annotate DESeq.Rmd @ 4:7f0281d26b81 draft

planemo upload for repository https://github.com/statonlab/docker-GRReport/tree/master/my_tools/rmarkdown_deseq2 commit a23e23222252167ef7c3338a4872e84706df8f83-dirty
author mingchen0919
date Tue, 08 Aug 2017 14:33:57 -0400
parents 312e9bcc02f1
children 2f8ddef8d545
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1 ---
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2 title: 'DESeq2: Perform DESeq analysis'
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3 output:
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4 html_document:
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5 number_sections: true
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6 toc: true
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7 theme: cosmo
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8 highlight: tango
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9 ---
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11 ```{r setup, include=FALSE, warning=FALSE, message=FALSE}
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12 knitr::opts_chunk$set(
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13 echo = ECHO
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14 )
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16 library(stringi)
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17 library(DESeq2)
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18 library(pheatmap)
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19 # library(PoiClaClu)
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20 library(RColorBrewer)
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21 ```
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23 # `DESeqDataSet` object
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25 ```{r}
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26 count_files = strsplit(opt$count_files, ',')[[1]]
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27 sample_table = read.table(opt$sample_table, header = TRUE)
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29 ## copy count files into working directory
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30 file_copy = file.copy(count_files, sample_table$fileName, overwrite = TRUE)
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32 ## DESeqDataSet object
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33 dds = DESeqDataSetFromHTSeqCount(sampleTable = sample_table,
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34 directory = './',
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35 design = DESIGN_FORMULA)
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36 dds
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37 ```
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39 # Pre-filtering the dataset.
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41 We can remove the rows that have 0 or 1 count to reduce object size and increase the calculation speed.
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43 * Number of rows before pre-filtering
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44 ```{r}
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45 nrow(dds)
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46 ```
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48 * Number of rows after pre-filtering
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49 ```{r}
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50 dds = dds[rowSums(counts(dds)) > 1, ]
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51 nrow(dds)
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52 ```
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54 # Peek at data {.tabset}
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56 ## Count Data
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58 ```{r}
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59 datatable(head(counts(dds), 100), style="bootstrap",
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60 class="table-condensed", options = list(dom = 'tp', scrollX = TRUE))
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61 ```
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63 ## Sample Table
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65 ```{r}
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66 datatable(sample_table, style="bootstrap",
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67 class="table-condensed", options = list(dom = 'tp', scrollX = TRUE))
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68 ```
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70 # Sample distance on variance stabilized data {.tabset}
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72 ## `rlog` Stabilizing transformation
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74 ```{r}
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75 rld = rlog(dds, blind = FALSE)
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76 datatable(head(assay(rld), 100), style="bootstrap",
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77 class="table-condensed", options = list(dom = 'tp', scrollX = TRUE))
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78 ```
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80 ## Sample distance
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81
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82 ```{r}
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83 sampleDists <- dist(t(assay(rld)))
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84 sampleDists
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85 ```
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86
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87 # Differential expression analysis
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89 ```{r}
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90 dds <- DESeq(dds)
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91 ```
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92
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93 ```{r}
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94 rm("opt")
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95 save(list=ls(all.names = TRUE), file='DESEQ_WORKSPACE')
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96 ```
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97
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98