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annotate small_rna_maps.r @ 6:a3be3601bcb3 draft

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planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit 9f9c64aff0d225881bedb97bd5035ccbca945d9d
author artbio
date Mon, 09 Oct 2017 11:07:09 -0400
parents 12c14642e6ac
children a96e6a7df2b7
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6d48150495e3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit d4d8106d66b65679a1a685ab94bfcf99cdb7b959
artbio
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1 ## Setup R error handling to go to stderr
6d48150495e3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit d4d8106d66b65679a1a685ab94bfcf99cdb7b959
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2 options( show.error.messages=F,
6d48150495e3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit d4d8106d66b65679a1a685ab94bfcf99cdb7b959
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3 error = function () { cat( geterrmessage(), file=stderr() ); q( "no", 1, F ) } )
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12c14642e6ac planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit 24a21619d79d83b38cef7f1a7b858c621e4c8449
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4 # options(warn = -1)
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6d48150495e3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit d4d8106d66b65679a1a685ab94bfcf99cdb7b959
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5 library(RColorBrewer)
6d48150495e3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit d4d8106d66b65679a1a685ab94bfcf99cdb7b959
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6 library(lattice)
6d48150495e3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit d4d8106d66b65679a1a685ab94bfcf99cdb7b959
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7 library(latticeExtra)
6d48150495e3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit d4d8106d66b65679a1a685ab94bfcf99cdb7b959
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8 library(grid)
6d48150495e3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit d4d8106d66b65679a1a685ab94bfcf99cdb7b959
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9 library(gridExtra)
6d48150495e3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit d4d8106d66b65679a1a685ab94bfcf99cdb7b959
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10 library(optparse)
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11
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6d48150495e3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit d4d8106d66b65679a1a685ab94bfcf99cdb7b959
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12 option_list <- list(
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13 make_option(c("-f", "--first_dataframe"), type="character", help="path to first dataframe"),
507383cce5a8 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit edbb53cb13b52bf8e71c562fa8acc2c3be2fb270
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14 make_option(c("-e", "--extra_dataframe"), type="character", help="path to additional dataframe"),
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a3be3601bcb3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit 9f9c64aff0d225881bedb97bd5035ccbca945d9d
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15 make_option(c("-n", "--normalization"), type="character", help="space-separated normalization/size factors"),
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16 make_option("--first_plot_method", type = "character", help="How additional data should be plotted"),
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artbio
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17 make_option("--extra_plot_method", type = "character", help="How additional data should be plotted"),
507383cce5a8 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit edbb53cb13b52bf8e71c562fa8acc2c3be2fb270
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18 make_option("--output_pdf", type = "character", help="path to the pdf file with plots")
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6d48150495e3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit d4d8106d66b65679a1a685ab94bfcf99cdb7b959
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19 )
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21 parser <- OptionParser(usage = "%prog [options] file", option_list = option_list)
6d48150495e3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit d4d8106d66b65679a1a685ab94bfcf99cdb7b959
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22 args = parse_args(parser)
6d48150495e3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit d4d8106d66b65679a1a685ab94bfcf99cdb7b959
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23
2
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24 # data frames implementation
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25 ## first table
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26 Table = read.delim(args$first_dataframe, header=T, row.names=NULL)
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27 if (args$first_plot_method == "Counts" | args$first_plot_method == "Size") {
12c14642e6ac planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit 24a21619d79d83b38cef7f1a7b858c621e4c8449
artbio
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28 Table <- within(Table, Counts[Polarity=="R"] <- (Counts[Polarity=="R"]*-1))
12c14642e6ac planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit 24a21619d79d83b38cef7f1a7b858c621e4c8449
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29 }
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6d48150495e3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit d4d8106d66b65679a1a685ab94bfcf99cdb7b959
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30 n_samples=length(unique(Table$Dataset))
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a3be3601bcb3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit 9f9c64aff0d225881bedb97bd5035ccbca945d9d
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31 samples = unique(Table$Dataset)
a3be3601bcb3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit 9f9c64aff0d225881bedb97bd5035ccbca945d9d
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32 if (args$normalization != "") {
a3be3601bcb3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit 9f9c64aff0d225881bedb97bd5035ccbca945d9d
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33 norm_factors = as.numeric(unlist(strsplit(args$normalization, " ")))
a3be3601bcb3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit 9f9c64aff0d225881bedb97bd5035ccbca945d9d
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34 } else {
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35 norm_factors = rep(1, n_samples)
a3be3601bcb3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit 9f9c64aff0d225881bedb97bd5035ccbca945d9d
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36 }
a3be3601bcb3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit 9f9c64aff0d225881bedb97bd5035ccbca945d9d
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37 if (args$first_plot_method == "Counts" | args$first_plot_method == "Size" | args$first_plot_method == "Coverage") {
a3be3601bcb3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit 9f9c64aff0d225881bedb97bd5035ccbca945d9d
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38 i = 1
a3be3601bcb3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit 9f9c64aff0d225881bedb97bd5035ccbca945d9d
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39 for (sample in samples) {
a3be3601bcb3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit 9f9c64aff0d225881bedb97bd5035ccbca945d9d
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40 print(norm_factors[i])
a3be3601bcb3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit 9f9c64aff0d225881bedb97bd5035ccbca945d9d
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41 Table[, length(Table)][Table$Dataset==sample] <- Table[, length(Table)][Table$Dataset==sample]*norm_factors[i]
a3be3601bcb3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit 9f9c64aff0d225881bedb97bd5035ccbca945d9d
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42 i = i + 1
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43 }
a3be3601bcb3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit 9f9c64aff0d225881bedb97bd5035ccbca945d9d
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44 print(tail(Table))
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45 }
0
6d48150495e3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit d4d8106d66b65679a1a685ab94bfcf99cdb7b959
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46 genes=unique(levels(Table$Chromosome))
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47 per_gene_readmap=lapply(genes, function(x) subset(Table, Chromosome==x))
6d48150495e3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit d4d8106d66b65679a1a685ab94bfcf99cdb7b959
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48 per_gene_limit=lapply(genes, function(x) c(1, unique(subset(Table, Chromosome==x)$Chrom_length)) )
6d48150495e3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit d4d8106d66b65679a1a685ab94bfcf99cdb7b959
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49 n_genes=length(per_gene_readmap)
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50 # second table
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51 if (args$extra_plot_method != '') {
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52 ExtraTable=read.delim(args$extra_dataframe, header=T, row.names=NULL)
12c14642e6ac planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit 24a21619d79d83b38cef7f1a7b858c621e4c8449
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53 if (args$extra_plot_method == "Counts" | args$extra_plot_method=='Size') {
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54 ExtraTable <- within(ExtraTable, Counts[Polarity=="R"] <- (Counts[Polarity=="R"]*-1))
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55 }
a3be3601bcb3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit 9f9c64aff0d225881bedb97bd5035ccbca945d9d
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56 if (args$extra_plot_method == "Counts" | args$extra_plot_method == "Size" | args$extra_plot_method == "Coverage") {
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57 i = 1
a3be3601bcb3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit 9f9c64aff0d225881bedb97bd5035ccbca945d9d
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58 for (sample in samples) {
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59 ExtraTable[, length(ExtraTable)][ExtraTable$Dataset==sample] <- ExtraTable[, length(ExtraTable)][ExtraTable$Dataset==sample]*norm_factors[i]
a3be3601bcb3 planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit 9f9c64aff0d225881bedb97bd5035ccbca945d9d
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60 i = i + 1
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61 }
6
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62 }
5
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63 per_gene_size=lapply(genes, function(x) subset(ExtraTable, Chromosome==x))
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64 }
0
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65
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66 ## functions
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67
5
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68 plot_unit = function(df, method=args$first_plot_method, ...) {
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69 if (method == 'Counts') {
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70 p = xyplot(Counts~Coordinate|factor(Dataset, levels=unique(Dataset))+factor(Chromosome, levels=unique(Chromosome)),
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71 data=df,
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72 type='h',
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73 lwd=1.5,
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74 scales= list(relation="free", x=list(rot=0, cex=0.7, axs="i", tck=0.5), y=list(tick.number=4, rot=90, cex=0.7)),
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75 xlab=NULL, main=NULL, ylab=NULL,
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76 as.table=T,
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77 origin = 0,
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78 horizontal=FALSE,
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79 group=Polarity,
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80 col=c("red","blue"),
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81 par.strip.text = list(cex=0.7),
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82 ...)
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83 } else if (method != "Size") {
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84 p = xyplot(eval(as.name(method))~Coordinate|factor(Dataset, levels=unique(Dataset))+factor(Chromosome, levels=unique(Chromosome)),
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85 data=df,
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86 type='p',
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87 pch=19,
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88 cex=0.35,
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89 scales= list(relation="free", x=list(rot=0, cex=0.7, axs="i", tck=0.5), y=list(tick.number=4, rot=90, cex=0.7)),
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90 xlab=NULL, main=NULL, ylab=NULL,
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91 as.table=T,
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92 origin = 0,
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93 horizontal=FALSE,
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94 group=Polarity,
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95 col=c("red","blue"),
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96 par.strip.text = list(cex=0.7),
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97 ...)
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98 } else {
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99 p = barchart(Counts~as.factor(Size)|factor(Dataset, levels=unique(Dataset))+Chromosome, data = df, origin = 0,
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100 horizontal=FALSE,
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101 group=Polarity,
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102 stack=TRUE,
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103 col=c('red', 'blue'),
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104 scales=list(y=list(tick.number=4, rot=90, relation="free", cex=0.7), x=list(rot=0, cex=0.7, axs="i", tck=0.5)),
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105 xlab = NULL,
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106 ylab = NULL,
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107 main = NULL,
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108 as.table=TRUE,
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109 par.strip.text = list(cex=0.6),
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110 ...)
0
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111 }
5
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112 combineLimits(p)
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113 }
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114
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115 plot_single <- function(df, method=args$first_plot_method, rows_per_page=rows_per_page, ...) {
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116 if (method == 'Counts') {
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117 p = xyplot(Counts~Coordinate|factor(Dataset, levels=unique(Dataset))+factor(Chromosome, levels=unique(Chromosome)),
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118 data=df,
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119 type='h',
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120 lwd=1.5,
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121 scales= list(relation="free", x=list(rot=0, cex=0.7, axs="i", tck=0.5), y=list(tick.number=4, rot=90, cex=0.7)),
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122 xlab=list(label=bottom_first_method[[args$first_plot_method]], cex=.85),
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123 ylab=list(label=legend_first_method[[args$first_plot_method]], cex=.85),
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124 main=title_first_method[[args$first_plot_method]],
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125 origin = 0,
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126 group=Polarity,
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127 col=c("red","blue"),
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128 par.strip.text = list(cex=0.7),
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129 as.table=T,
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130 ...)
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131 p = update(useOuterStrips(p, strip.left=strip.custom(par.strip.text = list(cex=0.5))), layout=c(n_samples, rows_per_page))
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132 return(p)
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133 } else if (method != "Size") {
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134 p = xyplot(eval(as.name(method))~Coordinate|factor(Dataset, levels=unique(Dataset))+factor(Chromosome, levels=unique(Chromosome)),
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135 data=df,
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136 type='p',
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137 pch=19,
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138 cex=0.35,
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139 scales= list(relation="free", x=list(rot=0, cex=0.7, axs="i", tck=0.5), y=list(tick.number=4, rot=90, cex=0.7)),
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140 xlab=list(label=bottom_first_method[[args$first_plot_method]], cex=.85),
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141 ylab=list(label=legend_first_method[[args$first_plot_method]], cex=.85),
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142 main=title_first_method[[args$first_plot_method]],
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143 origin = 0,
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144 group=Polarity,
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145 col=c("red","blue"),
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146 par.strip.text = list(cex=0.7),
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147 as.table=T,
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148 ...)
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149 p = update(useOuterStrips(p, strip.left=strip.custom(par.strip.text = list(cex=0.5))), layout=c(n_samples, rows_per_page))
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150 return(p)
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151 } else {
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152 p= barchart(Counts~as.factor(Size)|factor(Dataset, levels=unique(Dataset))+Chromosome, data = df, origin = 0,
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153 horizontal=FALSE,
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154 group=Polarity,
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155 stack=TRUE,
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156 col=c('red', 'blue'),
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157 scales=list(y=list(tick.number=4, rot=90, relation="free", cex=0.5, alternating=T), x=list(rot=0, cex=0.6, tck=0.5, alternating=c(3,3))),
12c14642e6ac planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit 24a21619d79d83b38cef7f1a7b858c621e4c8449
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158 xlab=list(label=bottom_first_method[[args$first_plot_method]], cex=.85),
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159 ylab=list(label=legend_first_method[[args$first_plot_method]], cex=.85),
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160 main=title_first_method[[args$first_plot_method]],
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161 par.strip.text = list(cex=0.7),
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162 nrow = 8,
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163 as.table=TRUE,
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164
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165 ...)
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166 p = update(useOuterStrips(p, strip.left=strip.custom(par.strip.text = list(cex=0.5))), layout=c(n_samples, rows_per_page))
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167
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168 p = combineLimits(p, extend=TRUE)
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169 return (p)
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170 }
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171 }
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172
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173 ## function parameters
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174
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175 #par.settings.firstplot = list(layout.heights=list(top.padding=11, bottom.padding = -14))
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176 #par.settings.secondplot=list(layout.heights=list(top.padding=11, bottom.padding = -15), strip.background=list(col=c("lavender","deepskyblue")))
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177 par.settings.firstplot = list(layout.heights=list(top.padding=-2, bottom.padding=-2))
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178 par.settings.secondplot=list(layout.heights=list(top.padding=-1, bottom.padding=-1), strip.background=list(col=c("lavender","deepskyblue")))
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179 par.settings.single_plot=list(strip.background = list(col = c("lightblue", "lightgreen")))
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180 title_first_method = list(Counts="Read Counts", Coverage="Coverage depths", Median="Median sizes", Mean="Mean sizes", Size="Size Distributions")
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181 title_extra_method = list(Counts="Read Counts", Coverage="Coverage depths", Median="Median sizes", Mean="Mean sizes", Size="Size Distributions")
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182 legend_first_method =list(Counts="Read count", Coverage="Coverage depth", Median="Median size", Mean="Mean size", Size="Read count")
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183 legend_extra_method =list(Counts="Read count", Coverage="Coveragedepth", Median="Median size", Mean="Mean size", Size="Read count")
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184 bottom_first_method =list(Counts="Coordinates (nbre of bases)",Coverage="Coordinates (nbre of bases)", Median="Coordinates (nbre of bases)", Mean="Coordinates (nbre of bases)", Size="Sizes of reads")
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185 bottom_extra_method =list(Counts="Coordinates (nbre of bases)",Coverage="Coordinates (nbre of bases)", Median="Coordinates (nbre of bases)", Mean="Coordinates (nbre of bases)", Size="Sizes of reads")
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186
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187 ## Plotting Functions
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188
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189 double_plot <- function(...) {
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190 if (n_genes > 5) {page_height=15; rows_per_page=10} else {
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191 rows_per_page= 2 * n_genes; page_height=1.5*n_genes}
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192 if (n_samples > 4) {page_width = 8.2677*n_samples/4} else {page_width = 7 * n_samples/2}
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193 pdf(file=args$output_pdf, paper="special", height=page_height, width=page_width)
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194 for (i in seq(1,n_genes,rows_per_page/2)) {
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195 start=i
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196 end=i+rows_per_page/2-1
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197 if (end>n_genes) {end=n_genes}
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198 first_plot.list = lapply(per_gene_readmap[start:end], function(x) plot_unit(x, strip=FALSE, par.settings=par.settings.firstplot))
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199 second_plot.list = lapply(per_gene_size[start:end], function(x) plot_unit(x, method=args$extra_plot_method, par.settings=par.settings.secondplot))
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200 plot.list=rbind(second_plot.list, first_plot.list)
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201 args_list=c(plot.list, list( nrow=rows_per_page+1, ncol=1, heights=unit(c(40,30,40,30,40,30,40,30,40,30,10), rep("mm", 11)),
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202 top=textGrob(paste(title_first_method[[args$first_plot_method]], "and", title_extra_method[[args$extra_plot_method]]), gp=gpar(cex=1), vjust=0, just="top"),
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203 left=textGrob(paste(legend_first_method[[args$first_plot_method]], "/", legend_extra_method[[args$extra_plot_method]]), gp=gpar(cex=1), vjust=2, rot=90),
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204 sub=textGrob(paste(bottom_first_method[[args$first_plot_method]], "/", bottom_extra_method[[args$extra_plot_method]]), gp=gpar(cex=1), just="bottom", vjust=2)
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205 )
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206 )
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207 do.call(grid.arrange, args_list)
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208 }
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209 devname=dev.off()
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210 }
0
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211
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212
5
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213 single_plot <- function(...) {
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214 width = 8.2677 * n_samples / 2
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215 rows_per_page=8
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216 pdf(file=args$output_pdf, paper="special", height=11.69, width=width)
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217 for (i in seq(1,n_genes,rows_per_page)) {
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218 start=i
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219 end=i+rows_per_page-1
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220 if (end>n_genes) {end=n_genes}
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221 bunch = do.call(rbind, per_gene_readmap[start:end]) # sub dataframe from the list
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222 p = plot_single(bunch, method=args$first_plot_method, par.settings=par.settings.single_plot, rows_per_page=rows_per_page)
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223 plot(p)
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224 }
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225 devname=dev.off()
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226 }
0
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227
5
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228 # main
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229
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230 if (args$extra_plot_method != '') { double_plot() }
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231 if (args$extra_plot_method == '') {
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232 single_plot()
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233 }
0
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240
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