L002_ReadsPerGene.out.tab'\n", "31. '12_RZ_P_S44_L003_ReadsPerGene.out.tab'\n", "32. '12_RZ_P_S44_L004_ReadsPerGene.out.tab'\n", "33. '13_MA_J_S21_L001_ReadsPerGene.out.tab'\n", "34. '13_MA_J_S21_L002_ReadsPerGene.out.tab'\n", "35. '13_MA_J_S21_L003_ReadsPerGene.out.tab'\n", "36. '13_MA_J_S21_L004_ReadsPerGene.out.tab'\n", "37. '13_RZ_J_S29_L001_ReadsPerGene.out.tab'\n", "38. '13_RZ_J_S29_L002_ReadsPerGene.out.tab'\n", "39. '13_RZ_J_S29_L003_ReadsPerGene.out.tab'\n", "40. '13_RZ_J_S29_L004_ReadsPerGene.out.tab'\n", "41. '14_MA_C_S4_L001_ReadsPerGene.out.tab'\n", "42. '14_MA_C_S4_L002_ReadsPerGene.out.tab'\n", "43. '14_MA_C_S4_L003_ReadsPerGene.out.tab'\n", "44. '14_MA_C_S4_L004_ReadsPerGene.out.tab'\n", "45. '14_RZ_C_S12_L001_ReadsPerGene.out.tab'\n", "46. '14_RZ_C_S12_L002_ReadsPerGene.out.tab'\n", "47. '14_RZ_C_S12_L003_ReadsPerGene.out.tab'\n", "48. '14_RZ_C_S12_L004_ReadsPerGene.out.tab'\n", "49. '15_MA_C_S5_L001_ReadsPerGene.out.tab'\n", "50. '15_MA_C_S5_L002_ReadsPerGene.out.tab'\n", "51. '15_MA_C_S5_L003_ReadsPerGene.out.tab'\n", "52. '15_MA_C_S5_L004_ReadsPerGene.out.tab'\n", "53. '15_RZ_C_S13_L001_ReadsPerGene.out.tab'\n", "54. '15_RZ_C_S13_L002_ReadsPerGene.out.tab'\n", "55. '15_RZ_C_S13_L003_ReadsPerGene.out.tab'\n", "56. '15_RZ_C_S13_L004_ReadsPerGene.out.tab'\n", "57. '16_MA_P_S37_L001_ReadsPerGene.out.tab'\n", "58. '16_MA_P_S37_L002_ReadsPerGene.out.tab'\n", "59. '16_MA_P_S37_L003_ReadsPerGene.out.tab'\n", "60. '16_MA_P_S37_L004_ReadsPerGene.out.tab'\n", "61. '16_RZ_P_S45_L001_ReadsPerGene.out.tab'\n", "62. '16_RZ_P_S45_L002_ReadsPerGene.out.tab'\n", "63. '16_RZ_P_S45_L003_ReadsPerGene.out.tab'\n", "64. '16_RZ_P_S45_L004_ReadsPerGene.out.tab'\n", "65. '2_MA_C_S1_L001_ReadsPerGene.out.tab'\n", "66. '2_MA_C_S1_L002_ReadsPerGene.out.tab'\n", "67. '2_MA_C_S1_L003_ReadsPerGene.out.tab'\n", "68. '2_MA_C_S1_L004_ReadsPerGene.out.tab'\n", "69. '2_RZ_C_S9_L001_ReadsPerGene.out.tab'\n", "70. '2_RZ_C_S9_L002_ReadsPerGene.out.tab'\n", "71. '2_RZ_C_S9_L003_ReadsPerGene.out.tab'\n", "72. '2_RZ_C_S9_L004_ReadsPerGene.out.tab'\n", "73. '2_TOT_C_S17_L001_ReadsPerGene.out.tab'\n", "74. '2_TOT_C_S17_L002_ReadsPerGene.out.tab'\n", "75. '2_TOT_C_S17_L003_ReadsPerGene.out.tab'\n", "76. '2_TOT_C_S17_L004_ReadsPerGene.out.tab'\n", "77. '21_MA_C_S6_L001_ReadsPerGene.out.tab'\n", "78. '21_MA_C_S6_L002_ReadsPerGene.out.tab'\n", "79. '21_MA_C_S6_L003_ReadsPerGene.out.tab'\n", "80. '21_MA_C_S6_L004_ReadsPerGene.out.tab'\n", "81. '21_RZ_C_S14_L001_ReadsPerGene.out.tab'\n", "82. '21_RZ_C_S14_L002_ReadsPerGene.out.tab'\n", "83. '21_RZ_C_S14_L003_ReadsPerGene.out.tab'\n", "84. '21_RZ_C_S14_L004_ReadsPerGene.out.tab'\n", "85. '22_MA_C_S7_L001_ReadsPerGene.out.tab'\n", "86. '22_MA_C_S7_L002_ReadsPerGene.out.tab'\n", "87. '22_MA_C_S7_L003_ReadsPerGene.out.tab'\n", "88. '22_MA_C_S7_L004_ReadsPerGene.out.tab'\n", "89. '22_RZ_C_S15_L001_ReadsPerGene.out.tab'\n", "90. '22_RZ_C_S15_L002_ReadsPerGene.out.tab'\n", "91. '22_RZ_C_S15_L003_ReadsPerGene.out.tab'\n", "92. '22_RZ_C_S15_L004_ReadsPerGene.out.tab'\n", "93. '23_MA_J_S22_L001_ReadsPerGene.out.tab'\n", "94. '23_MA_J_S22_L002_ReadsPerGene.out.tab'\n", "95. '23_MA_J_S22_L003_ReadsPerGene.out.tab'\n", "96. '23_MA_J_S22_L004_ReadsPerGene.out.tab'\n", "97. '23_RZ_J_S30_L001_ReadsPerGene.out.tab'\n", "98. '23_RZ_J_S30_L002_ReadsPerGene.out.tab'\n", "99. '23_RZ_J_S30_L003_ReadsPerGene.out.tab'\n", "100. '23_RZ_J_S30_L004_ReadsPerGene.out.tab'\n", "101. '24_MA_J_S23_L001_ReadsPerGene.out.tab'\n", "102. '24_MA_J_S23_L002_ReadsPerGene.out.tab'\n", "103. '24_MA_J_S23_L003_ReadsPerGene.out.tab'\n", "104. '24_MA_J_S23_L004_ReadsPerGene.out.tab'\n", "105. '24_RZ_J_S31_L001_ReadsPerGene.out.tab'\n", "106. '24_RZ_J_S31_L002_ReadsPerGene.out.tab'\n", "107. '24_RZ_J_S31_L003_ReadsPerGene.out.tab'\n", "108. '24_RZ_J_S31_L004_ReadsPerGene.out.tab'\n", "109. '26_MA_C_S8_L001_ReadsPerGene.out.tab'\n", "110. '26_MA_C_S8_L002_ReadsPerGene.out.tab'\n", "111. '26_MA_C_S8_L003_ReadsPerGene.out.tab'\n", "112. '26_MA_C_S8_L004_ReadsPerGene.out.tab'\n", "113. '26_RZ_C_S16_L001_ReadsPerGene.out.tab'\n", "114. '26_RZ_C_S16_L002_ReadsPerGene.out.tab'\n", "115. '26_RZ_C_S16_L003_ReadsPerGene.out.tab'\n", "116. '26_RZ_C_S16_L004_ReadsPerGene.out.tab'\n", "117. '27_MA_P_S38_L001_ReadsPerGene.out.tab'\n", "118. '27_MA_P_S38_L002_ReadsPerGene.out.tab'\n", "119. '27_MA_P_S38_L003_ReadsPerGene.out.tab'\n", "120. '27_MA_P_S38_L004_ReadsPerGene.out.tab'\n", "121. '27_RZ_P_S46_L001_ReadsPerGene.out.tab'\n", "122. '27_RZ_P_S46_L002_ReadsPerGene.out.tab'\n", "123. '27_RZ_P_S46_L003_ReadsPerGene.out.tab'\n", "124. '27_RZ_P_S46_L004_ReadsPerGene.out.tab'\n", "125. '3_MA_J_S19_L001_ReadsPerGene.out.tab'\n", "126. '3_MA_J_S19_L002_ReadsPerGene.out.tab'\n", "127. '3_MA_J_S19_L003_ReadsPerGene.out.tab'\n", "128. '3_MA_J_S19_L004_ReadsPerGene.out.tab'\n", "129. '3_RZ_J_S27_L001_ReadsPerGene.out.tab'\n", "130. '3_RZ_J_S27_L002_ReadsPerGene.out.tab'\n", "131. '3_RZ_J_S27_L003_ReadsPerGene.out.tab'\n", "132. '3_RZ_J_S27_L004_ReadsPerGene.out.tab'\n", "133. '3_TOT_J_S34_L001_ReadsPerGene.out.tab'\n", "134. '3_TOT_J_S34_L002_ReadsPerGene.out.tab'\n", "135. '3_TOT_J_S34_L003_ReadsPerGene.out.tab'\n", "136. '3_TOT_J_S34_L004_ReadsPerGene.out.tab'\n", "137. '35_MA_P_S39_L001_ReadsPerGene.out.tab'\n", "138. '35_MA_P_S39_L002_ReadsPerGene.out.tab'\n", "139. '35_MA_P_S39_L003_ReadsPerGene.out.tab'\n", "140. '35_MA_P_S39_L004_ReadsPerGene.out.tab'\n", "141. '35_RZ_P_S47_L001_ReadsPerGene.out.tab'\n", "142. '35_RZ_P_S47_L002_ReadsPerGene.out.tab'\n", "143. '35_RZ_P_S47_L003_ReadsPerGene.out.tab'\n", "144. '35_RZ_P_S47_L004_ReadsPerGene.out.tab'\n", "145. '36_MA_J_S24_L001_ReadsPerGene.out.tab'\n", "146. '36_MA_J_S24_L002_ReadsPerGene.out.tab'\n", "147. '36_MA_J_S24_L003_ReadsPerGene.out.tab'\n", "148. '36_MA_J_S24_L004_ReadsPerGene.out.tab'\n", "149. '36_RZ_J_S32_L001_ReadsPerGene.out.tab'\n", "150. '36_RZ_J_S32_L002_ReadsPerGene.out.tab'\n", "151. '36_RZ_J_S32_L003_ReadsPerGene.out.tab'\n", "152. '36_RZ_J_S32_L004_ReadsPerGene.out.tab'\n", "153. '38_MA_P_S40_L001_ReadsPerGene.out.tab'\n", "154. '38_MA_P_S40_L002_ReadsPerGene.out.tab'\n", "155. '38_MA_P_S40_L003_ReadsPerGene.out.tab'\n", "156. '38_MA_P_S40_L004_ReadsPerGene.out.tab'\n", "157. '38_RZ_P_S48_L001_ReadsPerGene.out.tab'\n", "158. '38_RZ_P_S48_L002_ReadsPerGene.out.tab'\n", "159. '38_RZ_P_S48_L003_ReadsPerGene.out.tab'\n", "160. '38_RZ_P_S48_L004_ReadsPerGene.out.tab'\n", "161. '4_MA_P_S35_L001_ReadsPerGene.out.tab'\n", "162. '4_MA_P_S35_L002_ReadsPerGene.out.tab'\n", "163. '4_MA_P_S35_L003_ReadsPerGene.out.tab'\n", "164. '4_MA_P_S35_L004_ReadsPerGene.out.tab'\n", "165. '4_RZ_P_S43_L001_ReadsPerGene.out.tab'\n", "166. '4_RZ_P_S43_L002_ReadsPerGene.out.tab'\n", "167. '4_RZ_P_S43_L003_ReadsPerGene.out.tab'\n", "168. '4_RZ_P_S43_L004_ReadsPerGene.out.tab'\n", "169. '4_TOT_P_S51_L001_ReadsPerGene.out.tab'\n", "170. '4_TOT_P_S51_L002_ReadsPerGene.out.tab'\n", "171. '4_TOT_P_S51_L003_ReadsPerGene.out.tab'\n", "172. '4_TOT_P_S51_L004_ReadsPerGene.out.tab'\n", "173. '40_MA_J_S25_L001_ReadsPerGene.out.tab'\n", "174. '40_MA_J_S25_L002_ReadsPerGene.out.tab'\n", "175. '40_MA_J_S25_L003_ReadsPerGene.out.tab'\n", "176. '40_MA_J_S25_L004_ReadsPerGene.out.tab'\n", "177. '40_RZ_J_S33_L001_ReadsPerGene.out.tab'\n", "178. '40_RZ_J_S33_L002_ReadsPerGene.out.tab'\n", "179. '40_RZ_J_S33_L003_ReadsPerGene.out.tab'\n", "180. '40_RZ_J_S33_L004_ReadsPerGene.out.tab'\n", "181. '45_MA_P_S41_L001_ReadsPerGene.out.tab'\n", "182. '45_MA_P_S41_L002_ReadsPerGene.out.tab'\n", "183. '45_MA_P_S41_L003_ReadsPerGene.out.tab'\n", "184. '45_MA_P_S41_L004_ReadsPerGene.out.tab'\n", "185. '45_RZ_P_S49_L001_ReadsPerGene.out.tab'\n", "186. '45_RZ_P_S49_L002_ReadsPerGene.out.tab'\n", "187. '45_RZ_P_S49_L003_ReadsPerGene.out.tab'\n", "188. '45_RZ_P_S49_L004_ReadsPerGene.out.tab'\n", "189. '47_MA_P_S42_L001_ReadsPerGene.out.tab'\n", "190. '47_MA_P_S42_L002_ReadsPerGene.out.tab'\n", "191. '47_MA_P_S42_L003_ReadsPerGene.out.tab'\n", "192. '47_MA_P_S42_L004_ReadsPerGene.out.tab'\n", "193. '47_RZ_P_S50_L001_ReadsPerGene.out.tab'\n", "194. '47_RZ_P_S50_L002_ReadsPerGene.out.tab'\n", "195. '47_RZ_P_S50_L003_ReadsPerGene.out.tab'\n", "196. '47_RZ_P_S50_L004_ReadsPerGene.out.tab'\n", "197. '9_MA_C_S2_L001_ReadsPerGene.out.tab'\n", "198. '9_MA_C_S2_L002_ReadsPerGene.out.tab'\n", "199. '9_MA_C_S2_L003_ReadsPerGene.out.tab'\n", "200. '9_MA_C_S2_L004_ReadsPerGene.out.tab'\n", "201. 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'9_RZ_C_S10_L004_ReadsPerGene.out.tab'\n", "\n", "\n" ], "text/plain": [ " [1] \"1_MA_J_S18_L001_ReadsPerGene.out.tab\" \n", " [2] \"1_MA_J_S18_L002_ReadsPerGene.out.tab\" \n", " [3] \"1_MA_J_S18_L003_ReadsPerGene.out.tab\" \n", " [4] \"1_MA_J_S18_L004_ReadsPerGene.out.tab\" \n", " [5] \"1_RZ_J_S26_L001_ReadsPerGene.out.tab\" \n", " [6] \"1_RZ_J_S26_L002_ReadsPerGene.out.tab\" \n", " [7] \"1_RZ_J_S26_L003_ReadsPerGene.out.tab\" \n", " [8] \"1_RZ_J_S26_L004_ReadsPerGene.out.tab\" \n", " [9] \"10_MA_C_S3_L001_ReadsPerGene.out.tab\" \n", " [10] \"10_MA_C_S3_L002_ReadsPerGene.out.tab\" \n", " [11] \"10_MA_C_S3_L003_ReadsPerGene.out.tab\" \n", " [12] \"10_MA_C_S3_L004_ReadsPerGene.out.tab\" \n", " [13] \"10_RZ_C_S11_L001_ReadsPerGene.out.tab\"\n", " [14] \"10_RZ_C_S11_L002_ReadsPerGene.out.tab\"\n", " [15] \"10_RZ_C_S11_L003_ReadsPerGene.out.tab\"\n", " [16] \"10_RZ_C_S11_L004_ReadsPerGene.out.tab\"\n", " [17] \"11_MA_J_S20_L001_ReadsPerGene.out.tab\"\n", " [18] 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" [37] \"13_RZ_J_S29_L001_ReadsPerGene.out.tab\"\n", " [38] \"13_RZ_J_S29_L002_ReadsPerGene.out.tab\"\n", " [39] \"13_RZ_J_S29_L003_ReadsPerGene.out.tab\"\n", " [40] \"13_RZ_J_S29_L004_ReadsPerGene.out.tab\"\n", " [41] \"14_MA_C_S4_L001_ReadsPerGene.out.tab\" \n", " [42] \"14_MA_C_S4_L002_ReadsPerGene.out.tab\" \n", " [43] \"14_MA_C_S4_L003_ReadsPerGene.out.tab\" \n", " [44] \"14_MA_C_S4_L004_ReadsPerGene.out.tab\" \n", " [45] \"14_RZ_C_S12_L001_ReadsPerGene.out.tab\"\n", " [46] \"14_RZ_C_S12_L002_ReadsPerGene.out.tab\"\n", " [47] \"14_RZ_C_S12_L003_ReadsPerGene.out.tab\"\n", " [48] \"14_RZ_C_S12_L004_ReadsPerGene.out.tab\"\n", " [49] \"15_MA_C_S5_L001_ReadsPerGene.out.tab\" \n", " [50] \"15_MA_C_S5_L002_ReadsPerGene.out.tab\" \n", " [51] \"15_MA_C_S5_L003_ReadsPerGene.out.tab\" \n", " [52] \"15_MA_C_S5_L004_ReadsPerGene.out.tab\" \n", " [53] \"15_RZ_C_S13_L001_ReadsPerGene.out.tab\"\n", " [54] \"15_RZ_C_S13_L002_ReadsPerGene.out.tab\"\n", " [55] 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" [93] \"23_MA_J_S22_L001_ReadsPerGene.out.tab\"\n", " [94] \"23_MA_J_S22_L002_ReadsPerGene.out.tab\"\n", " [95] \"23_MA_J_S22_L003_ReadsPerGene.out.tab\"\n", " [96] \"23_MA_J_S22_L004_ReadsPerGene.out.tab\"\n", " [97] \"23_RZ_J_S30_L001_ReadsPerGene.out.tab\"\n", " [98] \"23_RZ_J_S30_L002_ReadsPerGene.out.tab\"\n", " [99] \"23_RZ_J_S30_L003_ReadsPerGene.out.tab\"\n", "[100] \"23_RZ_J_S30_L004_ReadsPerGene.out.tab\"\n", "[101] \"24_MA_J_S23_L001_ReadsPerGene.out.tab\"\n", "[102] \"24_MA_J_S23_L002_ReadsPerGene.out.tab\"\n", "[103] \"24_MA_J_S23_L003_ReadsPerGene.out.tab\"\n", "[104] \"24_MA_J_S23_L004_ReadsPerGene.out.tab\"\n", "[105] \"24_RZ_J_S31_L001_ReadsPerGene.out.tab\"\n", "[106] \"24_RZ_J_S31_L002_ReadsPerGene.out.tab\"\n", "[107] \"24_RZ_J_S31_L003_ReadsPerGene.out.tab\"\n", "[108] \"24_RZ_J_S31_L004_ReadsPerGene.out.tab\"\n", "[109] \"26_MA_C_S8_L001_ReadsPerGene.out.tab\" \n", "[110] \"26_MA_C_S8_L002_ReadsPerGene.out.tab\" \n", "[111] \"26_MA_C_S8_L003_ReadsPerGene.out.tab\" \n", "[112] \"26_MA_C_S8_L004_ReadsPerGene.out.tab\" \n", "[113] \"26_RZ_C_S16_L001_ReadsPerGene.out.tab\"\n", "[114] \"26_RZ_C_S16_L002_ReadsPerGene.out.tab\"\n", "[115] \"26_RZ_C_S16_L003_ReadsPerGene.out.tab\"\n", "[116] \"26_RZ_C_S16_L004_ReadsPerGene.out.tab\"\n", "[117] \"27_MA_P_S38_L001_ReadsPerGene.out.tab\"\n", "[118] \"27_MA_P_S38_L002_ReadsPerGene.out.tab\"\n", "[119] \"27_MA_P_S38_L003_ReadsPerGene.out.tab\"\n", "[120] \"27_MA_P_S38_L004_ReadsPerGene.out.tab\"\n", "[121] \"27_RZ_P_S46_L001_ReadsPerGene.out.tab\"\n", "[122] \"27_RZ_P_S46_L002_ReadsPerGene.out.tab\"\n", "[123] \"27_RZ_P_S46_L003_ReadsPerGene.out.tab\"\n", "[124] \"27_RZ_P_S46_L004_ReadsPerGene.out.tab\"\n", "[125] \"3_MA_J_S19_L001_ReadsPerGene.out.tab\" \n", "[126] \"3_MA_J_S19_L002_ReadsPerGene.out.tab\" \n", "[127] \"3_MA_J_S19_L003_ReadsPerGene.out.tab\" \n", "[128] \"3_MA_J_S19_L004_ReadsPerGene.out.tab\" \n", "[129] \"3_RZ_J_S27_L001_ReadsPerGene.out.tab\" \n", "[130] \"3_RZ_J_S27_L002_ReadsPerGene.out.tab\" \n", "[131] \"3_RZ_J_S27_L003_ReadsPerGene.out.tab\" \n", "[132] \"3_RZ_J_S27_L004_ReadsPerGene.out.tab\" \n", "[133] \"3_TOT_J_S34_L001_ReadsPerGene.out.tab\"\n", "[134] \"3_TOT_J_S34_L002_ReadsPerGene.out.tab\"\n", "[135] \"3_TOT_J_S34_L003_ReadsPerGene.out.tab\"\n", "[136] \"3_TOT_J_S34_L004_ReadsPerGene.out.tab\"\n", "[137] \"35_MA_P_S39_L001_ReadsPerGene.out.tab\"\n", "[138] \"35_MA_P_S39_L002_ReadsPerGene.out.tab\"\n", "[139] \"35_MA_P_S39_L003_ReadsPerGene.out.tab\"\n", "[140] \"35_MA_P_S39_L004_ReadsPerGene.out.tab\"\n", "[141] \"35_RZ_P_S47_L001_ReadsPerGene.out.tab\"\n", "[142] \"35_RZ_P_S47_L002_ReadsPerGene.out.tab\"\n", "[143] \"35_RZ_P_S47_L003_ReadsPerGene.out.tab\"\n", "[144] \"35_RZ_P_S47_L004_ReadsPerGene.out.tab\"\n", "[145] \"36_MA_J_S24_L001_ReadsPerGene.out.tab\"\n", "[146] \"36_MA_J_S24_L002_ReadsPerGene.out.tab\"\n", "[147] \"36_MA_J_S24_L003_ReadsPerGene.out.tab\"\n", "[148] \"36_MA_J_S24_L004_ReadsPerGene.out.tab\"\n", "[149] \"36_RZ_J_S32_L001_ReadsPerGene.out.tab\"\n", "[150] \"36_RZ_J_S32_L002_ReadsPerGene.out.tab\"\n", "[151] \"36_RZ_J_S32_L003_ReadsPerGene.out.tab\"\n", "[152] \"36_RZ_J_S32_L004_ReadsPerGene.out.tab\"\n", "[153] \"38_MA_P_S40_L001_ReadsPerGene.out.tab\"\n", "[154] \"38_MA_P_S40_L002_ReadsPerGene.out.tab\"\n", "[155] \"38_MA_P_S40_L003_ReadsPerGene.out.tab\"\n", "[156] \"38_MA_P_S40_L004_ReadsPerGene.out.tab\"\n", "[157] \"38_RZ_P_S48_L001_ReadsPerGene.out.tab\"\n", "[158] \"38_RZ_P_S48_L002_ReadsPerGene.out.tab\"\n", "[159] \"38_RZ_P_S48_L003_ReadsPerGene.out.tab\"\n", "[160] \"38_RZ_P_S48_L004_ReadsPerGene.out.tab\"\n", "[161] \"4_MA_P_S35_L001_ReadsPerGene.out.tab\" \n", "[162] \"4_MA_P_S35_L002_ReadsPerGene.out.tab\" \n", "[163] \"4_MA_P_S35_L003_ReadsPerGene.out.tab\" \n", "[164] \"4_MA_P_S35_L004_ReadsPerGene.out.tab\" \n", "[165] \"4_RZ_P_S43_L001_ReadsPerGene.out.tab\" \n", "[166] \"4_RZ_P_S43_L002_ReadsPerGene.out.tab\" \n", "[167] \"4_RZ_P_S43_L003_ReadsPerGene.out.tab\" \n", "[168] \"4_RZ_P_S43_L004_ReadsPerGene.out.tab\" \n", "[169] \"4_TOT_P_S51_L001_ReadsPerGene.out.tab\"\n", "[170] \"4_TOT_P_S51_L002_ReadsPerGene.out.tab\"\n", "[171] \"4_TOT_P_S51_L003_ReadsPerGene.out.tab\"\n", "[172] \"4_TOT_P_S51_L004_ReadsPerGene.out.tab\"\n", "[173] \"40_MA_J_S25_L001_ReadsPerGene.out.tab\"\n", "[174] \"40_MA_J_S25_L002_ReadsPerGene.out.tab\"\n", "[175] \"40_MA_J_S25_L003_ReadsPerGene.out.tab\"\n", "[176] \"40_MA_J_S25_L004_ReadsPerGene.out.tab\"\n", "[177] \"40_RZ_J_S33_L001_ReadsPerGene.out.tab\"\n", "[178] \"40_RZ_J_S33_L002_ReadsPerGene.out.tab\"\n", "[179] \"40_RZ_J_S33_L003_ReadsPerGene.out.tab\"\n", "[180] \"40_RZ_J_S33_L004_ReadsPerGene.out.tab\"\n", "[181] \"45_MA_P_S41_L001_ReadsPerGene.out.tab\"\n", "[182] \"45_MA_P_S41_L002_ReadsPerGene.out.tab\"\n", "[183] \"45_MA_P_S41_L003_ReadsPerGene.out.tab\"\n", "[184] \"45_MA_P_S41_L004_ReadsPerGene.out.tab\"\n", "[185] \"45_RZ_P_S49_L001_ReadsPerGene.out.tab\"\n", "[186] \"45_RZ_P_S49_L002_ReadsPerGene.out.tab\"\n", "[187] \"45_RZ_P_S49_L003_ReadsPerGene.out.tab\"\n", "[188] \"45_RZ_P_S49_L004_ReadsPerGene.out.tab\"\n", "[189] \"47_MA_P_S42_L001_ReadsPerGene.out.tab\"\n", "[190] \"47_MA_P_S42_L002_ReadsPerGene.out.tab\"\n", "[191] \"47_MA_P_S42_L003_ReadsPerGene.out.tab\"\n", "[192] \"47_MA_P_S42_L004_ReadsPerGene.out.tab\"\n", "[193] \"47_RZ_P_S50_L001_ReadsPerGene.out.tab\"\n", "[194] \"47_RZ_P_S50_L002_ReadsPerGene.out.tab\"\n", "[195] \"47_RZ_P_S50_L003_ReadsPerGene.out.tab\"\n", "[196] \"47_RZ_P_S50_L004_ReadsPerGene.out.tab\"\n", "[197] \"9_MA_C_S2_L001_ReadsPerGene.out.tab\" \n", "[198] \"9_MA_C_S2_L002_ReadsPerGene.out.tab\" \n", "[199] \"9_MA_C_S2_L003_ReadsPerGene.out.tab\" \n", "[200] \"9_MA_C_S2_L004_ReadsPerGene.out.tab\" \n", "[201] \"9_RZ_C_S10_L001_ReadsPerGene.out.tab\" \n", "[202] \"9_RZ_C_S10_L002_ReadsPerGene.out.tab\" \n", "[203] \"9_RZ_C_S10_L003_ReadsPerGene.out.tab\" \n", "[204] \"9_RZ_C_S10_L004_ReadsPerGene.out.tab\" " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "list.files(\"/data/hts2018_pilot/star_counts/\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can also see these in the terminal window (open a terminal window and use the bash command 'ls'). Let's quickly go to the terminal and do this. Also, we can look at the content of the files." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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    \n", "
    11. \n", "
\n" ], "text/latex": [ "\\begin{enumerate}\n", "\\item \\begin{enumerate*}\n", "\\item 'N\\_unmapped'\n", "\\item '2690'\n", "\\item '2690'\n", "\\item '2690'\n", "\\end{enumerate*}\n", "\n", "\\item \\begin{enumerate*}\n", "\\item 'N\\_multimapping'\n", "\\item '66100'\n", "\\item '66100'\n", "\\item '66100'\n", "\\end{enumerate*}\n", "\n", "\\item \\begin{enumerate*}\n", "\\item 'N\\_noFeature'\n", "\\item '10626'\n", "\\item '2238382'\n", "\\item '20347'\n", "\\end{enumerate*}\n", "\n", "\\item \\begin{enumerate*}\n", "\\item 'N\\_ambiguous'\n", "\\item '173170'\n", "\\item '1622'\n", "\\item '647'\n", "\\end{enumerate*}\n", "\n", "\\item \\begin{enumerate*}\n", "\\item 'CNAG\\_04548'\n", "\\item '0'\n", "\\item '0'\n", "\\item '0'\n", "\\end{enumerate*}\n", "\n", "\\item \\begin{enumerate*}\n", "\\item 'CNAG\\_07303'\n", "\\item '0'\n", "\\item '0'\n", "\\item '0'\n", "\\end{enumerate*}\n", "\n", "\\item \\begin{enumerate*}\n", "\\item 'CNAG\\_07304'\n", "\\item '8'\n", "\\item '0'\n", "\\item '8'\n", "\\end{enumerate*}\n", "\n", "\\item \\begin{enumerate*}\n", "\\item 'CNAG\\_00001'\n", "\\item '0'\n", "\\item '0'\n", "\\item '0'\n", "\\end{enumerate*}\n", "\n", "\\item \\begin{enumerate*}\n", "\\item 'CNAG\\_07305'\n", "\\item '0'\n", "\\item '0'\n", "\\item '0'\n", "\\end{enumerate*}\n", "\n", "\\item \\begin{enumerate*}\n", "\\item 'CNAG\\_00002'\n", "\\item '66'\n", "\\item '0'\n", "\\item '66'\n", "\\end{enumerate*}\n", "\n", "\\end{enumerate}\n" ], "text/markdown": [ "1. 1. 'N_unmapped'\n", "2. '2690'\n", "3. '2690'\n", "4. '2690'\n", "\n", "\n", "\n", "2. 1. 'N_multimapping'\n", "2. '66100'\n", "3. '66100'\n", "4. '66100'\n", "\n", "\n", "\n", "3. 1. 'N_noFeature'\n", "2. '10626'\n", "3. '2238382'\n", "4. '20347'\n", "\n", "\n", "\n", "4. 1. 'N_ambiguous'\n", "2. '173170'\n", "3. '1622'\n", "4. '647'\n", "\n", "\n", "\n", "5. 1. 'CNAG_04548'\n", "2. '0'\n", "3. '0'\n", "4. '0'\n", "\n", "\n", "\n", "6. 1. 'CNAG_07303'\n", "2. '0'\n", "3. '0'\n", "4. '0'\n", "\n", "\n", "\n", "7. 1. 'CNAG_07304'\n", "2. '8'\n", "3. '0'\n", "4. '8'\n", "\n", "\n", "\n", "8. 1. 'CNAG_00001'\n", "2. '0'\n", "3. '0'\n", "4. '0'\n", "\n", "\n", "\n", "9. 1. 'CNAG_07305'\n", "2. '0'\n", "3. '0'\n", "4. '0'\n", "\n", "\n", "\n", "10. 1. 'CNAG_00002'\n", "2. '66'\n", "3. '0'\n", "4. '66'\n", "\n", "\n", "\n", "\n", "\n" ], "text/plain": [ "[[1]]\n", "[1] \"N_unmapped\" \"2690\" \"2690\" \"2690\" \n", "\n", "[[2]]\n", "[1] \"N_multimapping\" \"66100\" \"66100\" \"66100\" \n", "\n", "[[3]]\n", "[1] \"N_noFeature\" \"10626\" \"2238382\" \"20347\" \n", "\n", "[[4]]\n", "[1] \"N_ambiguous\" \"173170\" \"1622\" \"647\" \n", "\n", "[[5]]\n", "[1] \"CNAG_04548\" \"0\" \"0\" \"0\" \n", "\n", "[[6]]\n", "[1] \"CNAG_07303\" \"0\" \"0\" \"0\" \n", "\n", "[[7]]\n", "[1] \"CNAG_07304\" \"8\" \"0\" \"8\" \n", "\n", "[[8]]\n", "[1] \"CNAG_00001\" \"0\" \"0\" \"0\" \n", "\n", "[[9]]\n", "[1] \"CNAG_07305\" \"0\" \"0\" \"0\" \n", "\n", "[[10]]\n", "[1] \"CNAG_00002\" \"66\" \"0\" \"66\" \n" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Save the names in variable\n", "stardirs <- list.files(DATDIR)\n", "\n", "# Look at the beginning of the first file from R\n", "cmdstr <- paste(\"head\", file.path(DATDIR, stardirs[1]))\n", "cmdout <- system(cmdstr, intern = TRUE)\n", "str_split(cmdout, pattern = \"\\t\")\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "There are several things to note:\n", " * There are four columns. We only want the first (gene name) and the fourth (count).\n", " * There are no headers.\n", " * This is a tab-delimited file (we can't see this, but what we can see is that it is not a csv)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Exercise:\n", " 1. How many files are in the directory?\n", " 2. Print the first 10 filenames\n", " 3. Use the command read_tsv to read in the second file and save it in a tibble called \"sample_2\". Use the note above to pass the correct options to read_tsv.\n" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Parsed with column specification:\n", "cols(\n", " X1 = \u001b[31mcol_character()\u001b[39m,\n", " X2 = \u001b[32mcol_double()\u001b[39m,\n", " X3 = \u001b[32mcol_double()\u001b[39m,\n", " X4 = \u001b[32mcol_double()\u001b[39m\n", ")\n" ] } ], "source": [ "sample_file <- paste0(DATDIR, \"/\", stardirs[2])\n", "sample_2 <- read_tsv(sample_file, col_names = FALSE)" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\t\n", "\t\n", "\n", "\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\n", "
A tibble: 6 × 4
X1X2X3X4
<chr><dbl><dbl><dbl>
N_unmapped 2684 2684 2684
N_multimapping 65234 6523465234
N_noFeature 10340220418720004
N_ambiguous 169504 1523 652
CNAG_04548 0 0 0
CNAG_07303 0 0 0
\n" ], "text/latex": [ "A tibble: 6 × 4\n", "\\begin{tabular}{r|llll}\n", " X1 & X2 & X3 & X4\\\\\n", " & & & \\\\\n", "\\hline\n", "\t N\\_unmapped & 2684 & 2684 & 2684\\\\\n", "\t N\\_multimapping & 65234 & 65234 & 65234\\\\\n", "\t N\\_noFeature & 10340 & 2204187 & 20004\\\\\n", "\t N\\_ambiguous & 169504 & 1523 & 652\\\\\n", "\t CNAG\\_04548 & 0 & 0 & 0\\\\\n", "\t CNAG\\_07303 & 0 & 0 & 0\\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", "A tibble: 6 × 4\n", "\n", "| X1 <chr> | X2 <dbl> | X3 <dbl> | X4 <dbl> |\n", "|---|---|---|---|\n", "| N_unmapped | 2684 | 2684 | 2684 |\n", "| N_multimapping | 65234 | 65234 | 65234 |\n", "| N_noFeature | 10340 | 2204187 | 20004 |\n", "| N_ambiguous | 169504 | 1523 | 652 |\n", "| CNAG_04548 | 0 | 0 | 0 |\n", "| CNAG_07303 | 0 | 0 | 0 |\n", "\n" ], "text/plain": [ " X1 X2 X3 X4 \n", "1 N_unmapped 2684 2684 2684\n", "2 N_multimapping 65234 65234 65234\n", "3 N_noFeature 10340 2204187 20004\n", "4 N_ambiguous 169504 1523 652\n", "5 CNAG_04548 0 0 0\n", "6 CNAG_07303 0 0 0" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sample_2 %>% head\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Our goal is to read in all of these files and collect the first and fourth columns into one large tibble. Let's first do this for two files.\n", "\n", "Exercise:\n", "\n", " 1. Read in the first two files, one into a tibble called df1, the other into a tibble called df2.\n", " 2. Remove the middle two columns using dplyr, and rename the remaining two columns 'gene' and the name of the count file.\n", " 3. Join the two tibbles together using 'gene' as the key." ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "# Fancy way to read in columns 1 and 4 only\n", "\n", "coltypes<- \"?--i\"\n", "\n", "sample_file <- paste0(DATDIR, \"/\", stardirs[1])\n", "df1 <- readr::read_tsv(sample_file, col_types = coltypes, col_names = c(\"gene\", stardirs[1]))\n", "\n", "sample_file <- paste0(DATDIR, \"/\", stardirs[2])\n", "df2 <- readr::read_tsv(sample_file, col_types = coltypes, col_names = c(\"gene\", stardirs[2]))" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\t\n", "\t\n", "\n", "\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\n", "
A tibble: 6 × 2
gene1_MA_J_S18_L001_ReadsPerGene.out.tab
<chr><int>
N_unmapped 2690
N_multimapping66100
N_noFeature 20347
N_ambiguous 647
CNAG_04548 0
CNAG_07303 0
\n" ], "text/latex": [ "A tibble: 6 × 2\n", "\\begin{tabular}{r|ll}\n", " gene & 1\\_MA\\_J\\_S18\\_L001\\_ReadsPerGene.out.tab\\\\\n", " & \\\\\n", "\\hline\n", "\t N\\_unmapped & 2690\\\\\n", "\t N\\_multimapping & 66100\\\\\n", "\t N\\_noFeature & 20347\\\\\n", "\t N\\_ambiguous & 647\\\\\n", "\t CNAG\\_04548 & 0\\\\\n", "\t CNAG\\_07303 & 0\\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", "A tibble: 6 × 2\n", "\n", "| gene <chr> | 1_MA_J_S18_L001_ReadsPerGene.out.tab <int> |\n", "|---|---|\n", "| N_unmapped | 2690 |\n", "| N_multimapping | 66100 |\n", "| N_noFeature | 20347 |\n", "| N_ambiguous | 647 |\n", "| CNAG_04548 | 0 |\n", "| CNAG_07303 | 0 |\n", "\n" ], "text/plain": [ " gene 1_MA_J_S18_L001_ReadsPerGene.out.tab\n", "1 N_unmapped 2690 \n", "2 N_multimapping 66100 \n", "3 N_noFeature 20347 \n", "4 N_ambiguous 647 \n", "5 CNAG_04548 0 \n", "6 CNAG_07303 0 " ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "\n", "\n", "\n", "\t\n", "\t\n", "\n", "\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\n", "
A tibble: 6 × 2
gene1_MA_J_S18_L002_ReadsPerGene.out.tab
<chr><int>
N_unmapped 2684
N_multimapping65234
N_noFeature 20004
N_ambiguous 652
CNAG_04548 0
CNAG_07303 0
\n" ], "text/latex": [ "A tibble: 6 × 2\n", "\\begin{tabular}{r|ll}\n", " gene & 1\\_MA\\_J\\_S18\\_L002\\_ReadsPerGene.out.tab\\\\\n", " & \\\\\n", "\\hline\n", "\t N\\_unmapped & 2684\\\\\n", "\t N\\_multimapping & 65234\\\\\n", "\t N\\_noFeature & 20004\\\\\n", "\t N\\_ambiguous & 652\\\\\n", "\t CNAG\\_04548 & 0\\\\\n", "\t CNAG\\_07303 & 0\\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", "A tibble: 6 × 2\n", "\n", "| gene <chr> | 1_MA_J_S18_L002_ReadsPerGene.out.tab <int> |\n", "|---|---|\n", "| N_unmapped | 2684 |\n", "| N_multimapping | 65234 |\n", "| N_noFeature | 20004 |\n", "| N_ambiguous | 652 |\n", "| CNAG_04548 | 0 |\n", "| CNAG_07303 | 0 |\n", "\n" ], "text/plain": [ " gene 1_MA_J_S18_L002_ReadsPerGene.out.tab\n", "1 N_unmapped 2684 \n", "2 N_multimapping 65234 \n", "3 N_noFeature 20004 \n", "4 N_ambiguous 652 \n", "5 CNAG_04548 0 \n", "6 CNAG_07303 0 " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "df1 %>% head\n", "df2 %>% head" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\t\n", "\t\n", "\n", "\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\n", "
A tibble: 6 × 3
gene1_MA_J_S18_L001_ReadsPerGene.out.tab1_MA_J_S18_L002_ReadsPerGene.out.tab
<chr><int><int>
N_unmapped 2690 2684
N_multimapping6610065234
N_noFeature 2034720004
N_ambiguous 647 652
CNAG_04548 0 0
CNAG_07303 0 0
\n" ], "text/latex": [ "A tibble: 6 × 3\n", "\\begin{tabular}{r|lll}\n", " gene & 1\\_MA\\_J\\_S18\\_L001\\_ReadsPerGene.out.tab & 1\\_MA\\_J\\_S18\\_L002\\_ReadsPerGene.out.tab\\\\\n", " & & \\\\\n", "\\hline\n", "\t N\\_unmapped & 2690 & 2684\\\\\n", "\t N\\_multimapping & 66100 & 65234\\\\\n", "\t N\\_noFeature & 20347 & 20004\\\\\n", "\t N\\_ambiguous & 647 & 652\\\\\n", "\t CNAG\\_04548 & 0 & 0\\\\\n", "\t CNAG\\_07303 & 0 & 0\\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", "A tibble: 6 × 3\n", "\n", "| gene <chr> | 1_MA_J_S18_L001_ReadsPerGene.out.tab <int> | 1_MA_J_S18_L002_ReadsPerGene.out.tab <int> |\n", "|---|---|---|\n", "| N_unmapped | 2690 | 2684 |\n", "| N_multimapping | 66100 | 65234 |\n", "| N_noFeature | 20347 | 20004 |\n", "| N_ambiguous | 647 | 652 |\n", "| CNAG_04548 | 0 | 0 |\n", "| CNAG_07303 | 0 | 0 |\n", "\n" ], "text/plain": [ " gene 1_MA_J_S18_L001_ReadsPerGene.out.tab\n", "1 N_unmapped 2690 \n", "2 N_multimapping 66100 \n", "3 N_noFeature 20347 \n", "4 N_ambiguous 647 \n", "5 CNAG_04548 0 \n", "6 CNAG_07303 0 \n", " 1_MA_J_S18_L002_ReadsPerGene.out.tab\n", "1 2684 \n", "2 65234 \n", "3 20004 \n", "4 652 \n", "5 0 \n", "6 0 " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "full_join(df1, df2, by = \"gene\") %>% head" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Of course, we don't want to do this manually for every file. We'll use the `foreach` package in R to iterate over the files. This will require defining some of the steps above as functions, so first let's review what a function is." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Functions\n", "\n", "Functions are simply objects that *do* something. In the functional programming paradigm, functions should be self-contained, in that they receive as inputs all the variables they need and do not modify anything else. They 'return' an output.\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Example\n", "\n", "*Good*" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "myfunction_add <- function(a,b){\n", " a + b # In R, the last statement is what is returned\n", "}" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "text/html": [ "3" ], "text/latex": [ "3" ], "text/markdown": [ "3" ], "text/plain": [ "[1] 3" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "myfunction_add(1,2)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "*Bad*" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [], "source": [ "a <- 1\n", "b <- 2\n", "\n", "myfunction_add <- function(){\n", " a + b # We are using values from the 'global environment' instead of passing them in\n", " \n", "}" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "text/html": [ "3" ], "text/latex": [ "3" ], "text/markdown": [ "3" ], "text/plain": [ "[1] 3" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "myfunction_add()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Exercise:\n", "\n", " 1. Write a function to multiply two numbers and return the result.\n", " 2. Write a function to join two dataframes" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [], "source": [ "mycombine <- function(df1, df2) {\n", " # Combine two data frames by gene names\n", " #\n", " # Args:\n", " # df1 (Dataframe): the first count data\n", " # df2 (Dataframe): the second count data\n", " #\n", " # Returns:\n", " # (Dataframe) The combined data frame of df1 and df2\n", " full_join(df1, df2, by = \"gene\")\n", "}\n", "\n", "myfile <- function(filedir, filename) {\n", " # Get the absolute paths of a file\n", " #\n", " # Args:\n", " # filedir (Character): the directory of the folder\n", " # filename (Character): the filename\n", " #\n", " # Returns:\n", " # (Character) the directory of the input file\n", " file.path(filedir, filename)\n", "}\n", "\n" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Warning message:\n", "“rename_() is deprecated. \n", "Please use rename() instead\n", "\n", "The 'programming' vignette or the tidyeval book can help you\n", "to program with rename() : https://tidyeval.tidyverse.org\n", "\u001b[90mThis warning is displayed once per session.\u001b[39m”" ] } ], "source": [ "coltypes<- \"?--i\"\n", "\n", "out <- foreach(stardir = stardirs, .combine = mycombine) %do% {\n", " \n", " # get a directory of each count file\n", " cntfile <- myfile(DATDIR, stardir)\n", " \n", " # read in the count file\n", " readr::read_tsv(cntfile, col_names = FALSE, col_types = coltypes) %>%\n", " dplyr::rename_(.dots=setNames(names(.), c(\"gene\",stardir)))\n", " #dplyr::rename(\"gene\" = \"X1\", `stardir` = \"X4\")\n", "}" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\t\n", "\t\n", "\n", "\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\n", "
A tibble: 6 × 205
gene1_MA_J_S18_L001_ReadsPerGene.out.tab1_MA_J_S18_L002_ReadsPerGene.out.tab1_MA_J_S18_L003_ReadsPerGene.out.tab1_MA_J_S18_L004_ReadsPerGene.out.tab1_RZ_J_S26_L001_ReadsPerGene.out.tab1_RZ_J_S26_L002_ReadsPerGene.out.tab1_RZ_J_S26_L003_ReadsPerGene.out.tab1_RZ_J_S26_L004_ReadsPerGene.out.tab10_MA_C_S3_L001_ReadsPerGene.out.tab⋯47_RZ_P_S50_L003_ReadsPerGene.out.tab47_RZ_P_S50_L004_ReadsPerGene.out.tab9_MA_C_S2_L001_ReadsPerGene.out.tab9_MA_C_S2_L002_ReadsPerGene.out.tab9_MA_C_S2_L003_ReadsPerGene.out.tab9_MA_C_S2_L004_ReadsPerGene.out.tab9_RZ_C_S10_L001_ReadsPerGene.out.tab9_RZ_C_S10_L002_ReadsPerGene.out.tab9_RZ_C_S10_L003_ReadsPerGene.out.tab9_RZ_C_S10_L004_ReadsPerGene.out.tab
<chr><int><int><int><int><int><int><int><int><int>⋯<int><int><int><int><int><int><int><int><int><int>
N_unmapped 2690 2684 2672 2585 7218 7022 7355 707638278⋯ 10036 9962 2245 2291 2276 2105 3386 3612 3283 4853
N_multimapping6610065234665386506639584838807940133839549064124⋯ 536339 52936376258744907637075176149388149618150874156664
N_noFeature 2034720004205492050576814675565477774977371228540⋯1055322104717127956276382837228459503625504801510186525524
N_ambiguous 647 652 697 616 1431 1337 1425 1322 147⋯ 1260 1236 903 848 943 838 1354 1333 1359 1357
CNAG_04548 0 0 0 1 0 0 0 1 0⋯ 0 0 0 0 0 0 1 0 0 0
CNAG_07303 0 0 0 0 0 0 0 0 0⋯ 0 0 0 0 0 0 0 0 0 0
\n" ], "text/latex": [ "A tibble: 6 × 205\n", "\\begin{tabular}{r|lllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllll}\n", " gene & 1\\_MA\\_J\\_S18\\_L001\\_ReadsPerGene.out.tab & 1\\_MA\\_J\\_S18\\_L002\\_ReadsPerGene.out.tab & 1\\_MA\\_J\\_S18\\_L003\\_ReadsPerGene.out.tab & 1\\_MA\\_J\\_S18\\_L004\\_ReadsPerGene.out.tab & 1\\_RZ\\_J\\_S26\\_L001\\_ReadsPerGene.out.tab & 1\\_RZ\\_J\\_S26\\_L002\\_ReadsPerGene.out.tab & 1\\_RZ\\_J\\_S26\\_L003\\_ReadsPerGene.out.tab & 1\\_RZ\\_J\\_S26\\_L004\\_ReadsPerGene.out.tab & 10\\_MA\\_C\\_S3\\_L001\\_ReadsPerGene.out.tab & 10\\_MA\\_C\\_S3\\_L002\\_ReadsPerGene.out.tab & 10\\_MA\\_C\\_S3\\_L003\\_ReadsPerGene.out.tab & 10\\_MA\\_C\\_S3\\_L004\\_ReadsPerGene.out.tab & 10\\_RZ\\_C\\_S11\\_L001\\_ReadsPerGene.out.tab & 10\\_RZ\\_C\\_S11\\_L002\\_ReadsPerGene.out.tab & 10\\_RZ\\_C\\_S11\\_L003\\_ReadsPerGene.out.tab & 10\\_RZ\\_C\\_S11\\_L004\\_ReadsPerGene.out.tab & 11\\_MA\\_J\\_S20\\_L001\\_ReadsPerGene.out.tab & 11\\_MA\\_J\\_S20\\_L002\\_ReadsPerGene.out.tab & 11\\_MA\\_J\\_S20\\_L003\\_ReadsPerGene.out.tab & 11\\_MA\\_J\\_S20\\_L004\\_ReadsPerGene.out.tab & 11\\_RZ\\_J\\_S28\\_L001\\_ReadsPerGene.out.tab & 11\\_RZ\\_J\\_S28\\_L002\\_ReadsPerGene.out.tab & 11\\_RZ\\_J\\_S28\\_L003\\_ReadsPerGene.out.tab & 11\\_RZ\\_J\\_S28\\_L004\\_ReadsPerGene.out.tab & 12\\_MA\\_P\\_S36\\_L001\\_ReadsPerGene.out.tab & 12\\_MA\\_P\\_S36\\_L002\\_ReadsPerGene.out.tab & 12\\_MA\\_P\\_S36\\_L003\\_ReadsPerGene.out.tab & 12\\_MA\\_P\\_S36\\_L004\\_ReadsPerGene.out.tab & 12\\_RZ\\_P\\_S44\\_L001\\_ReadsPerGene.out.tab & 12\\_RZ\\_P\\_S44\\_L002\\_ReadsPerGene.out.tab & 12\\_RZ\\_P\\_S44\\_L003\\_ReadsPerGene.out.tab & 12\\_RZ\\_P\\_S44\\_L004\\_ReadsPerGene.out.tab & 13\\_MA\\_J\\_S21\\_L001\\_ReadsPerGene.out.tab & 13\\_MA\\_J\\_S21\\_L002\\_ReadsPerGene.out.tab & 13\\_MA\\_J\\_S21\\_L003\\_ReadsPerGene.out.tab & 13\\_MA\\_J\\_S21\\_L004\\_ReadsPerGene.out.tab & 13\\_RZ\\_J\\_S29\\_L001\\_ReadsPerGene.out.tab & 13\\_RZ\\_J\\_S29\\_L002\\_ReadsPerGene.out.tab & 13\\_RZ\\_J\\_S29\\_L003\\_ReadsPerGene.out.tab & 13\\_RZ\\_J\\_S29\\_L004\\_ReadsPerGene.out.tab & 14\\_MA\\_C\\_S4\\_L001\\_ReadsPerGene.out.tab & 14\\_MA\\_C\\_S4\\_L002\\_ReadsPerGene.out.tab & 14\\_MA\\_C\\_S4\\_L003\\_ReadsPerGene.out.tab & 14\\_MA\\_C\\_S4\\_L004\\_ReadsPerGene.out.tab & 14\\_RZ\\_C\\_S12\\_L001\\_ReadsPerGene.out.tab & 14\\_RZ\\_C\\_S12\\_L002\\_ReadsPerGene.out.tab & 14\\_RZ\\_C\\_S12\\_L003\\_ReadsPerGene.out.tab & 14\\_RZ\\_C\\_S12\\_L004\\_ReadsPerGene.out.tab & 15\\_MA\\_C\\_S5\\_L001\\_ReadsPerGene.out.tab & 15\\_MA\\_C\\_S5\\_L002\\_ReadsPerGene.out.tab & 15\\_MA\\_C\\_S5\\_L003\\_ReadsPerGene.out.tab & 15\\_MA\\_C\\_S5\\_L004\\_ReadsPerGene.out.tab & 15\\_RZ\\_C\\_S13\\_L001\\_ReadsPerGene.out.tab & 15\\_RZ\\_C\\_S13\\_L002\\_ReadsPerGene.out.tab & 15\\_RZ\\_C\\_S13\\_L003\\_ReadsPerGene.out.tab & 15\\_RZ\\_C\\_S13\\_L004\\_ReadsPerGene.out.tab & 16\\_MA\\_P\\_S37\\_L001\\_ReadsPerGene.out.tab & 16\\_MA\\_P\\_S37\\_L002\\_ReadsPerGene.out.tab & 16\\_MA\\_P\\_S37\\_L003\\_ReadsPerGene.out.tab & 16\\_MA\\_P\\_S37\\_L004\\_ReadsPerGene.out.tab & 16\\_RZ\\_P\\_S45\\_L001\\_ReadsPerGene.out.tab & 16\\_RZ\\_P\\_S45\\_L002\\_ReadsPerGene.out.tab & 16\\_RZ\\_P\\_S45\\_L003\\_ReadsPerGene.out.tab & 16\\_RZ\\_P\\_S45\\_L004\\_ReadsPerGene.out.tab & 2\\_MA\\_C\\_S1\\_L001\\_ReadsPerGene.out.tab & 2\\_MA\\_C\\_S1\\_L002\\_ReadsPerGene.out.tab & 2\\_MA\\_C\\_S1\\_L003\\_ReadsPerGene.out.tab & 2\\_MA\\_C\\_S1\\_L004\\_ReadsPerGene.out.tab & 2\\_RZ\\_C\\_S9\\_L001\\_ReadsPerGene.out.tab & 2\\_RZ\\_C\\_S9\\_L002\\_ReadsPerGene.out.tab & 2\\_RZ\\_C\\_S9\\_L003\\_ReadsPerGene.out.tab & 2\\_RZ\\_C\\_S9\\_L004\\_ReadsPerGene.out.tab & 2\\_TOT\\_C\\_S17\\_L001\\_ReadsPerGene.out.tab & 2\\_TOT\\_C\\_S17\\_L002\\_ReadsPerGene.out.tab & 2\\_TOT\\_C\\_S17\\_L003\\_ReadsPerGene.out.tab & 2\\_TOT\\_C\\_S17\\_L004\\_ReadsPerGene.out.tab & 21\\_MA\\_C\\_S6\\_L001\\_ReadsPerGene.out.tab & 21\\_MA\\_C\\_S6\\_L002\\_ReadsPerGene.out.tab & 21\\_MA\\_C\\_S6\\_L003\\_ReadsPerGene.out.tab & 21\\_MA\\_C\\_S6\\_L004\\_ReadsPerGene.out.tab & 21\\_RZ\\_C\\_S14\\_L001\\_ReadsPerGene.out.tab & 21\\_RZ\\_C\\_S14\\_L002\\_ReadsPerGene.out.tab & 21\\_RZ\\_C\\_S14\\_L003\\_ReadsPerGene.out.tab & 21\\_RZ\\_C\\_S14\\_L004\\_ReadsPerGene.out.tab & 22\\_MA\\_C\\_S7\\_L001\\_ReadsPerGene.out.tab & 22\\_MA\\_C\\_S7\\_L002\\_ReadsPerGene.out.tab & 22\\_MA\\_C\\_S7\\_L003\\_ReadsPerGene.out.tab & 22\\_MA\\_C\\_S7\\_L004\\_ReadsPerGene.out.tab & 22\\_RZ\\_C\\_S15\\_L001\\_ReadsPerGene.out.tab & 22\\_RZ\\_C\\_S15\\_L002\\_ReadsPerGene.out.tab & 22\\_RZ\\_C\\_S15\\_L003\\_ReadsPerGene.out.tab & 22\\_RZ\\_C\\_S15\\_L004\\_ReadsPerGene.out.tab & 23\\_MA\\_J\\_S22\\_L001\\_ReadsPerGene.out.tab & 23\\_MA\\_J\\_S22\\_L002\\_ReadsPerGene.out.tab & 23\\_MA\\_J\\_S22\\_L003\\_ReadsPerGene.out.tab & 23\\_MA\\_J\\_S22\\_L004\\_ReadsPerGene.out.tab & 23\\_RZ\\_J\\_S30\\_L001\\_ReadsPerGene.out.tab & 23\\_RZ\\_J\\_S30\\_L002\\_ReadsPerGene.out.tab & 23\\_RZ\\_J\\_S30\\_L003\\_ReadsPerGene.out.tab & 23\\_RZ\\_J\\_S30\\_L004\\_ReadsPerGene.out.tab & 24\\_MA\\_J\\_S23\\_L001\\_ReadsPerGene.out.tab & 24\\_MA\\_J\\_S23\\_L002\\_ReadsPerGene.out.tab & 24\\_MA\\_J\\_S23\\_L003\\_ReadsPerGene.out.tab & 24\\_MA\\_J\\_S23\\_L004\\_ReadsPerGene.out.tab & 24\\_RZ\\_J\\_S31\\_L001\\_ReadsPerGene.out.tab & 24\\_RZ\\_J\\_S31\\_L002\\_ReadsPerGene.out.tab & 24\\_RZ\\_J\\_S31\\_L003\\_ReadsPerGene.out.tab & 24\\_RZ\\_J\\_S31\\_L004\\_ReadsPerGene.out.tab & 26\\_MA\\_C\\_S8\\_L001\\_ReadsPerGene.out.tab & 26\\_MA\\_C\\_S8\\_L002\\_ReadsPerGene.out.tab & 26\\_MA\\_C\\_S8\\_L003\\_ReadsPerGene.out.tab & 26\\_MA\\_C\\_S8\\_L004\\_ReadsPerGene.out.tab & 26\\_RZ\\_C\\_S16\\_L001\\_ReadsPerGene.out.tab & 26\\_RZ\\_C\\_S16\\_L002\\_ReadsPerGene.out.tab & 26\\_RZ\\_C\\_S16\\_L003\\_ReadsPerGene.out.tab & 26\\_RZ\\_C\\_S16\\_L004\\_ReadsPerGene.out.tab & 27\\_MA\\_P\\_S38\\_L001\\_ReadsPerGene.out.tab & 27\\_MA\\_P\\_S38\\_L002\\_ReadsPerGene.out.tab & 27\\_MA\\_P\\_S38\\_L003\\_ReadsPerGene.out.tab & 27\\_MA\\_P\\_S38\\_L004\\_ReadsPerGene.out.tab & 27\\_RZ\\_P\\_S46\\_L001\\_ReadsPerGene.out.tab & 27\\_RZ\\_P\\_S46\\_L002\\_ReadsPerGene.out.tab & 27\\_RZ\\_P\\_S46\\_L003\\_ReadsPerGene.out.tab & 27\\_RZ\\_P\\_S46\\_L004\\_ReadsPerGene.out.tab & 3\\_MA\\_J\\_S19\\_L001\\_ReadsPerGene.out.tab & 3\\_MA\\_J\\_S19\\_L002\\_ReadsPerGene.out.tab & 3\\_MA\\_J\\_S19\\_L003\\_ReadsPerGene.out.tab & 3\\_MA\\_J\\_S19\\_L004\\_ReadsPerGene.out.tab & 3\\_RZ\\_J\\_S27\\_L001\\_ReadsPerGene.out.tab & 3\\_RZ\\_J\\_S27\\_L002\\_ReadsPerGene.out.tab & 3\\_RZ\\_J\\_S27\\_L003\\_ReadsPerGene.out.tab & 3\\_RZ\\_J\\_S27\\_L004\\_ReadsPerGene.out.tab & 3\\_TOT\\_J\\_S34\\_L001\\_ReadsPerGene.out.tab & 3\\_TOT\\_J\\_S34\\_L002\\_ReadsPerGene.out.tab & 3\\_TOT\\_J\\_S34\\_L003\\_ReadsPerGene.out.tab & 3\\_TOT\\_J\\_S34\\_L004\\_ReadsPerGene.out.tab & 35\\_MA\\_P\\_S39\\_L001\\_ReadsPerGene.out.tab & 35\\_MA\\_P\\_S39\\_L002\\_ReadsPerGene.out.tab & 35\\_MA\\_P\\_S39\\_L003\\_ReadsPerGene.out.tab & 35\\_MA\\_P\\_S39\\_L004\\_ReadsPerGene.out.tab & 35\\_RZ\\_P\\_S47\\_L001\\_ReadsPerGene.out.tab & 35\\_RZ\\_P\\_S47\\_L002\\_ReadsPerGene.out.tab & 35\\_RZ\\_P\\_S47\\_L003\\_ReadsPerGene.out.tab & 35\\_RZ\\_P\\_S47\\_L004\\_ReadsPerGene.out.tab & 36\\_MA\\_J\\_S24\\_L001\\_ReadsPerGene.out.tab & 36\\_MA\\_J\\_S24\\_L002\\_ReadsPerGene.out.tab & 36\\_MA\\_J\\_S24\\_L003\\_ReadsPerGene.out.tab & 36\\_MA\\_J\\_S24\\_L004\\_ReadsPerGene.out.tab & 36\\_RZ\\_J\\_S32\\_L001\\_ReadsPerGene.out.tab & 36\\_RZ\\_J\\_S32\\_L002\\_ReadsPerGene.out.tab & 36\\_RZ\\_J\\_S32\\_L003\\_ReadsPerGene.out.tab & 36\\_RZ\\_J\\_S32\\_L004\\_ReadsPerGene.out.tab & 38\\_MA\\_P\\_S40\\_L001\\_ReadsPerGene.out.tab & 38\\_MA\\_P\\_S40\\_L002\\_ReadsPerGene.out.tab & 38\\_MA\\_P\\_S40\\_L003\\_ReadsPerGene.out.tab & 38\\_MA\\_P\\_S40\\_L004\\_ReadsPerGene.out.tab & 38\\_RZ\\_P\\_S48\\_L001\\_ReadsPerGene.out.tab & 38\\_RZ\\_P\\_S48\\_L002\\_ReadsPerGene.out.tab & 38\\_RZ\\_P\\_S48\\_L003\\_ReadsPerGene.out.tab & 38\\_RZ\\_P\\_S48\\_L004\\_ReadsPerGene.out.tab & 4\\_MA\\_P\\_S35\\_L001\\_ReadsPerGene.out.tab & 4\\_MA\\_P\\_S35\\_L002\\_ReadsPerGene.out.tab & 4\\_MA\\_P\\_S35\\_L003\\_ReadsPerGene.out.tab & 4\\_MA\\_P\\_S35\\_L004\\_ReadsPerGene.out.tab & 4\\_RZ\\_P\\_S43\\_L001\\_ReadsPerGene.out.tab & 4\\_RZ\\_P\\_S43\\_L002\\_ReadsPerGene.out.tab & 4\\_RZ\\_P\\_S43\\_L003\\_ReadsPerGene.out.tab & 4\\_RZ\\_P\\_S43\\_L004\\_ReadsPerGene.out.tab & 4\\_TOT\\_P\\_S51\\_L001\\_ReadsPerGene.out.tab & 4\\_TOT\\_P\\_S51\\_L002\\_ReadsPerGene.out.tab & 4\\_TOT\\_P\\_S51\\_L003\\_ReadsPerGene.out.tab & 4\\_TOT\\_P\\_S51\\_L004\\_ReadsPerGene.out.tab & 40\\_MA\\_J\\_S25\\_L001\\_ReadsPerGene.out.tab & 40\\_MA\\_J\\_S25\\_L002\\_ReadsPerGene.out.tab & 40\\_MA\\_J\\_S25\\_L003\\_ReadsPerGene.out.tab & 40\\_MA\\_J\\_S25\\_L004\\_ReadsPerGene.out.tab & 40\\_RZ\\_J\\_S33\\_L001\\_ReadsPerGene.out.tab & 40\\_RZ\\_J\\_S33\\_L002\\_ReadsPerGene.out.tab & 40\\_RZ\\_J\\_S33\\_L003\\_ReadsPerGene.out.tab & 40\\_RZ\\_J\\_S33\\_L004\\_ReadsPerGene.out.tab & 45\\_MA\\_P\\_S41\\_L001\\_ReadsPerGene.out.tab & 45\\_MA\\_P\\_S41\\_L002\\_ReadsPerGene.out.tab & 45\\_MA\\_P\\_S41\\_L003\\_ReadsPerGene.out.tab & 45\\_MA\\_P\\_S41\\_L004\\_ReadsPerGene.out.tab & 45\\_RZ\\_P\\_S49\\_L001\\_ReadsPerGene.out.tab & 45\\_RZ\\_P\\_S49\\_L002\\_ReadsPerGene.out.tab & 45\\_RZ\\_P\\_S49\\_L003\\_ReadsPerGene.out.tab & 45\\_RZ\\_P\\_S49\\_L004\\_ReadsPerGene.out.tab & 47\\_MA\\_P\\_S42\\_L001\\_ReadsPerGene.out.tab & 47\\_MA\\_P\\_S42\\_L002\\_ReadsPerGene.out.tab & 47\\_MA\\_P\\_S42\\_L003\\_ReadsPerGene.out.tab & 47\\_MA\\_P\\_S42\\_L004\\_ReadsPerGene.out.tab & 47\\_RZ\\_P\\_S50\\_L001\\_ReadsPerGene.out.tab & 47\\_RZ\\_P\\_S50\\_L002\\_ReadsPerGene.out.tab & 47\\_RZ\\_P\\_S50\\_L003\\_ReadsPerGene.out.tab & 47\\_RZ\\_P\\_S50\\_L004\\_ReadsPerGene.out.tab & 9\\_MA\\_C\\_S2\\_L001\\_ReadsPerGene.out.tab & 9\\_MA\\_C\\_S2\\_L002\\_ReadsPerGene.out.tab & 9\\_MA\\_C\\_S2\\_L003\\_ReadsPerGene.out.tab & 9\\_MA\\_C\\_S2\\_L004\\_ReadsPerGene.out.tab & 9\\_RZ\\_C\\_S10\\_L001\\_ReadsPerGene.out.tab & 9\\_RZ\\_C\\_S10\\_L002\\_ReadsPerGene.out.tab & 9\\_RZ\\_C\\_S10\\_L003\\_ReadsPerGene.out.tab & 9\\_RZ\\_C\\_S10\\_L004\\_ReadsPerGene.out.tab\\\\\n", " & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & \\\\\n", "\\hline\n", "\t N\\_unmapped & 2690 & 2684 & 2672 & 2585 & 7218 & 7022 & 7355 & 7076 & 38278 & 38180 & 39830 & 36152 & 29051 & 28498 & 29272 & 28454 & 16661 & 16002 & 16883 & 14378 & 111436 & 109267 & 113414 & 111747 & 25260 & 25586 & 26118 & 26753 & 33635 & 33057 & 34575 & 33574 & 15943 & 15846 & 16345 & 13522 & 4819 & 4866 & 4911 & 4731 & 3174 & 3423 & 3277 & 2793 & 4305 & 4152 & 4150 & 4653 & 4057 & 4170 & 4098 & 3643 & 6750 & 6475 & 6283 & 7437 & 5925 & 5568 & 6001 & 6080 & 4679 & 4525 & 4723 & 4816 & 4503 & 4534 & 4663 & 4407 & 13455 & 12808 & 12056 & 14591 & 2090 & 2344 & 2321 & 1718 & 2937 & 3056 & 2853 & 2624 & 10561 & 10067 & 10038 & 11719 & 3189 & 3289 & 3228 & 2776 & 11081 & 11148 & 9978 & 14667 & 1608 & 1661 & 1635 & 1444 & 4139 & 4177 & 4368 & 4248 & 1717 & 1813 & 1849 & 1500 & 2662 & 2592 & 1194 & 1150 & 4002 & 4309 & 4131 & 3409 & 19999 & 19038 & 18723 & 21521 & 3374 & 3366 & 3560 & 3284 & 7706 & 7412 & 8073 & 7902 & 1438 & 1598 & 1465 & 1998 & 3261 & 3220 & 3373 & 3458 & 2279 & 2605 & 2328 & 2381 & 30923 & 29760 & 31539 & 31087 & 11456 & 11318 & 11765 & 11762 & 1538 & 1639 & 1626 & 1410 & 1006 & 1006 & 1107 & 973 & 12097 & 11518 & 12033 & 12089 & 7541 & 7006 & 7516 & 7567 & 8279 & 8308 & 8298 & 8685 & 4993 & 4639 & 5067 & 4856 & 2122 & 2104 & 2111 & 2686 & 2761 & 2812 & 2808 & 2317 & 1134 & 1108 & 1199 & 1040 & 3642 & 3493 & 3572 & 3682 & 7130 & 6903 & 7386 & 7252 & 6541 & 6398 & 6822 & 6734 & 9864 & 9338 & 10036 & 9962 & 2245 & 2291 & 2276 & 2105 & 3386 & 3612 & 3283 & 4853\\\\\n", "\t N\\_multimapping & 66100 & 65234 & 66538 & 65066 & 395848 & 388079 & 401338 & 395490 & 64124 & 62999 & 64876 & 64189 & 63441 & 62031 & 64264 & 64135 & 38568 & 37731 & 38678 & 38700 & 194151 & 190997 & 196432 & 195439 & 92923 & 91814 & 93406 & 94385 & 330393 & 324708 & 334513 & 331710 & 32343 & 31647 & 33091 & 32141 & 261889 & 256455 & 265177 & 261879 & 68765 & 67923 & 70091 & 67429 & 107979 & 106555 & 111006 & 108387 & 117640 & 115460 & 119296 & 116531 & 119221 & 117692 & 120577 & 119224 & 97120 & 93941 & 97410 & 96164 & 275941 & 270306 & 278401 & 276886 & 88417 & 87315 & 90292 & 88646 & 192231 & 188517 & 194169 & 192884 & 1199220 & 1168755 & 1202680 & 1187923 & 80629 & 78767 & 81509 & 79877 & 124056 & 122381 & 127120 & 124162 & 111368 & 109308 & 113007 & 110196 & 165434 & 165797 & 166474 & 171414 & 55184 & 54361 & 56400 & 54216 & 258819 & 254252 & 264445 & 259785 & 51672 & 51506 & 52642 & 50464 & 105530 & 104003 & 105267 & 104137 & 187574 & 182514 & 189153 & 184099 & 221240 & 214768 & 225029 & 217369 & 60186 & 58433 & 60529 & 58704 & 493270 & 480776 & 497663 & 490320 & 39097 & 38612 & 39371 & 40049 & 186710 & 182886 & 188860 & 186838 & 2478334 & 2439361 & 2488112 & 2486314 & 150158 & 147408 & 152255 & 150625 & 487248 & 479023 & 495855 & 490441 & 65502 & 63860 & 65472 & 64099 & 128968 & 125356 & 129156 & 127728 & 89557 & 86727 & 89566 & 88453 & 395309 & 387687 & 400785 & 397047 & 114304 & 111064 & 114557 & 113144 & 1089673 & 1066109 & 1097336 & 1087066 & 1419948 & 1383032 & 1414948 & 1396867 & 72234 & 71039 & 73313 & 68715 & 104401 & 102689 & 105886 & 103948 & 78670 & 76516 & 79110 & 78150 & 444307 & 436571 & 448627 & 445049 & 106272 & 103233 & 107856 & 105301 & 528563 & 514265 & 536339 & 529363 & 76258 & 74490 & 76370 & 75176 & 149388 & 149618 & 150874 & 156664\\\\\n", "\t N\\_noFeature & 20347 & 20004 & 20549 & 20505 & 768146 & 755654 & 777749 & 773712 & 28540 & 28321 & 28968 & 29142 & 345554 & 340522 & 350657 & 350896 & 16831 & 16599 & 17101 & 17270 & 488851 & 482235 & 496302 & 494215 & 26903 & 26724 & 27298 & 27818 & 446859 & 440203 & 455335 & 453828 & 20402 & 19902 & 20885 & 20587 & 510401 & 498126 & 517314 & 512278 & 34335 & 33833 & 35198 & 34464 & 349356 & 343142 & 354918 & 352897 & 60568 & 59706 & 61217 & 59905 & 377641 & 371603 & 382575 & 380492 & 31192 & 30693 & 31664 & 31631 & 409641 & 402322 & 416546 & 414796 & 34916 & 34327 & 35686 & 35535 & 442513 & 436060 & 448033 & 447981 & 88840 & 87478 & 89996 & 88736 & 34160 & 33828 & 34875 & 34184 & 396304 & 389697 & 402911 & 399490 & 35745 & 35100 & 36488 & 35998 & 657881 & 648907 & 664259 & 667515 & 23467 & 23044 & 23848 & 23836 & 573543 & 563250 & 583384 & 578328 & 21692 & 21697 & 22260 & 21494 & 437811 & 429827 & 445188 & 440770 & 31121 & 29910 & 31271 & 30722 & 832099 & 812546 & 843994 & 836824 & 13870 & 13508 & 13863 & 14067 & 478939 & 469160 & 486180 & 482572 & 13229 & 13268 & 13639 & 13919 & 322891 & 317017 & 329119 & 326427 & 210205 & 209522 & 213671 & 215063 & 20307 & 18952 & 19854 & 20019 & 790790 & 779587 & 808081 & 801076 & 19846 & 19503 & 20375 & 20209 & 783680 & 770517 & 795163 & 791830 & 27953 & 27674 & 28812 & 28280 & 874255 & 859873 & 890420 & 885005 & 25539 & 24828 & 25637 & 25495 & 197311 & 193984 & 201826 & 200115 & 112322 & 110188 & 114814 & 113224 & 33660 & 32706 & 34133 & 33202 & 631757 & 617216 & 641085 & 635424 & 34780 & 34009 & 35183 & 34997 & 1001488 & 985895 & 1016783 & 1008052 & 35016 & 33787 & 35697 & 35112 & 1037590 & 1013016 & 1055322 & 1047171 & 27956 & 27638 & 28372 & 28459 & 503625 & 504801 & 510186 & 525524\\\\\n", "\t N\\_ambiguous & 647 & 652 & 697 & 616 & 1431 & 1337 & 1425 & 1322 & 147 & 134 & 135 & 122 & 608 & 652 & 633 & 642 & 79 & 66 & 69 & 75 & 613 & 608 & 652 & 639 & 99 & 96 & 90 & 88 & 483 & 496 & 516 & 513 & 74 & 77 & 85 & 75 & 1112 & 1112 & 1185 & 1141 & 1032 & 887 & 914 & 913 & 1018 & 929 & 1033 & 1028 & 1142 & 1016 & 1168 & 1074 & 1234 & 1153 & 1153 & 1120 & 816 & 767 & 865 & 734 & 549 & 568 & 585 & 579 & 860 & 805 & 868 & 805 & 1306 & 1305 & 1350 & 1330 & 264 & 245 & 302 & 300 & 910 & 890 & 951 & 903 & 1140 & 1099 & 1227 & 1139 & 1179 & 1101 & 1153 & 1115 & 1918 & 1820 & 1917 & 1917 & 528 & 579 & 565 & 587 & 1245 & 1313 & 1264 & 1173 & 473 & 453 & 472 & 466 & 1085 & 1090 & 1237 & 1206 & 1057 & 954 & 1030 & 992 & 2335 & 2207 & 2276 & 2303 & 549 & 538 & 589 & 483 & 494 & 412 & 483 & 458 & 443 & 385 & 439 & 407 & 669 & 648 & 712 & 681 & 501 & 494 & 527 & 497 & 321 & 355 & 291 & 255 & 1163 & 1088 & 1207 & 1118 & 578 & 522 & 630 & 526 & 1732 & 1690 & 1733 & 1674 & 691 & 661 & 761 & 674 & 795 & 821 & 819 & 792 & 1123 & 1097 & 1127 & 1020 & 424 & 447 & 432 & 468 & 214 & 213 & 214 & 223 & 769 & 682 & 712 & 648 & 1542 & 1484 & 1571 & 1637 & 710 & 621 & 732 & 645 & 1255 & 1152 & 1191 & 1157 & 1057 & 980 & 1079 & 992 & 1127 & 1158 & 1260 & 1236 & 903 & 848 & 943 & 838 & 1354 & 1333 & 1359 & 1357\\\\\n", "\t CNAG\\_04548 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 4 & 1 & 1 & 4 & 1 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 1 & 0 & 1 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 1 & 0 & 1 & 1 & 1 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0\\\\\n", "\t CNAG\\_07303 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0\\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", "A tibble: 6 × 205\n", "\n", "| gene <chr> | 1_MA_J_S18_L001_ReadsPerGene.out.tab <int> | 1_MA_J_S18_L002_ReadsPerGene.out.tab <int> | 1_MA_J_S18_L003_ReadsPerGene.out.tab <int> | 1_MA_J_S18_L004_ReadsPerGene.out.tab <int> | 1_RZ_J_S26_L001_ReadsPerGene.out.tab <int> | 1_RZ_J_S26_L002_ReadsPerGene.out.tab <int> | 1_RZ_J_S26_L003_ReadsPerGene.out.tab <int> | 1_RZ_J_S26_L004_ReadsPerGene.out.tab <int> | 10_MA_C_S3_L001_ReadsPerGene.out.tab <int> | ⋯ ⋯ | 47_RZ_P_S50_L003_ReadsPerGene.out.tab <int> | 47_RZ_P_S50_L004_ReadsPerGene.out.tab <int> | 9_MA_C_S2_L001_ReadsPerGene.out.tab <int> | 9_MA_C_S2_L002_ReadsPerGene.out.tab <int> | 9_MA_C_S2_L003_ReadsPerGene.out.tab <int> | 9_MA_C_S2_L004_ReadsPerGene.out.tab <int> | 9_RZ_C_S10_L001_ReadsPerGene.out.tab <int> | 9_RZ_C_S10_L002_ReadsPerGene.out.tab <int> | 9_RZ_C_S10_L003_ReadsPerGene.out.tab <int> | 9_RZ_C_S10_L004_ReadsPerGene.out.tab <int> |\n", "|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n", "| N_unmapped | 2690 | 2684 | 2672 | 2585 | 7218 | 7022 | 7355 | 7076 | 38278 | ⋯ | 10036 | 9962 | 2245 | 2291 | 2276 | 2105 | 3386 | 3612 | 3283 | 4853 |\n", "| N_multimapping | 66100 | 65234 | 66538 | 65066 | 395848 | 388079 | 401338 | 395490 | 64124 | ⋯ | 536339 | 529363 | 76258 | 74490 | 76370 | 75176 | 149388 | 149618 | 150874 | 156664 |\n", "| N_noFeature | 20347 | 20004 | 20549 | 20505 | 768146 | 755654 | 777749 | 773712 | 28540 | ⋯ | 1055322 | 1047171 | 27956 | 27638 | 28372 | 28459 | 503625 | 504801 | 510186 | 525524 |\n", "| N_ambiguous | 647 | 652 | 697 | 616 | 1431 | 1337 | 1425 | 1322 | 147 | ⋯ | 1260 | 1236 | 903 | 848 | 943 | 838 | 1354 | 1333 | 1359 | 1357 |\n", "| CNAG_04548 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | ⋯ | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 |\n", "| CNAG_07303 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ⋯ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |\n", "\n" ], "text/plain": [ " gene 1_MA_J_S18_L001_ReadsPerGene.out.tab\n", "1 N_unmapped 2690 \n", "2 N_multimapping 66100 \n", "3 N_noFeature 20347 \n", "4 N_ambiguous 647 \n", "5 CNAG_04548 0 \n", "6 CNAG_07303 0 \n", " 1_MA_J_S18_L002_ReadsPerGene.out.tab 1_MA_J_S18_L003_ReadsPerGene.out.tab\n", "1 2684 2672 \n", "2 65234 66538 \n", "3 20004 20549 \n", "4 652 697 \n", "5 0 0 \n", "6 0 0 \n", " 1_MA_J_S18_L004_ReadsPerGene.out.tab 1_RZ_J_S26_L001_ReadsPerGene.out.tab\n", "1 2585 7218 \n", "2 65066 395848 \n", "3 20505 768146 \n", "4 616 1431 \n", "5 1 0 \n", "6 0 0 \n", " 1_RZ_J_S26_L002_ReadsPerGene.out.tab 1_RZ_J_S26_L003_ReadsPerGene.out.tab\n", "1 7022 7355 \n", "2 388079 401338 \n", "3 755654 777749 \n", "4 1337 1425 \n", "5 0 0 \n", "6 0 0 \n", " 1_RZ_J_S26_L004_ReadsPerGene.out.tab 10_MA_C_S3_L001_ReadsPerGene.out.tab ⋯\n", "1 7076 38278 ⋯\n", "2 395490 64124 ⋯\n", "3 773712 28540 ⋯\n", "4 1322 147 ⋯\n", "5 1 0 ⋯\n", "6 0 0 ⋯\n", " 47_RZ_P_S50_L003_ReadsPerGene.out.tab 47_RZ_P_S50_L004_ReadsPerGene.out.tab\n", "1 10036 9962 \n", "2 536339 529363 \n", "3 1055322 1047171 \n", "4 1260 1236 \n", "5 0 0 \n", "6 0 0 \n", " 9_MA_C_S2_L001_ReadsPerGene.out.tab 9_MA_C_S2_L002_ReadsPerGene.out.tab\n", "1 2245 2291 \n", "2 76258 74490 \n", "3 27956 27638 \n", "4 903 848 \n", "5 0 0 \n", "6 0 0 \n", " 9_MA_C_S2_L003_ReadsPerGene.out.tab 9_MA_C_S2_L004_ReadsPerGene.out.tab\n", "1 2276 2105 \n", "2 76370 75176 \n", "3 28372 28459 \n", "4 943 838 \n", "5 0 0 \n", "6 0 0 \n", " 9_RZ_C_S10_L001_ReadsPerGene.out.tab 9_RZ_C_S10_L002_ReadsPerGene.out.tab\n", "1 3386 3612 \n", "2 149388 149618 \n", "3 503625 504801 \n", "4 1354 1333 \n", "5 1 0 \n", "6 0 0 \n", " 9_RZ_C_S10_L003_ReadsPerGene.out.tab 9_RZ_C_S10_L004_ReadsPerGene.out.tab\n", "1 3283 4853 \n", "2 150874 156664 \n", "3 510186 525524 \n", "4 1359 1357 \n", "5 0 0 \n", "6 0 0 " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "out %>% head" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Exercise: Create the 'out' tibble using a for loop instead of foreach." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Gather and spread \n", "\n", "Now, we have a few other things to fix. To begin with, the first four rows are really summaries and not genes." ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [], "source": [ "### Gather and spread the first four rows\n", "out %>%\n", " dplyr::slice(1:4) %>%\n", " gather(expid, value, -gene) %>% \n", " spread(gene, value) %>%\n", " rename_(.dots = setNames(names(.), c(\"expid\", \"namb\", \"nmulti\", \"nnofeat\",\"nunmap\"))) ->\n", " nmisc" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\t\n", "\t\n", "\n", "\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\n", "
A tibble: 6 × 5
expidnambnmultinnofeatnunmap
<chr><int><int><int><int>
1_MA_J_S18_L001_ReadsPerGene.out.tab 647 66100 203472690
1_MA_J_S18_L002_ReadsPerGene.out.tab 652 65234 200042684
1_MA_J_S18_L003_ReadsPerGene.out.tab 697 66538 205492672
1_MA_J_S18_L004_ReadsPerGene.out.tab 616 65066 205052585
1_RZ_J_S26_L001_ReadsPerGene.out.tab14313958487681467218
1_RZ_J_S26_L002_ReadsPerGene.out.tab13373880797556547022
\n" ], "text/latex": [ "A tibble: 6 × 5\n", "\\begin{tabular}{r|lllll}\n", " expid & namb & nmulti & nnofeat & nunmap\\\\\n", " & & & & \\\\\n", "\\hline\n", "\t 1\\_MA\\_J\\_S18\\_L001\\_ReadsPerGene.out.tab & 647 & 66100 & 20347 & 2690\\\\\n", "\t 1\\_MA\\_J\\_S18\\_L002\\_ReadsPerGene.out.tab & 652 & 65234 & 20004 & 2684\\\\\n", "\t 1\\_MA\\_J\\_S18\\_L003\\_ReadsPerGene.out.tab & 697 & 66538 & 20549 & 2672\\\\\n", "\t 1\\_MA\\_J\\_S18\\_L004\\_ReadsPerGene.out.tab & 616 & 65066 & 20505 & 2585\\\\\n", "\t 1\\_RZ\\_J\\_S26\\_L001\\_ReadsPerGene.out.tab & 1431 & 395848 & 768146 & 7218\\\\\n", "\t 1\\_RZ\\_J\\_S26\\_L002\\_ReadsPerGene.out.tab & 1337 & 388079 & 755654 & 7022\\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", "A tibble: 6 × 5\n", "\n", "| expid <chr> | namb <int> | nmulti <int> | nnofeat <int> | nunmap <int> |\n", "|---|---|---|---|---|\n", "| 1_MA_J_S18_L001_ReadsPerGene.out.tab | 647 | 66100 | 20347 | 2690 |\n", "| 1_MA_J_S18_L002_ReadsPerGene.out.tab | 652 | 65234 | 20004 | 2684 |\n", "| 1_MA_J_S18_L003_ReadsPerGene.out.tab | 697 | 66538 | 20549 | 2672 |\n", "| 1_MA_J_S18_L004_ReadsPerGene.out.tab | 616 | 65066 | 20505 | 2585 |\n", "| 1_RZ_J_S26_L001_ReadsPerGene.out.tab | 1431 | 395848 | 768146 | 7218 |\n", "| 1_RZ_J_S26_L002_ReadsPerGene.out.tab | 1337 | 388079 | 755654 | 7022 |\n", "\n" ], "text/plain": [ " expid namb nmulti nnofeat nunmap\n", "1 1_MA_J_S18_L001_ReadsPerGene.out.tab 647 66100 20347 2690 \n", "2 1_MA_J_S18_L002_ReadsPerGene.out.tab 652 65234 20004 2684 \n", "3 1_MA_J_S18_L003_ReadsPerGene.out.tab 697 66538 20549 2672 \n", "4 1_MA_J_S18_L004_ReadsPerGene.out.tab 616 65066 20505 2585 \n", "5 1_RZ_J_S26_L001_ReadsPerGene.out.tab 1431 395848 768146 7218 \n", "6 1_RZ_J_S26_L002_ReadsPerGene.out.tab 1337 388079 755654 7022 " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "nmisc %>% head" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's break this down and see what each step does." ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\t\n", "\t\n", "\n", "\n", "\t\n", "\t\n", "\t\n", "\t\n", "\n", "
A spec_tbl_df: 4 × 205
gene1_MA_J_S18_L001_ReadsPerGene.out.tab1_MA_J_S18_L002_ReadsPerGene.out.tab1_MA_J_S18_L003_ReadsPerGene.out.tab1_MA_J_S18_L004_ReadsPerGene.out.tab1_RZ_J_S26_L001_ReadsPerGene.out.tab1_RZ_J_S26_L002_ReadsPerGene.out.tab1_RZ_J_S26_L003_ReadsPerGene.out.tab1_RZ_J_S26_L004_ReadsPerGene.out.tab10_MA_C_S3_L001_ReadsPerGene.out.tab⋯47_RZ_P_S50_L003_ReadsPerGene.out.tab47_RZ_P_S50_L004_ReadsPerGene.out.tab9_MA_C_S2_L001_ReadsPerGene.out.tab9_MA_C_S2_L002_ReadsPerGene.out.tab9_MA_C_S2_L003_ReadsPerGene.out.tab9_MA_C_S2_L004_ReadsPerGene.out.tab9_RZ_C_S10_L001_ReadsPerGene.out.tab9_RZ_C_S10_L002_ReadsPerGene.out.tab9_RZ_C_S10_L003_ReadsPerGene.out.tab9_RZ_C_S10_L004_ReadsPerGene.out.tab
<chr><int><int><int><int><int><int><int><int><int>⋯<int><int><int><int><int><int><int><int><int><int>
N_unmapped 2690 2684 2672 2585 7218 7022 7355 707638278⋯ 10036 9962 2245 2291 2276 2105 3386 3612 3283 4853
N_multimapping6610065234665386506639584838807940133839549064124⋯ 536339 52936376258744907637075176149388149618150874156664
N_noFeature 2034720004205492050576814675565477774977371228540⋯1055322104717127956276382837228459503625504801510186525524
N_ambiguous 647 652 697 616 1431 1337 1425 1322 147⋯ 1260 1236 903 848 943 838 1354 1333 1359 1357
\n" ], "text/latex": [ "A spec_tbl_df: 4 × 205\n", "\\begin{tabular}{r|lllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllll}\n", " gene & 1\\_MA\\_J\\_S18\\_L001\\_ReadsPerGene.out.tab & 1\\_MA\\_J\\_S18\\_L002\\_ReadsPerGene.out.tab & 1\\_MA\\_J\\_S18\\_L003\\_ReadsPerGene.out.tab & 1\\_MA\\_J\\_S18\\_L004\\_ReadsPerGene.out.tab & 1\\_RZ\\_J\\_S26\\_L001\\_ReadsPerGene.out.tab & 1\\_RZ\\_J\\_S26\\_L002\\_ReadsPerGene.out.tab & 1\\_RZ\\_J\\_S26\\_L003\\_ReadsPerGene.out.tab & 1\\_RZ\\_J\\_S26\\_L004\\_ReadsPerGene.out.tab & 10\\_MA\\_C\\_S3\\_L001\\_ReadsPerGene.out.tab & 10\\_MA\\_C\\_S3\\_L002\\_ReadsPerGene.out.tab & 10\\_MA\\_C\\_S3\\_L003\\_ReadsPerGene.out.tab & 10\\_MA\\_C\\_S3\\_L004\\_ReadsPerGene.out.tab & 10\\_RZ\\_C\\_S11\\_L001\\_ReadsPerGene.out.tab & 10\\_RZ\\_C\\_S11\\_L002\\_ReadsPerGene.out.tab & 10\\_RZ\\_C\\_S11\\_L003\\_ReadsPerGene.out.tab & 10\\_RZ\\_C\\_S11\\_L004\\_ReadsPerGene.out.tab & 11\\_MA\\_J\\_S20\\_L001\\_ReadsPerGene.out.tab & 11\\_MA\\_J\\_S20\\_L002\\_ReadsPerGene.out.tab & 11\\_MA\\_J\\_S20\\_L003\\_ReadsPerGene.out.tab & 11\\_MA\\_J\\_S20\\_L004\\_ReadsPerGene.out.tab & 11\\_RZ\\_J\\_S28\\_L001\\_ReadsPerGene.out.tab & 11\\_RZ\\_J\\_S28\\_L002\\_ReadsPerGene.out.tab & 11\\_RZ\\_J\\_S28\\_L003\\_ReadsPerGene.out.tab & 11\\_RZ\\_J\\_S28\\_L004\\_ReadsPerGene.out.tab & 12\\_MA\\_P\\_S36\\_L001\\_ReadsPerGene.out.tab & 12\\_MA\\_P\\_S36\\_L002\\_ReadsPerGene.out.tab & 12\\_MA\\_P\\_S36\\_L003\\_ReadsPerGene.out.tab & 12\\_MA\\_P\\_S36\\_L004\\_ReadsPerGene.out.tab & 12\\_RZ\\_P\\_S44\\_L001\\_ReadsPerGene.out.tab & 12\\_RZ\\_P\\_S44\\_L002\\_ReadsPerGene.out.tab & 12\\_RZ\\_P\\_S44\\_L003\\_ReadsPerGene.out.tab & 12\\_RZ\\_P\\_S44\\_L004\\_ReadsPerGene.out.tab & 13\\_MA\\_J\\_S21\\_L001\\_ReadsPerGene.out.tab & 13\\_MA\\_J\\_S21\\_L002\\_ReadsPerGene.out.tab & 13\\_MA\\_J\\_S21\\_L003\\_ReadsPerGene.out.tab & 13\\_MA\\_J\\_S21\\_L004\\_ReadsPerGene.out.tab & 13\\_RZ\\_J\\_S29\\_L001\\_ReadsPerGene.out.tab & 13\\_RZ\\_J\\_S29\\_L002\\_ReadsPerGene.out.tab & 13\\_RZ\\_J\\_S29\\_L003\\_ReadsPerGene.out.tab & 13\\_RZ\\_J\\_S29\\_L004\\_ReadsPerGene.out.tab & 14\\_MA\\_C\\_S4\\_L001\\_ReadsPerGene.out.tab & 14\\_MA\\_C\\_S4\\_L002\\_ReadsPerGene.out.tab & 14\\_MA\\_C\\_S4\\_L003\\_ReadsPerGene.out.tab & 14\\_MA\\_C\\_S4\\_L004\\_ReadsPerGene.out.tab & 14\\_RZ\\_C\\_S12\\_L001\\_ReadsPerGene.out.tab & 14\\_RZ\\_C\\_S12\\_L002\\_ReadsPerGene.out.tab & 14\\_RZ\\_C\\_S12\\_L003\\_ReadsPerGene.out.tab & 14\\_RZ\\_C\\_S12\\_L004\\_ReadsPerGene.out.tab & 15\\_MA\\_C\\_S5\\_L001\\_ReadsPerGene.out.tab & 15\\_MA\\_C\\_S5\\_L002\\_ReadsPerGene.out.tab & 15\\_MA\\_C\\_S5\\_L003\\_ReadsPerGene.out.tab & 15\\_MA\\_C\\_S5\\_L004\\_ReadsPerGene.out.tab & 15\\_RZ\\_C\\_S13\\_L001\\_ReadsPerGene.out.tab & 15\\_RZ\\_C\\_S13\\_L002\\_ReadsPerGene.out.tab & 15\\_RZ\\_C\\_S13\\_L003\\_ReadsPerGene.out.tab & 15\\_RZ\\_C\\_S13\\_L004\\_ReadsPerGene.out.tab & 16\\_MA\\_P\\_S37\\_L001\\_ReadsPerGene.out.tab & 16\\_MA\\_P\\_S37\\_L002\\_ReadsPerGene.out.tab & 16\\_MA\\_P\\_S37\\_L003\\_ReadsPerGene.out.tab & 16\\_MA\\_P\\_S37\\_L004\\_ReadsPerGene.out.tab & 16\\_RZ\\_P\\_S45\\_L001\\_ReadsPerGene.out.tab & 16\\_RZ\\_P\\_S45\\_L002\\_ReadsPerGene.out.tab & 16\\_RZ\\_P\\_S45\\_L003\\_ReadsPerGene.out.tab & 16\\_RZ\\_P\\_S45\\_L004\\_ReadsPerGene.out.tab & 2\\_MA\\_C\\_S1\\_L001\\_ReadsPerGene.out.tab & 2\\_MA\\_C\\_S1\\_L002\\_ReadsPerGene.out.tab & 2\\_MA\\_C\\_S1\\_L003\\_ReadsPerGene.out.tab & 2\\_MA\\_C\\_S1\\_L004\\_ReadsPerGene.out.tab & 2\\_RZ\\_C\\_S9\\_L001\\_ReadsPerGene.out.tab & 2\\_RZ\\_C\\_S9\\_L002\\_ReadsPerGene.out.tab & 2\\_RZ\\_C\\_S9\\_L003\\_ReadsPerGene.out.tab & 2\\_RZ\\_C\\_S9\\_L004\\_ReadsPerGene.out.tab & 2\\_TOT\\_C\\_S17\\_L001\\_ReadsPerGene.out.tab & 2\\_TOT\\_C\\_S17\\_L002\\_ReadsPerGene.out.tab & 2\\_TOT\\_C\\_S17\\_L003\\_ReadsPerGene.out.tab & 2\\_TOT\\_C\\_S17\\_L004\\_ReadsPerGene.out.tab & 21\\_MA\\_C\\_S6\\_L001\\_ReadsPerGene.out.tab & 21\\_MA\\_C\\_S6\\_L002\\_ReadsPerGene.out.tab & 21\\_MA\\_C\\_S6\\_L003\\_ReadsPerGene.out.tab & 21\\_MA\\_C\\_S6\\_L004\\_ReadsPerGene.out.tab & 21\\_RZ\\_C\\_S14\\_L001\\_ReadsPerGene.out.tab & 21\\_RZ\\_C\\_S14\\_L002\\_ReadsPerGene.out.tab & 21\\_RZ\\_C\\_S14\\_L003\\_ReadsPerGene.out.tab & 21\\_RZ\\_C\\_S14\\_L004\\_ReadsPerGene.out.tab & 22\\_MA\\_C\\_S7\\_L001\\_ReadsPerGene.out.tab & 22\\_MA\\_C\\_S7\\_L002\\_ReadsPerGene.out.tab & 22\\_MA\\_C\\_S7\\_L003\\_ReadsPerGene.out.tab & 22\\_MA\\_C\\_S7\\_L004\\_ReadsPerGene.out.tab & 22\\_RZ\\_C\\_S15\\_L001\\_ReadsPerGene.out.tab & 22\\_RZ\\_C\\_S15\\_L002\\_ReadsPerGene.out.tab & 22\\_RZ\\_C\\_S15\\_L003\\_ReadsPerGene.out.tab & 22\\_RZ\\_C\\_S15\\_L004\\_ReadsPerGene.out.tab & 23\\_MA\\_J\\_S22\\_L001\\_ReadsPerGene.out.tab & 23\\_MA\\_J\\_S22\\_L002\\_ReadsPerGene.out.tab & 23\\_MA\\_J\\_S22\\_L003\\_ReadsPerGene.out.tab & 23\\_MA\\_J\\_S22\\_L004\\_ReadsPerGene.out.tab & 23\\_RZ\\_J\\_S30\\_L001\\_ReadsPerGene.out.tab & 23\\_RZ\\_J\\_S30\\_L002\\_ReadsPerGene.out.tab & 23\\_RZ\\_J\\_S30\\_L003\\_ReadsPerGene.out.tab & 23\\_RZ\\_J\\_S30\\_L004\\_ReadsPerGene.out.tab & 24\\_MA\\_J\\_S23\\_L001\\_ReadsPerGene.out.tab & 24\\_MA\\_J\\_S23\\_L002\\_ReadsPerGene.out.tab & 24\\_MA\\_J\\_S23\\_L003\\_ReadsPerGene.out.tab & 24\\_MA\\_J\\_S23\\_L004\\_ReadsPerGene.out.tab & 24\\_RZ\\_J\\_S31\\_L001\\_ReadsPerGene.out.tab & 24\\_RZ\\_J\\_S31\\_L002\\_ReadsPerGene.out.tab & 24\\_RZ\\_J\\_S31\\_L003\\_ReadsPerGene.out.tab & 24\\_RZ\\_J\\_S31\\_L004\\_ReadsPerGene.out.tab & 26\\_MA\\_C\\_S8\\_L001\\_ReadsPerGene.out.tab & 26\\_MA\\_C\\_S8\\_L002\\_ReadsPerGene.out.tab & 26\\_MA\\_C\\_S8\\_L003\\_ReadsPerGene.out.tab & 26\\_MA\\_C\\_S8\\_L004\\_ReadsPerGene.out.tab & 26\\_RZ\\_C\\_S16\\_L001\\_ReadsPerGene.out.tab & 26\\_RZ\\_C\\_S16\\_L002\\_ReadsPerGene.out.tab & 26\\_RZ\\_C\\_S16\\_L003\\_ReadsPerGene.out.tab & 26\\_RZ\\_C\\_S16\\_L004\\_ReadsPerGene.out.tab & 27\\_MA\\_P\\_S38\\_L001\\_ReadsPerGene.out.tab & 27\\_MA\\_P\\_S38\\_L002\\_ReadsPerGene.out.tab & 27\\_MA\\_P\\_S38\\_L003\\_ReadsPerGene.out.tab & 27\\_MA\\_P\\_S38\\_L004\\_ReadsPerGene.out.tab & 27\\_RZ\\_P\\_S46\\_L001\\_ReadsPerGene.out.tab & 27\\_RZ\\_P\\_S46\\_L002\\_ReadsPerGene.out.tab & 27\\_RZ\\_P\\_S46\\_L003\\_ReadsPerGene.out.tab & 27\\_RZ\\_P\\_S46\\_L004\\_ReadsPerGene.out.tab & 3\\_MA\\_J\\_S19\\_L001\\_ReadsPerGene.out.tab & 3\\_MA\\_J\\_S19\\_L002\\_ReadsPerGene.out.tab & 3\\_MA\\_J\\_S19\\_L003\\_ReadsPerGene.out.tab & 3\\_MA\\_J\\_S19\\_L004\\_ReadsPerGene.out.tab & 3\\_RZ\\_J\\_S27\\_L001\\_ReadsPerGene.out.tab & 3\\_RZ\\_J\\_S27\\_L002\\_ReadsPerGene.out.tab & 3\\_RZ\\_J\\_S27\\_L003\\_ReadsPerGene.out.tab & 3\\_RZ\\_J\\_S27\\_L004\\_ReadsPerGene.out.tab & 3\\_TOT\\_J\\_S34\\_L001\\_ReadsPerGene.out.tab & 3\\_TOT\\_J\\_S34\\_L002\\_ReadsPerGene.out.tab & 3\\_TOT\\_J\\_S34\\_L003\\_ReadsPerGene.out.tab & 3\\_TOT\\_J\\_S34\\_L004\\_ReadsPerGene.out.tab & 35\\_MA\\_P\\_S39\\_L001\\_ReadsPerGene.out.tab & 35\\_MA\\_P\\_S39\\_L002\\_ReadsPerGene.out.tab & 35\\_MA\\_P\\_S39\\_L003\\_ReadsPerGene.out.tab & 35\\_MA\\_P\\_S39\\_L004\\_ReadsPerGene.out.tab & 35\\_RZ\\_P\\_S47\\_L001\\_ReadsPerGene.out.tab & 35\\_RZ\\_P\\_S47\\_L002\\_ReadsPerGene.out.tab & 35\\_RZ\\_P\\_S47\\_L003\\_ReadsPerGene.out.tab & 35\\_RZ\\_P\\_S47\\_L004\\_ReadsPerGene.out.tab & 36\\_MA\\_J\\_S24\\_L001\\_ReadsPerGene.out.tab & 36\\_MA\\_J\\_S24\\_L002\\_ReadsPerGene.out.tab & 36\\_MA\\_J\\_S24\\_L003\\_ReadsPerGene.out.tab & 36\\_MA\\_J\\_S24\\_L004\\_ReadsPerGene.out.tab & 36\\_RZ\\_J\\_S32\\_L001\\_ReadsPerGene.out.tab & 36\\_RZ\\_J\\_S32\\_L002\\_ReadsPerGene.out.tab & 36\\_RZ\\_J\\_S32\\_L003\\_ReadsPerGene.out.tab & 36\\_RZ\\_J\\_S32\\_L004\\_ReadsPerGene.out.tab & 38\\_MA\\_P\\_S40\\_L001\\_ReadsPerGene.out.tab & 38\\_MA\\_P\\_S40\\_L002\\_ReadsPerGene.out.tab & 38\\_MA\\_P\\_S40\\_L003\\_ReadsPerGene.out.tab & 38\\_MA\\_P\\_S40\\_L004\\_ReadsPerGene.out.tab & 38\\_RZ\\_P\\_S48\\_L001\\_ReadsPerGene.out.tab & 38\\_RZ\\_P\\_S48\\_L002\\_ReadsPerGene.out.tab & 38\\_RZ\\_P\\_S48\\_L003\\_ReadsPerGene.out.tab & 38\\_RZ\\_P\\_S48\\_L004\\_ReadsPerGene.out.tab & 4\\_MA\\_P\\_S35\\_L001\\_ReadsPerGene.out.tab & 4\\_MA\\_P\\_S35\\_L002\\_ReadsPerGene.out.tab & 4\\_MA\\_P\\_S35\\_L003\\_ReadsPerGene.out.tab & 4\\_MA\\_P\\_S35\\_L004\\_ReadsPerGene.out.tab & 4\\_RZ\\_P\\_S43\\_L001\\_ReadsPerGene.out.tab & 4\\_RZ\\_P\\_S43\\_L002\\_ReadsPerGene.out.tab & 4\\_RZ\\_P\\_S43\\_L003\\_ReadsPerGene.out.tab & 4\\_RZ\\_P\\_S43\\_L004\\_ReadsPerGene.out.tab & 4\\_TOT\\_P\\_S51\\_L001\\_ReadsPerGene.out.tab & 4\\_TOT\\_P\\_S51\\_L002\\_ReadsPerGene.out.tab & 4\\_TOT\\_P\\_S51\\_L003\\_ReadsPerGene.out.tab & 4\\_TOT\\_P\\_S51\\_L004\\_ReadsPerGene.out.tab & 40\\_MA\\_J\\_S25\\_L001\\_ReadsPerGene.out.tab & 40\\_MA\\_J\\_S25\\_L002\\_ReadsPerGene.out.tab & 40\\_MA\\_J\\_S25\\_L003\\_ReadsPerGene.out.tab & 40\\_MA\\_J\\_S25\\_L004\\_ReadsPerGene.out.tab & 40\\_RZ\\_J\\_S33\\_L001\\_ReadsPerGene.out.tab & 40\\_RZ\\_J\\_S33\\_L002\\_ReadsPerGene.out.tab & 40\\_RZ\\_J\\_S33\\_L003\\_ReadsPerGene.out.tab & 40\\_RZ\\_J\\_S33\\_L004\\_ReadsPerGene.out.tab & 45\\_MA\\_P\\_S41\\_L001\\_ReadsPerGene.out.tab & 45\\_MA\\_P\\_S41\\_L002\\_ReadsPerGene.out.tab & 45\\_MA\\_P\\_S41\\_L003\\_ReadsPerGene.out.tab & 45\\_MA\\_P\\_S41\\_L004\\_ReadsPerGene.out.tab & 45\\_RZ\\_P\\_S49\\_L001\\_ReadsPerGene.out.tab & 45\\_RZ\\_P\\_S49\\_L002\\_ReadsPerGene.out.tab & 45\\_RZ\\_P\\_S49\\_L003\\_ReadsPerGene.out.tab & 45\\_RZ\\_P\\_S49\\_L004\\_ReadsPerGene.out.tab & 47\\_MA\\_P\\_S42\\_L001\\_ReadsPerGene.out.tab & 47\\_MA\\_P\\_S42\\_L002\\_ReadsPerGene.out.tab & 47\\_MA\\_P\\_S42\\_L003\\_ReadsPerGene.out.tab & 47\\_MA\\_P\\_S42\\_L004\\_ReadsPerGene.out.tab & 47\\_RZ\\_P\\_S50\\_L001\\_ReadsPerGene.out.tab & 47\\_RZ\\_P\\_S50\\_L002\\_ReadsPerGene.out.tab & 47\\_RZ\\_P\\_S50\\_L003\\_ReadsPerGene.out.tab & 47\\_RZ\\_P\\_S50\\_L004\\_ReadsPerGene.out.tab & 9\\_MA\\_C\\_S2\\_L001\\_ReadsPerGene.out.tab & 9\\_MA\\_C\\_S2\\_L002\\_ReadsPerGene.out.tab & 9\\_MA\\_C\\_S2\\_L003\\_ReadsPerGene.out.tab & 9\\_MA\\_C\\_S2\\_L004\\_ReadsPerGene.out.tab & 9\\_RZ\\_C\\_S10\\_L001\\_ReadsPerGene.out.tab & 9\\_RZ\\_C\\_S10\\_L002\\_ReadsPerGene.out.tab & 9\\_RZ\\_C\\_S10\\_L003\\_ReadsPerGene.out.tab & 9\\_RZ\\_C\\_S10\\_L004\\_ReadsPerGene.out.tab\\\\\n", " & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & & \\\\\n", "\\hline\n", "\t N\\_unmapped & 2690 & 2684 & 2672 & 2585 & 7218 & 7022 & 7355 & 7076 & 38278 & 38180 & 39830 & 36152 & 29051 & 28498 & 29272 & 28454 & 16661 & 16002 & 16883 & 14378 & 111436 & 109267 & 113414 & 111747 & 25260 & 25586 & 26118 & 26753 & 33635 & 33057 & 34575 & 33574 & 15943 & 15846 & 16345 & 13522 & 4819 & 4866 & 4911 & 4731 & 3174 & 3423 & 3277 & 2793 & 4305 & 4152 & 4150 & 4653 & 4057 & 4170 & 4098 & 3643 & 6750 & 6475 & 6283 & 7437 & 5925 & 5568 & 6001 & 6080 & 4679 & 4525 & 4723 & 4816 & 4503 & 4534 & 4663 & 4407 & 13455 & 12808 & 12056 & 14591 & 2090 & 2344 & 2321 & 1718 & 2937 & 3056 & 2853 & 2624 & 10561 & 10067 & 10038 & 11719 & 3189 & 3289 & 3228 & 2776 & 11081 & 11148 & 9978 & 14667 & 1608 & 1661 & 1635 & 1444 & 4139 & 4177 & 4368 & 4248 & 1717 & 1813 & 1849 & 1500 & 2662 & 2592 & 1194 & 1150 & 4002 & 4309 & 4131 & 3409 & 19999 & 19038 & 18723 & 21521 & 3374 & 3366 & 3560 & 3284 & 7706 & 7412 & 8073 & 7902 & 1438 & 1598 & 1465 & 1998 & 3261 & 3220 & 3373 & 3458 & 2279 & 2605 & 2328 & 2381 & 30923 & 29760 & 31539 & 31087 & 11456 & 11318 & 11765 & 11762 & 1538 & 1639 & 1626 & 1410 & 1006 & 1006 & 1107 & 973 & 12097 & 11518 & 12033 & 12089 & 7541 & 7006 & 7516 & 7567 & 8279 & 8308 & 8298 & 8685 & 4993 & 4639 & 5067 & 4856 & 2122 & 2104 & 2111 & 2686 & 2761 & 2812 & 2808 & 2317 & 1134 & 1108 & 1199 & 1040 & 3642 & 3493 & 3572 & 3682 & 7130 & 6903 & 7386 & 7252 & 6541 & 6398 & 6822 & 6734 & 9864 & 9338 & 10036 & 9962 & 2245 & 2291 & 2276 & 2105 & 3386 & 3612 & 3283 & 4853\\\\\n", "\t N\\_multimapping & 66100 & 65234 & 66538 & 65066 & 395848 & 388079 & 401338 & 395490 & 64124 & 62999 & 64876 & 64189 & 63441 & 62031 & 64264 & 64135 & 38568 & 37731 & 38678 & 38700 & 194151 & 190997 & 196432 & 195439 & 92923 & 91814 & 93406 & 94385 & 330393 & 324708 & 334513 & 331710 & 32343 & 31647 & 33091 & 32141 & 261889 & 256455 & 265177 & 261879 & 68765 & 67923 & 70091 & 67429 & 107979 & 106555 & 111006 & 108387 & 117640 & 115460 & 119296 & 116531 & 119221 & 117692 & 120577 & 119224 & 97120 & 93941 & 97410 & 96164 & 275941 & 270306 & 278401 & 276886 & 88417 & 87315 & 90292 & 88646 & 192231 & 188517 & 194169 & 192884 & 1199220 & 1168755 & 1202680 & 1187923 & 80629 & 78767 & 81509 & 79877 & 124056 & 122381 & 127120 & 124162 & 111368 & 109308 & 113007 & 110196 & 165434 & 165797 & 166474 & 171414 & 55184 & 54361 & 56400 & 54216 & 258819 & 254252 & 264445 & 259785 & 51672 & 51506 & 52642 & 50464 & 105530 & 104003 & 105267 & 104137 & 187574 & 182514 & 189153 & 184099 & 221240 & 214768 & 225029 & 217369 & 60186 & 58433 & 60529 & 58704 & 493270 & 480776 & 497663 & 490320 & 39097 & 38612 & 39371 & 40049 & 186710 & 182886 & 188860 & 186838 & 2478334 & 2439361 & 2488112 & 2486314 & 150158 & 147408 & 152255 & 150625 & 487248 & 479023 & 495855 & 490441 & 65502 & 63860 & 65472 & 64099 & 128968 & 125356 & 129156 & 127728 & 89557 & 86727 & 89566 & 88453 & 395309 & 387687 & 400785 & 397047 & 114304 & 111064 & 114557 & 113144 & 1089673 & 1066109 & 1097336 & 1087066 & 1419948 & 1383032 & 1414948 & 1396867 & 72234 & 71039 & 73313 & 68715 & 104401 & 102689 & 105886 & 103948 & 78670 & 76516 & 79110 & 78150 & 444307 & 436571 & 448627 & 445049 & 106272 & 103233 & 107856 & 105301 & 528563 & 514265 & 536339 & 529363 & 76258 & 74490 & 76370 & 75176 & 149388 & 149618 & 150874 & 156664\\\\\n", "\t N\\_noFeature & 20347 & 20004 & 20549 & 20505 & 768146 & 755654 & 777749 & 773712 & 28540 & 28321 & 28968 & 29142 & 345554 & 340522 & 350657 & 350896 & 16831 & 16599 & 17101 & 17270 & 488851 & 482235 & 496302 & 494215 & 26903 & 26724 & 27298 & 27818 & 446859 & 440203 & 455335 & 453828 & 20402 & 19902 & 20885 & 20587 & 510401 & 498126 & 517314 & 512278 & 34335 & 33833 & 35198 & 34464 & 349356 & 343142 & 354918 & 352897 & 60568 & 59706 & 61217 & 59905 & 377641 & 371603 & 382575 & 380492 & 31192 & 30693 & 31664 & 31631 & 409641 & 402322 & 416546 & 414796 & 34916 & 34327 & 35686 & 35535 & 442513 & 436060 & 448033 & 447981 & 88840 & 87478 & 89996 & 88736 & 34160 & 33828 & 34875 & 34184 & 396304 & 389697 & 402911 & 399490 & 35745 & 35100 & 36488 & 35998 & 657881 & 648907 & 664259 & 667515 & 23467 & 23044 & 23848 & 23836 & 573543 & 563250 & 583384 & 578328 & 21692 & 21697 & 22260 & 21494 & 437811 & 429827 & 445188 & 440770 & 31121 & 29910 & 31271 & 30722 & 832099 & 812546 & 843994 & 836824 & 13870 & 13508 & 13863 & 14067 & 478939 & 469160 & 486180 & 482572 & 13229 & 13268 & 13639 & 13919 & 322891 & 317017 & 329119 & 326427 & 210205 & 209522 & 213671 & 215063 & 20307 & 18952 & 19854 & 20019 & 790790 & 779587 & 808081 & 801076 & 19846 & 19503 & 20375 & 20209 & 783680 & 770517 & 795163 & 791830 & 27953 & 27674 & 28812 & 28280 & 874255 & 859873 & 890420 & 885005 & 25539 & 24828 & 25637 & 25495 & 197311 & 193984 & 201826 & 200115 & 112322 & 110188 & 114814 & 113224 & 33660 & 32706 & 34133 & 33202 & 631757 & 617216 & 641085 & 635424 & 34780 & 34009 & 35183 & 34997 & 1001488 & 985895 & 1016783 & 1008052 & 35016 & 33787 & 35697 & 35112 & 1037590 & 1013016 & 1055322 & 1047171 & 27956 & 27638 & 28372 & 28459 & 503625 & 504801 & 510186 & 525524\\\\\n", "\t N\\_ambiguous & 647 & 652 & 697 & 616 & 1431 & 1337 & 1425 & 1322 & 147 & 134 & 135 & 122 & 608 & 652 & 633 & 642 & 79 & 66 & 69 & 75 & 613 & 608 & 652 & 639 & 99 & 96 & 90 & 88 & 483 & 496 & 516 & 513 & 74 & 77 & 85 & 75 & 1112 & 1112 & 1185 & 1141 & 1032 & 887 & 914 & 913 & 1018 & 929 & 1033 & 1028 & 1142 & 1016 & 1168 & 1074 & 1234 & 1153 & 1153 & 1120 & 816 & 767 & 865 & 734 & 549 & 568 & 585 & 579 & 860 & 805 & 868 & 805 & 1306 & 1305 & 1350 & 1330 & 264 & 245 & 302 & 300 & 910 & 890 & 951 & 903 & 1140 & 1099 & 1227 & 1139 & 1179 & 1101 & 1153 & 1115 & 1918 & 1820 & 1917 & 1917 & 528 & 579 & 565 & 587 & 1245 & 1313 & 1264 & 1173 & 473 & 453 & 472 & 466 & 1085 & 1090 & 1237 & 1206 & 1057 & 954 & 1030 & 992 & 2335 & 2207 & 2276 & 2303 & 549 & 538 & 589 & 483 & 494 & 412 & 483 & 458 & 443 & 385 & 439 & 407 & 669 & 648 & 712 & 681 & 501 & 494 & 527 & 497 & 321 & 355 & 291 & 255 & 1163 & 1088 & 1207 & 1118 & 578 & 522 & 630 & 526 & 1732 & 1690 & 1733 & 1674 & 691 & 661 & 761 & 674 & 795 & 821 & 819 & 792 & 1123 & 1097 & 1127 & 1020 & 424 & 447 & 432 & 468 & 214 & 213 & 214 & 223 & 769 & 682 & 712 & 648 & 1542 & 1484 & 1571 & 1637 & 710 & 621 & 732 & 645 & 1255 & 1152 & 1191 & 1157 & 1057 & 980 & 1079 & 992 & 1127 & 1158 & 1260 & 1236 & 903 & 848 & 943 & 838 & 1354 & 1333 & 1359 & 1357\\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", "A spec_tbl_df: 4 × 205\n", "\n", "| gene <chr> | 1_MA_J_S18_L001_ReadsPerGene.out.tab <int> | 1_MA_J_S18_L002_ReadsPerGene.out.tab <int> | 1_MA_J_S18_L003_ReadsPerGene.out.tab <int> | 1_MA_J_S18_L004_ReadsPerGene.out.tab <int> | 1_RZ_J_S26_L001_ReadsPerGene.out.tab <int> | 1_RZ_J_S26_L002_ReadsPerGene.out.tab <int> | 1_RZ_J_S26_L003_ReadsPerGene.out.tab <int> | 1_RZ_J_S26_L004_ReadsPerGene.out.tab <int> | 10_MA_C_S3_L001_ReadsPerGene.out.tab <int> | ⋯ ⋯ | 47_RZ_P_S50_L003_ReadsPerGene.out.tab <int> | 47_RZ_P_S50_L004_ReadsPerGene.out.tab <int> | 9_MA_C_S2_L001_ReadsPerGene.out.tab <int> | 9_MA_C_S2_L002_ReadsPerGene.out.tab <int> | 9_MA_C_S2_L003_ReadsPerGene.out.tab <int> | 9_MA_C_S2_L004_ReadsPerGene.out.tab <int> | 9_RZ_C_S10_L001_ReadsPerGene.out.tab <int> | 9_RZ_C_S10_L002_ReadsPerGene.out.tab <int> | 9_RZ_C_S10_L003_ReadsPerGene.out.tab <int> | 9_RZ_C_S10_L004_ReadsPerGene.out.tab <int> |\n", "|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n", "| N_unmapped | 2690 | 2684 | 2672 | 2585 | 7218 | 7022 | 7355 | 7076 | 38278 | ⋯ | 10036 | 9962 | 2245 | 2291 | 2276 | 2105 | 3386 | 3612 | 3283 | 4853 |\n", "| N_multimapping | 66100 | 65234 | 66538 | 65066 | 395848 | 388079 | 401338 | 395490 | 64124 | ⋯ | 536339 | 529363 | 76258 | 74490 | 76370 | 75176 | 149388 | 149618 | 150874 | 156664 |\n", "| N_noFeature | 20347 | 20004 | 20549 | 20505 | 768146 | 755654 | 777749 | 773712 | 28540 | ⋯ | 1055322 | 1047171 | 27956 | 27638 | 28372 | 28459 | 503625 | 504801 | 510186 | 525524 |\n", "| N_ambiguous | 647 | 652 | 697 | 616 | 1431 | 1337 | 1425 | 1322 | 147 | ⋯ | 1260 | 1236 | 903 | 848 | 943 | 838 | 1354 | 1333 | 1359 | 1357 |\n", "\n" ], "text/plain": [ " gene 1_MA_J_S18_L001_ReadsPerGene.out.tab\n", "1 N_unmapped 2690 \n", "2 N_multimapping 66100 \n", "3 N_noFeature 20347 \n", "4 N_ambiguous 647 \n", " 1_MA_J_S18_L002_ReadsPerGene.out.tab 1_MA_J_S18_L003_ReadsPerGene.out.tab\n", "1 2684 2672 \n", "2 65234 66538 \n", "3 20004 20549 \n", "4 652 697 \n", " 1_MA_J_S18_L004_ReadsPerGene.out.tab 1_RZ_J_S26_L001_ReadsPerGene.out.tab\n", "1 2585 7218 \n", "2 65066 395848 \n", "3 20505 768146 \n", "4 616 1431 \n", " 1_RZ_J_S26_L002_ReadsPerGene.out.tab 1_RZ_J_S26_L003_ReadsPerGene.out.tab\n", "1 7022 7355 \n", "2 388079 401338 \n", "3 755654 777749 \n", "4 1337 1425 \n", " 1_RZ_J_S26_L004_ReadsPerGene.out.tab 10_MA_C_S3_L001_ReadsPerGene.out.tab ⋯\n", "1 7076 38278 ⋯\n", "2 395490 64124 ⋯\n", "3 773712 28540 ⋯\n", "4 1322 147 ⋯\n", " 47_RZ_P_S50_L003_ReadsPerGene.out.tab 47_RZ_P_S50_L004_ReadsPerGene.out.tab\n", "1 10036 9962 \n", "2 536339 529363 \n", "3 1055322 1047171 \n", "4 1260 1236 \n", " 9_MA_C_S2_L001_ReadsPerGene.out.tab 9_MA_C_S2_L002_ReadsPerGene.out.tab\n", "1 2245 2291 \n", "2 76258 74490 \n", "3 27956 27638 \n", "4 903 848 \n", " 9_MA_C_S2_L003_ReadsPerGene.out.tab 9_MA_C_S2_L004_ReadsPerGene.out.tab\n", "1 2276 2105 \n", "2 76370 75176 \n", "3 28372 28459 \n", "4 943 838 \n", " 9_RZ_C_S10_L001_ReadsPerGene.out.tab 9_RZ_C_S10_L002_ReadsPerGene.out.tab\n", "1 3386 3612 \n", "2 149388 149618 \n", "3 503625 504801 \n", "4 1354 1333 \n", " 9_RZ_C_S10_L003_ReadsPerGene.out.tab 9_RZ_C_S10_L004_ReadsPerGene.out.tab\n", "1 3283 4853 \n", "2 150874 156664 \n", "3 510186 525524 \n", "4 1359 1357 " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "out %>%\n", " dplyr::slice(1:4) -> temp1\n", "\n", "temp1" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\t\n", "\t\n", "\n", "\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\n", "
A tibble: 6 × 3
geneexpidvalue
<chr><chr><int>
N_unmapped 1_MA_J_S18_L001_ReadsPerGene.out.tab 2690
N_multimapping1_MA_J_S18_L001_ReadsPerGene.out.tab66100
N_noFeature 1_MA_J_S18_L001_ReadsPerGene.out.tab20347
N_ambiguous 1_MA_J_S18_L001_ReadsPerGene.out.tab 647
N_unmapped 1_MA_J_S18_L002_ReadsPerGene.out.tab 2684
N_multimapping1_MA_J_S18_L002_ReadsPerGene.out.tab65234
\n" ], "text/latex": [ "A tibble: 6 × 3\n", "\\begin{tabular}{r|lll}\n", " gene & expid & value\\\\\n", " & & \\\\\n", "\\hline\n", "\t N\\_unmapped & 1\\_MA\\_J\\_S18\\_L001\\_ReadsPerGene.out.tab & 2690\\\\\n", "\t N\\_multimapping & 1\\_MA\\_J\\_S18\\_L001\\_ReadsPerGene.out.tab & 66100\\\\\n", "\t N\\_noFeature & 1\\_MA\\_J\\_S18\\_L001\\_ReadsPerGene.out.tab & 20347\\\\\n", "\t N\\_ambiguous & 1\\_MA\\_J\\_S18\\_L001\\_ReadsPerGene.out.tab & 647\\\\\n", "\t N\\_unmapped & 1\\_MA\\_J\\_S18\\_L002\\_ReadsPerGene.out.tab & 2684\\\\\n", "\t N\\_multimapping & 1\\_MA\\_J\\_S18\\_L002\\_ReadsPerGene.out.tab & 65234\\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", "A tibble: 6 × 3\n", "\n", "| gene <chr> | expid <chr> | value <int> |\n", "|---|---|---|\n", "| N_unmapped | 1_MA_J_S18_L001_ReadsPerGene.out.tab | 2690 |\n", "| N_multimapping | 1_MA_J_S18_L001_ReadsPerGene.out.tab | 66100 |\n", "| N_noFeature | 1_MA_J_S18_L001_ReadsPerGene.out.tab | 20347 |\n", "| N_ambiguous | 1_MA_J_S18_L001_ReadsPerGene.out.tab | 647 |\n", "| N_unmapped | 1_MA_J_S18_L002_ReadsPerGene.out.tab | 2684 |\n", "| N_multimapping | 1_MA_J_S18_L002_ReadsPerGene.out.tab | 65234 |\n", "\n" ], "text/plain": [ " gene expid value\n", "1 N_unmapped 1_MA_J_S18_L001_ReadsPerGene.out.tab 2690\n", "2 N_multimapping 1_MA_J_S18_L001_ReadsPerGene.out.tab 66100\n", "3 N_noFeature 1_MA_J_S18_L001_ReadsPerGene.out.tab 20347\n", "4 N_ambiguous 1_MA_J_S18_L001_ReadsPerGene.out.tab 647\n", "5 N_unmapped 1_MA_J_S18_L002_ReadsPerGene.out.tab 2684\n", "6 N_multimapping 1_MA_J_S18_L002_ReadsPerGene.out.tab 65234" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "temp1 %>% gather(expid, value, -gene) -> temp2\n", "\n", "head(temp2)" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\t\n", "\t\n", "\n", "\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\n", "
A tibble: 6 × 5
expidN_ambiguousN_multimappingN_noFeatureN_unmapped
<chr><int><int><int><int>
1_MA_J_S18_L001_ReadsPerGene.out.tab 647 66100 203472690
1_MA_J_S18_L002_ReadsPerGene.out.tab 652 65234 200042684
1_MA_J_S18_L003_ReadsPerGene.out.tab 697 66538 205492672
1_MA_J_S18_L004_ReadsPerGene.out.tab 616 65066 205052585
1_RZ_J_S26_L001_ReadsPerGene.out.tab14313958487681467218
1_RZ_J_S26_L002_ReadsPerGene.out.tab13373880797556547022
\n" ], "text/latex": [ "A tibble: 6 × 5\n", "\\begin{tabular}{r|lllll}\n", " expid & N\\_ambiguous & N\\_multimapping & N\\_noFeature & N\\_unmapped\\\\\n", " & & & & \\\\\n", "\\hline\n", "\t 1\\_MA\\_J\\_S18\\_L001\\_ReadsPerGene.out.tab & 647 & 66100 & 20347 & 2690\\\\\n", "\t 1\\_MA\\_J\\_S18\\_L002\\_ReadsPerGene.out.tab & 652 & 65234 & 20004 & 2684\\\\\n", "\t 1\\_MA\\_J\\_S18\\_L003\\_ReadsPerGene.out.tab & 697 & 66538 & 20549 & 2672\\\\\n", "\t 1\\_MA\\_J\\_S18\\_L004\\_ReadsPerGene.out.tab & 616 & 65066 & 20505 & 2585\\\\\n", "\t 1\\_RZ\\_J\\_S26\\_L001\\_ReadsPerGene.out.tab & 1431 & 395848 & 768146 & 7218\\\\\n", "\t 1\\_RZ\\_J\\_S26\\_L002\\_ReadsPerGene.out.tab & 1337 & 388079 & 755654 & 7022\\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", "A tibble: 6 × 5\n", "\n", "| expid <chr> | N_ambiguous <int> | N_multimapping <int> | N_noFeature <int> | N_unmapped <int> |\n", "|---|---|---|---|---|\n", "| 1_MA_J_S18_L001_ReadsPerGene.out.tab | 647 | 66100 | 20347 | 2690 |\n", "| 1_MA_J_S18_L002_ReadsPerGene.out.tab | 652 | 65234 | 20004 | 2684 |\n", "| 1_MA_J_S18_L003_ReadsPerGene.out.tab | 697 | 66538 | 20549 | 2672 |\n", "| 1_MA_J_S18_L004_ReadsPerGene.out.tab | 616 | 65066 | 20505 | 2585 |\n", "| 1_RZ_J_S26_L001_ReadsPerGene.out.tab | 1431 | 395848 | 768146 | 7218 |\n", "| 1_RZ_J_S26_L002_ReadsPerGene.out.tab | 1337 | 388079 | 755654 | 7022 |\n", "\n" ], "text/plain": [ " expid N_ambiguous N_multimapping N_noFeature\n", "1 1_MA_J_S18_L001_ReadsPerGene.out.tab 647 66100 20347 \n", "2 1_MA_J_S18_L002_ReadsPerGene.out.tab 652 65234 20004 \n", "3 1_MA_J_S18_L003_ReadsPerGene.out.tab 697 66538 20549 \n", "4 1_MA_J_S18_L004_ReadsPerGene.out.tab 616 65066 20505 \n", "5 1_RZ_J_S26_L001_ReadsPerGene.out.tab 1431 395848 768146 \n", "6 1_RZ_J_S26_L002_ReadsPerGene.out.tab 1337 388079 755654 \n", " N_unmapped\n", "1 2690 \n", "2 2684 \n", "3 2672 \n", "4 2585 \n", "5 7218 \n", "6 7022 " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "temp2 %>% spread(gene, value) -> temp3\n", "\n", "head(temp3)" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\t\n", "\t\n", "\n", "\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\n", "
A tibble: 6 × 5
expidnambnmultinnofeatnunmap
<chr><int><int><int><int>
1_MA_J_S18_L001_ReadsPerGene.out.tab 647 66100 203472690
1_MA_J_S18_L002_ReadsPerGene.out.tab 652 65234 200042684
1_MA_J_S18_L003_ReadsPerGene.out.tab 697 66538 205492672
1_MA_J_S18_L004_ReadsPerGene.out.tab 616 65066 205052585
1_RZ_J_S26_L001_ReadsPerGene.out.tab14313958487681467218
1_RZ_J_S26_L002_ReadsPerGene.out.tab13373880797556547022
\n" ], "text/latex": [ "A tibble: 6 × 5\n", "\\begin{tabular}{r|lllll}\n", " expid & namb & nmulti & nnofeat & nunmap\\\\\n", " & & & & \\\\\n", "\\hline\n", "\t 1\\_MA\\_J\\_S18\\_L001\\_ReadsPerGene.out.tab & 647 & 66100 & 20347 & 2690\\\\\n", "\t 1\\_MA\\_J\\_S18\\_L002\\_ReadsPerGene.out.tab & 652 & 65234 & 20004 & 2684\\\\\n", "\t 1\\_MA\\_J\\_S18\\_L003\\_ReadsPerGene.out.tab & 697 & 66538 & 20549 & 2672\\\\\n", "\t 1\\_MA\\_J\\_S18\\_L004\\_ReadsPerGene.out.tab & 616 & 65066 & 20505 & 2585\\\\\n", "\t 1\\_RZ\\_J\\_S26\\_L001\\_ReadsPerGene.out.tab & 1431 & 395848 & 768146 & 7218\\\\\n", "\t 1\\_RZ\\_J\\_S26\\_L002\\_ReadsPerGene.out.tab & 1337 & 388079 & 755654 & 7022\\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", "A tibble: 6 × 5\n", "\n", "| expid <chr> | namb <int> | nmulti <int> | nnofeat <int> | nunmap <int> |\n", "|---|---|---|---|---|\n", "| 1_MA_J_S18_L001_ReadsPerGene.out.tab | 647 | 66100 | 20347 | 2690 |\n", "| 1_MA_J_S18_L002_ReadsPerGene.out.tab | 652 | 65234 | 20004 | 2684 |\n", "| 1_MA_J_S18_L003_ReadsPerGene.out.tab | 697 | 66538 | 20549 | 2672 |\n", "| 1_MA_J_S18_L004_ReadsPerGene.out.tab | 616 | 65066 | 20505 | 2585 |\n", "| 1_RZ_J_S26_L001_ReadsPerGene.out.tab | 1431 | 395848 | 768146 | 7218 |\n", "| 1_RZ_J_S26_L002_ReadsPerGene.out.tab | 1337 | 388079 | 755654 | 7022 |\n", "\n" ], "text/plain": [ " expid namb nmulti nnofeat nunmap\n", "1 1_MA_J_S18_L001_ReadsPerGene.out.tab 647 66100 20347 2690 \n", "2 1_MA_J_S18_L002_ReadsPerGene.out.tab 652 65234 20004 2684 \n", "3 1_MA_J_S18_L003_ReadsPerGene.out.tab 697 66538 20549 2672 \n", "4 1_MA_J_S18_L004_ReadsPerGene.out.tab 616 65066 20505 2585 \n", "5 1_RZ_J_S26_L001_ReadsPerGene.out.tab 1431 395848 768146 7218 \n", "6 1_RZ_J_S26_L002_ReadsPerGene.out.tab 1337 388079 755654 7022 " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "temp3 %>% rename_(.dots = setNames(names(.), c(\"expid\", \"namb\", \"nmulti\", \"nnofeat\",\"nunmap\"))) %>% head" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [], "source": [ "### Gather and spread the genes to get a count matrix\n", "out %>%\n", " dplyr::slice(-(1:4)) %>%\n", " gather(expid, value, -gene) %>% \n", " spread(gene, value) -> genecounts" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\t\n", "\t\n", "\n", "\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\n", "
A tibble: 5 × 5
expidCNAG_00001CNAG_00002CNAG_00003CNAG_00004
<chr><int><int><int><int>
1_MA_J_S18_L001_ReadsPerGene.out.tab0663874
1_MA_J_S18_L002_ReadsPerGene.out.tab0592579
1_MA_J_S18_L003_ReadsPerGene.out.tab0742779
1_MA_J_S18_L004_ReadsPerGene.out.tab0662269
1_RZ_J_S26_L001_ReadsPerGene.out.tab0501651
\n" ], "text/latex": [ "A tibble: 5 × 5\n", "\\begin{tabular}{r|lllll}\n", " expid & CNAG\\_00001 & CNAG\\_00002 & CNAG\\_00003 & CNAG\\_00004\\\\\n", " & & & & \\\\\n", "\\hline\n", "\t 1\\_MA\\_J\\_S18\\_L001\\_ReadsPerGene.out.tab & 0 & 66 & 38 & 74\\\\\n", "\t 1\\_MA\\_J\\_S18\\_L002\\_ReadsPerGene.out.tab & 0 & 59 & 25 & 79\\\\\n", "\t 1\\_MA\\_J\\_S18\\_L003\\_ReadsPerGene.out.tab & 0 & 74 & 27 & 79\\\\\n", "\t 1\\_MA\\_J\\_S18\\_L004\\_ReadsPerGene.out.tab & 0 & 66 & 22 & 69\\\\\n", "\t 1\\_RZ\\_J\\_S26\\_L001\\_ReadsPerGene.out.tab & 0 & 50 & 16 & 51\\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", "A tibble: 5 × 5\n", "\n", "| expid <chr> | CNAG_00001 <int> | CNAG_00002 <int> | CNAG_00003 <int> | CNAG_00004 <int> |\n", "|---|---|---|---|---|\n", "| 1_MA_J_S18_L001_ReadsPerGene.out.tab | 0 | 66 | 38 | 74 |\n", "| 1_MA_J_S18_L002_ReadsPerGene.out.tab | 0 | 59 | 25 | 79 |\n", "| 1_MA_J_S18_L003_ReadsPerGene.out.tab | 0 | 74 | 27 | 79 |\n", "| 1_MA_J_S18_L004_ReadsPerGene.out.tab | 0 | 66 | 22 | 69 |\n", "| 1_RZ_J_S26_L001_ReadsPerGene.out.tab | 0 | 50 | 16 | 51 |\n", "\n" ], "text/plain": [ " expid CNAG_00001 CNAG_00002 CNAG_00003\n", "1 1_MA_J_S18_L001_ReadsPerGene.out.tab 0 66 38 \n", "2 1_MA_J_S18_L002_ReadsPerGene.out.tab 0 59 25 \n", "3 1_MA_J_S18_L003_ReadsPerGene.out.tab 0 74 27 \n", "4 1_MA_J_S18_L004_ReadsPerGene.out.tab 0 66 22 \n", "5 1_RZ_J_S26_L001_ReadsPerGene.out.tab 0 50 16 \n", " CNAG_00004\n", "1 74 \n", "2 79 \n", "3 79 \n", "4 69 \n", "5 51 " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "genecounts[1:5,1:5]" ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [], "source": [ "out %>%\n", " dplyr::slice(-(1:4)) %>% t() -> check" ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\n", "
A matrix: 5 × 5 of type chr
geneCNAG_04548CNAG_07303CNAG_07304CNAG_00001CNAG_07305
1_MA_J_S18_L001_ReadsPerGene.out.tab 0 0 8 0 0
1_MA_J_S18_L002_ReadsPerGene.out.tab 0 0 7 0 1
1_MA_J_S18_L003_ReadsPerGene.out.tab 0 0 10 0 0
1_MA_J_S18_L004_ReadsPerGene.out.tab 1 0 9 0 0
\n" ], "text/latex": [ "A matrix: 5 × 5 of type chr\n", "\\begin{tabular}{r|lllll}\n", "\tgene & CNAG\\_04548 & CNAG\\_07303 & CNAG\\_07304 & CNAG\\_00001 & CNAG\\_07305\\\\\n", "\t1\\_MA\\_J\\_S18\\_L001\\_ReadsPerGene.out.tab & 0 & 0 & 8 & 0 & 0 \\\\\n", "\t1\\_MA\\_J\\_S18\\_L002\\_ReadsPerGene.out.tab & 0 & 0 & 7 & 0 & 1 \\\\\n", "\t1\\_MA\\_J\\_S18\\_L003\\_ReadsPerGene.out.tab & 0 & 0 & 10 & 0 & 0 \\\\\n", "\t1\\_MA\\_J\\_S18\\_L004\\_ReadsPerGene.out.tab & 1 & 0 & 9 & 0 & 0 \\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", "A matrix: 5 × 5 of type chr\n", "\n", "| gene | CNAG_04548 | CNAG_07303 | CNAG_07304 | CNAG_00001 | CNAG_07305 |\n", "| 1_MA_J_S18_L001_ReadsPerGene.out.tab | 0 | 0 | 8 | 0 | 0 |\n", "| 1_MA_J_S18_L002_ReadsPerGene.out.tab | 0 | 0 | 7 | 0 | 1 |\n", "| 1_MA_J_S18_L003_ReadsPerGene.out.tab | 0 | 0 | 10 | 0 | 0 |\n", "| 1_MA_J_S18_L004_ReadsPerGene.out.tab | 1 | 0 | 9 | 0 | 0 |\n", "\n" ], "text/plain": [ " [,1] [,2] [,3] \n", "gene CNAG_04548 CNAG_07303 CNAG_07304\n", "1_MA_J_S18_L001_ReadsPerGene.out.tab 0 0 8 \n", "1_MA_J_S18_L002_ReadsPerGene.out.tab 0 0 7 \n", "1_MA_J_S18_L003_ReadsPerGene.out.tab 0 0 10 \n", "1_MA_J_S18_L004_ReadsPerGene.out.tab 1 0 9 \n", " [,4] [,5] \n", "gene CNAG_00001 CNAG_07305\n", "1_MA_J_S18_L001_ReadsPerGene.out.tab 0 0 \n", "1_MA_J_S18_L002_ReadsPerGene.out.tab 0 1 \n", "1_MA_J_S18_L003_ReadsPerGene.out.tab 0 0 \n", "1_MA_J_S18_L004_ReadsPerGene.out.tab 0 0 " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "check[1:5,1:5]" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "R", "language": "R", "name": "ir" }, "language_info": { "codemirror_mode": "r", "file_extension": ".r", "mimetype": "text/x-r-source", "name": "R", "pygments_lexer": "r", "version": "3.6.0" } }, "nbformat": 4, "nbformat_minor": 1 }