Mercurial > repos > bgruening > music_construct_eset

annotate scripts/compare.R @ 4:282819d09a4f draft

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"planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit d007ae51743e621dc47524f681501e72ef3a2910"
author bgruening
date Mon, 02 May 2022 09:58:18 +0000
parents 7ffaa0968da3
children
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1 suppressWarnings(suppressPackageStartupMessages(library(xbioc)))
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2 suppressWarnings(suppressPackageStartupMessages(library(MuSiC)))
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3 suppressWarnings(suppressPackageStartupMessages(library(reshape2)))
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4 suppressWarnings(suppressPackageStartupMessages(library(cowplot)))
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5 ## We use this script to estimate the effectiveness of proportion methods
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7 ## Load Conf
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8 args <- commandArgs(trailingOnly = TRUE)
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9 source(args[1])
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11 method_key <- list("MuSiC" = "est_music",
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12 "NNLS" = "est_nnls")[[est_method]]
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14 delim <- "::" ## separator bulk datasets and their samples
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16 scale_yaxes <- function(gplot, value) {
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17 if (is.na(value)) {
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18 gplot
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19 } else {
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20 gplot + scale_y_continuous(lim = c(0, value))
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21 }
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22 }
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25 set_factor_data <- function(bulk_data, factor_name = NULL) {
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26 if (is.null(factor_name)) {
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27 factor_name <- "None" ## change to something plottable
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28 }
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29 pdat <- pData(bulk_data)
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30 sam_fact <- NULL
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31 if (factor_name %in% colnames(pdat)) {
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32 sam_fact <- cbind(rownames(pdat),
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33 as.character(pdat[[factor_name]]))
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34 cat(paste0(" - factor: ", factor_name,
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35 " found in phenotypes\n"))
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36 } else {
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37 ## We assign this as the factor for the entire dataset
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38 sam_fact <- cbind(rownames(pdat),
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39 factor_name)
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40 cat(paste0(" - factor: assigning \"", factor_name,
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41 "\" to whole dataset\n"))
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42 }
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43 colnames(sam_fact) <- c("Samples", "Factors")
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44 return(as.data.frame(sam_fact))
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45 }
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46
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47 ## Due to limiting sizes, we need to load and unload
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48 ## possibly very large datasets.
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49 process_pair <- function(sc_data, bulk_data,
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50 ctypes_label, samples_label, ctypes,
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51 factor_group) {
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52 ## - Generate
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53 est_prop <- music_prop(
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54 bulk.eset = bulk_data, sc.eset = sc_data,
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55 clusters = ctypes_label,
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56 samples = samples_label, select.ct = ctypes, verbose = T)
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57 ## -
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58 estimated_music_props <- est_prop$Est.prop.weighted
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59 estimated_nnls_props <- est_prop$Est.prop.allgene
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60 ## -
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61 fact_data <- set_factor_data(bulk_data, factor_group)
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62 ## -
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63 return(list(est_music = estimated_music_props,
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64 est_nnls = estimated_nnls_props,
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65 bulk_sample_totals = colSums(exprs(bulk_data)),
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66 plot_groups = fact_data))
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67 }
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68
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69 music_on_all <- function(files) {
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70 results <- list()
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71 for (sc_name in names(files)) {
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72 cat(paste0("sc-group:", sc_name, "\n"))
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73 scgroup <- files[[sc_name]]
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74 ## - sc Data
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75 sc_est <- readRDS(scgroup$dataset)
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76 ## - params
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77 celltypes_label <- scgroup$label_cell
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78 samples_label <- scgroup$label_sample
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79 celltypes <- scgroup$celltype
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80
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81 results[[sc_name]] <- list()
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82 for (bulk_name in names(scgroup$bulk)) {
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83 cat(paste0(" - bulk-group:", bulk_name, "\n"))
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84 bulkgroup <- scgroup$bulk[[bulk_name]]
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85 ## - bulk Data
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86 bulk_est <- readRDS(bulkgroup$dataset)
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87 ## - bulk params
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88 pheno_facts <- bulkgroup$pheno_facts
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89 pheno_excl <- bulkgroup$pheno_excl
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90 ##
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91 results[[sc_name]][[bulk_name]] <- process_pair(
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92 sc_est, bulk_est,
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93 celltypes_label, samples_label,
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94 celltypes, bulkgroup$factor_group)
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95 ##
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96 rm(bulk_est) ## unload
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97 }
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98 rm(sc_est) ## unload
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99 }
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100 return(results)
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101 }
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102
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103 plot_all_individual_heatmaps <- function(results) {
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104 pdf(out_heatmulti_pdf, width = 8, height = 8)
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105 for (sc_name in names(results)) {
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106 for (bk_name in names(results[[sc_name]])) {
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107 res <- results[[sc_name]][[bk_name]]
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108 plot_hmap <- Prop_heat_Est(
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109 data.matrix(res[[method_key]]), method.name = est_method) +
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110 ggtitle(paste0("[", est_method, "Cell type ",
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111 "proportions in ",
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112 bk_name, " (Bulk) based on ",
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113 sc_name, " (scRNA)")) +
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114 xlab("Cell Types (scRNA)") +
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115 ylab("Samples (Bulk)") +
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116 theme(axis.text.x = element_text(angle = -90),
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117 axis.text.y = element_text(size = 6))
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118 print(plot_hmap)
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119 }
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120 }
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121 dev.off()
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122 }
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123
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124 merge_factors_spread <- function(grudat_spread, factor_groups) {
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125 ## Generated
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126 merge_it <- function(matr, plot_groups, valname) {
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127 ren <- melt(lapply(matr, function(mat) {
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128 mat["ct"] <- rownames(mat); return(mat)}))
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129 ## - Grab factors and merge into list
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130 ren_new <- merge(ren, plot_groups, by.x = "variable", by.y = "Samples")
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131 colnames(ren_new) <- c("Sample", "Cell", valname, "Bulk", "Factors")
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132 return(ren_new)
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133 }
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134 tab <- merge(merge_it(grudat$spread$prop, factor_groups, "value.prop"),
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135 merge_it(grudat$spread$scale, factor_groups, "value.scale"),
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136 by = c("Sample", "Cell", "Bulk", "Factors"))
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137 return(tab)
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138 }
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139
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140 unlist_names <- function(results, method, prepend_bkname=FALSE) {
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141 unique(sort(
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142 unlist(lapply(names(results), function(scname) {
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143 lapply(names(results[[scname]]), function(bkname) {
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144 res <- get(method)(results[[scname]][[bkname]][[method_key]])
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145 if (prepend_bkname) {
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146 ## We *do not* assume unique bulk sample names
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147 ## across different bulk datasets.
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148 res <- paste0(bkname, delim, res)
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149 }
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150 return(res)
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151 })
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152 }))
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153 ))
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154 }
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155
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156 summarized_matrix <- function(results) { # nolint
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157 ## We assume that cell types MUST be unique, but that sample
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158 ## names do not need to be. For this reason, we must prepend
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159 ## the bulk dataset name to the individual sample names.
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160 all_celltypes <- unlist_names(results, "colnames")
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161 all_samples <- unlist_names(results, "rownames", prepend_bkname = TRUE)
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162
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163 ## Iterate through all possible samples and populate a table.
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164 ddff <- data.frame()
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165 ddff_scale <- data.frame()
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166 for (cell in all_celltypes) {
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167 for (sample in all_samples) {
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168 group_sname <- unlist(strsplit(sample, split = delim))
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169 bulk <- group_sname[1]
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170 id_sample <- group_sname[2]
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171 for (scgroup in names(results)) {
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172 if (bulk %in% names(results[[scgroup]])) {
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173 mat_prop <- results[[scgroup]][[bulk]][[method_key]]
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174 vec_counts <- results[[scgroup]][[bulk]]$bulk_sample_totals
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175 ## - We use sample instead of id_sample because we need to
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176 ## extract bulk sets from the complete matrix later. It's
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177 ## messy, yes.
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178 if (cell %in% colnames(mat_prop)) {
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179 ddff[cell, sample] <- mat_prop[id_sample, cell]
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180 ddff_scale[cell, sample] <- mat_prop[id_sample, cell] * vec_counts[[id_sample]] #nolint
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181 } else {
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182 ddff[cell, sample] <- 0
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183 ddff_scale[cell, sample] <- 0
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184 }
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185 }
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186 }
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187 }
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188 }
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189 return(list(prop = ddff, scaled = ddff_scale))
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190 }
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191
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192 flatten_factor_list <- function(results) {
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193 ## Get a 2d DF of all factors across all bulk samples.
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194 res <- c()
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195 for (scgroup in names(results)) {
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196 for (bulkgroup in names(results[[scgroup]])) {
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197 dat <- results[[scgroup]][[bulkgroup]]$plot_groups
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198 dat$Samples <- paste0(bulkgroup, delim, dat$Samples) #nolint
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199 res <- rbind(res, dat)
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200 }
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201 }
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202 return(res)
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203 }
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204
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205 group_by_dataset <- function(summat) {
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206 bulk_names <- unlist(
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207 lapply(names(files), function(x) names(files[[x]]$bulk)))
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208 mat_names <- colnames(summat$prop)
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209 bd <- list()
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210 bd_scale <- list()
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211 bd_spread_scale <- list()
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212 bd_spread_prop <- list()
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213 for (bname in bulk_names) {
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214 subs <- mat_names[startsWith(mat_names, paste0(bname, delim))]
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215 ## -
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216 bd[[bname]] <- rowSums(summat$prop[, subs])
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217 bd_scale[[bname]] <- rowSums(summat$scaled[, subs])
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218 bd_spread_scale[[bname]] <- summat$scaled[, subs]
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219 bd_spread_prop[[bname]] <- summat$prop[, subs]
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220 }
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221 return(list(prop = as.data.frame(bd),
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222 scaled = as.data.frame(bd_scale),
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223 spread = list(scale = bd_spread_scale,
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224 prop = bd_spread_prop)))
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225 }
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226
4
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227 do_cluster <- function(grudat_spread_melt, xaxis, yaxis, value_name,
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228 xlabs="", ylabs="", titled="",
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229 order_col=T, order_row=T, size=11) {
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230
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231 data_m <- grudat_spread_melt
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232 data_matrix <- {
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233 tmp <- dcast(data_m, formula(paste0(yaxis, " ~ ", xaxis)), value.var = value_name)
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234 rownames(tmp) <- tmp[[yaxis]]
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235 tmp[[yaxis]] <- NULL
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236 tmp
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237 }
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238 dist_method <- "euclidean"
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239 clust_method <- "complete"
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240
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241 if (order_row) {
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242 dd_row <- as.dendrogram(hclust(dist(data_matrix, method = dist_method), method = clust_method))
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243 row_ord <- order.dendrogram(dd_row)
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244 ordered_row_names <- row.names(data_matrix[row_ord, ])
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245 data_m[[yaxis]] <- factor(data_m[[yaxis]], levels = ordered_row_names)
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246 }
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247
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248 if (order_col) {
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249 dd_col <- as.dendrogram(hclust(dist(t(data_matrix), method = dist_method),
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250 method = clust_method))
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251 col_ord <- order.dendrogram(dd_col)
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252 ordered_col_names <- colnames(data_matrix[, col_ord])
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253 data_m[[xaxis]] <- factor(data_m[[xaxis]], levels = ordered_col_names)
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254 }
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255
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256 heat_plot <- ggplot(data_m, aes_string(x = xaxis, y = yaxis, fill = value_name)) +
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257 geom_tile(colour = "white") +
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258 scale_fill_gradient2(low = "steelblue", high = "red", mid = "white",
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259 name = element_blank()) +
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260 scale_y_discrete(position = "right") +
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261 theme(axis.text.x = element_text(angle = -90, hjust = 0,
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262 size = size)) +
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263 ggtitle(label = titled) + xlab(xlabs) + ylab(ylabs)
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264
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265 ## Graphics
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266 dendro_linesize <- 0.5
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267 dendro_colunit <- 0.2
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268 dendro_rowunit <- 0.1
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269 final_plot <- heat_plot
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270
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271 if (order_row) {
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272 dendro_data_row <- ggdendro::dendro_data(dd_row, type = "rectangle")
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273 dendro_row <- cowplot::axis_canvas(heat_plot, axis = "y", coord_flip = TRUE) +
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274 ggplot2::geom_segment(data = ggdendro::segment(dendro_data_row),
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275 ggplot2::aes(y = -y, x = x, xend = xend, yend = -yend),
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276 size = dendro_linesize) + ggplot2::coord_flip()
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277 final_plot <- cowplot::insert_yaxis_grob(
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278 final_plot, dendro_row, grid::unit(dendro_colunit, "null"),
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279 position = "left")
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280 }
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281 if (order_col) {
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282 dendro_data_col <- ggdendro::dendro_data(dd_col, type = "rectangle")
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283 dendro_col <- cowplot::axis_canvas(heat_plot, axis = "x") +
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284 ggplot2::geom_segment(data = ggdendro::segment(dendro_data_col),
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285 ggplot2::aes(x = x, y = y, xend = xend, yend = yend),
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286 size = dendro_linesize)
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287 final_plot <- cowplot::insert_xaxis_grob(
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288 final_plot, dendro_col, grid::unit(dendro_rowunit, "null"),
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289 position = "top")
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290 }
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291 return(cowplot::ggdraw(final_plot))
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292 }
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293
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294 summarize_heatmaps <- function(grudat_spread_melt, do_factors, cluster="None") {
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295 ## - Cluster is either "Rows", "Cols", "Both", or "None"
3
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296 do_single <- function(grudat_melted, yaxis, xaxis, fillval, title,
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297 ylabs = element_blank(), xlabs = element_blank(),
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298 use_log = TRUE, size = 11) {
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299 ## Convert from matrix to long format
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300 melted <- grudat_melted ## copy?
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301 if (use_log) {
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302 melted[[fillval]] <- log10(melted[[fillval]] + 1)
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303 }
4
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304 if (cluster == "None") {
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305 return(ggplot(melted) +
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306 geom_tile(aes_string(y = yaxis, x = xaxis, fill = fillval),
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307 colour = "white") +
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308 scale_fill_gradient2(
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309 low = "steelblue", high = "red", mid = "white",
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310 name = element_blank()) +
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311 theme(axis.text.x = element_text(
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312 angle = -90, hjust = 0, size = size)) +
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313 ggtitle(label = title) + xlab(xlabs) + ylab(ylabs))
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314 } else {
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315 return(do_cluster(grudat_spread_melt, xaxis, yaxis, fillval,
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316 xlabs, ylabs, title,
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317 (cluster %in% c("Cols", "Both")),
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318 (cluster %in% c("Rows", "Both"))))
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319 }
3
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320 }
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321
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322 do_gridplot <- function(title, xvar, plot="both", ncol=2, size = 11) {
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323 do_logged <- (plot %in% c("log", "both"))
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324 do_normal <- (plot %in% c("normal", "both"))
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325 plist <- list()
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326 if (do_logged) {
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327 plist[["1"]] <- do_single(grudat_spread_melt, "Cell", xvar,
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328 "value.scale", "Reads (log10+1)",
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329 size = size)
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330 plist[["2"]] <- do_single(grudat_spread_melt, "Cell", xvar,
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331 "value.prop", "Sample (log10+1)",
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332 size = size)
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333 }
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334 if (do_normal) {
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335 plist[["A"]] <- do_single(grudat_spread_melt, "Cell", xvar,
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336 "value.scale", "Reads", use_log = F,
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337 size = size)
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338 plist[["B"]] <- do_single(grudat_spread_melt, "Cell", xvar,
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339 "value.prop", "Sample", use_log = F,
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340 size = size)
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341 }
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342 return(plot_grid(ggdraw() + draw_label(title, fontface = "bold"),
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343 plot_grid(plotlist = plist, ncol = ncol),
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344 ncol = 1, rel_heights = c(0.05, 0.95)))
4
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345 }
3
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346
4
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347 p1 <- do_gridplot("Cell Types vs Bulk Datasets", "Bulk", "both")
282819d09a4f "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit d007ae51743e621dc47524f681501e72ef3a2910"
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348 p2a <- do_gridplot("Cell Types vs Samples", "Sample", "normal",
282819d09a4f "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit d007ae51743e621dc47524f681501e72ef3a2910"
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349 ncol = 1, size = 8)
282819d09a4f "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit d007ae51743e621dc47524f681501e72ef3a2910"
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diff changeset
350 p2b <- do_gridplot("Cell Types vs Samples (log10+1)", "Sample", "log",
282819d09a4f "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit d007ae51743e621dc47524f681501e72ef3a2910"
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diff changeset
351 ncol = 1, size = 8)
3
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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352 p3 <- ggplot + theme_void()
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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diff changeset
353 if (do_factors) {
4
282819d09a4f "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit d007ae51743e621dc47524f681501e72ef3a2910"
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354 p3 <- do_gridplot("Cell Types vs Factors", "Factors", "both")
3
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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355 }
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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diff changeset
356 return(list(bulk = p1,
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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357 samples = list(log = p2b, normal = p2a),
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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358 factors = p3))
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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359 }
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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diff changeset
360
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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361 summarize_boxplots <- function(grudat_spread, do_factors) {
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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362 common1 <- ggplot(grudat_spread, aes(x = value.prop)) + ggtitle("Sample") +
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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363 xlab(element_blank()) + ylab(element_blank())
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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364 common2 <- ggplot(grudat_spread, aes(x = value.scale)) + ggtitle("Reads") +
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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365 xlab(element_blank()) + ylab(element_blank())
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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366
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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367 A <- B <- list() #nolint
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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diff changeset
368 ## Cell type by sample
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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369 A$p1 <- common2 + geom_boxplot(aes(y = Cell, color = Bulk))
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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370 A$p2 <- common1 + geom_boxplot(aes(y = Cell, color = Bulk))
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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371 ## Sample by Cell type
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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372 B$p1 <- common2 + geom_boxplot(aes(y = Bulk, color = Cell)) +
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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373 ylab("Bulk Dataset")
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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374 B$p2 <- common1 + geom_boxplot(aes(y = Bulk, color = Cell)) +
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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375 ylab("Bulk Dataset")
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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diff changeset
376 ## -- Factor plots are optional
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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377 A$p3 <- B$p3 <- A$p4 <- B$p4 <- ggplot() + theme_void()
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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378
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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379 if (do_factors) {
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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diff changeset
380 A$p3 <- common1 + geom_boxplot(aes(y = Cell, color = Factors))
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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381 A$p4 <- common2 + geom_boxplot(aes(y = Cell, color = Factors))
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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diff changeset
382 B$p3 <- common1 + geom_boxplot(aes(y = Bulk, color = Factors)) +
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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383 ylab("Bulk Dataset")
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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384 B$p4 <- common2 + geom_boxplot(aes(y = Bulk, color = Factors)) +
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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385 ylab("Bulk Dataset")
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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386 }
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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387
4
282819d09a4f "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit d007ae51743e621dc47524f681501e72ef3a2910"
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388 title_a <- "Cell Types vs Bulk Datasets"
282819d09a4f "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit d007ae51743e621dc47524f681501e72ef3a2910"
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389 title_b <- "Bulk Datasets vs Cell Types"
3
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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390 if (do_factors) {
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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391 title_a <- paste0(title_a, " and Factors")
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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392 title_b <- paste0(title_b, " and Factors")
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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393 }
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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394
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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395 a_all <- plot_grid(ggdraw() + draw_label(title_a, fontface = "bold"),
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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396 plot_grid(plotlist = A, ncol = 2),
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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397 ncol = 1, rel_heights = c(0.05, 0.95))
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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398 b_all <- plot_grid(ggdraw() + draw_label(title_b, fontface = "bold"),
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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399 plot_grid(plotlist = B, ncol = 2),
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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400 ncol = 1, rel_heights = c(0.05, 0.95))
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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diff changeset
401 return(list(cell = a_all, bulk = b_all))
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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402 }
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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403
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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404 filter_output <- function(grudat_spread_melt, out_filt) {
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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405 print_red <- function(comment, red_list) {
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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406 cat(paste(comment, paste(red_list, collapse = ", "), "\n"))
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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407 }
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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408 grudat_filt <- grudat_spread_melt
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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409 print_red("Total Cell types:", unique(grudat_filt$Cell))
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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410 if (!is.null(out_filt$cells)) {
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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411 grudat_filt <- grudat_filt[grudat_filt$Cell %in% out_filt$cells, ]
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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412 print_red(" - selecting:", out_filt$cells)
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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413 }
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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414 print_red("Total Factors:", unique(grudat_spread_melt$Factors))
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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415 if (!is.null(out_filt$facts)) {
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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416 grudat_filt <- grudat_filt[grudat_filt$Factors %in% out_filt$facts, ]
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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417 print_red(" - selecting:", out_filt$facts)
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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418 }
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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419 return(grudat_filt)
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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420 }
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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421
4
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diff changeset
422 writable2 <- function(obj, prefix, title) {
282819d09a4f "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit d007ae51743e621dc47524f681501e72ef3a2910"
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diff changeset
423 write.table(obj,
282819d09a4f "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit d007ae51743e621dc47524f681501e72ef3a2910"
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diff changeset
424 file = paste0("report_data/", prefix, "_",
282819d09a4f "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit d007ae51743e621dc47524f681501e72ef3a2910"
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diff changeset
425 title, ".tabular"),
282819d09a4f "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit d007ae51743e621dc47524f681501e72ef3a2910"
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diff changeset
426 quote = F, sep = "\t", col.names = NA)
282819d09a4f "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit d007ae51743e621dc47524f681501e72ef3a2910"
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diff changeset
427 }
282819d09a4f "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit d007ae51743e621dc47524f681501e72ef3a2910"
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diff changeset
428
3
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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429
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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430 results <- music_on_all(files)
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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431 summat <- summarized_matrix(results)
7ffaa0968da3 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 8beed1a19fcd9dc59f7746e1dfa735a2d5f29784"
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432 grudat <- group_by_dataset(summat)
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433 grudat_spread_melt <- merge_factors_spread(grudat$spread,
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434 flatten_factor_list(results))
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435 grudat_spread_melt_filt <- filter_output(grudat_spread_melt, out_filt)
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436
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437 plot_all_individual_heatmaps(results)
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438
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439 ## The output filters ONLY apply to boxplots, since these take
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440 do_factors <- (length(unique(grudat_spread_melt[["Factors"]])) > 1)
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441 box_plots <- summarize_boxplots(grudat_spread_melt_filt, do_factors)
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442 heat_maps <- summarize_heatmaps(grudat_spread_melt_filt, do_factors,
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443 dendro_setting)
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444
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445 pdf(out_heatsumm_pdf, width = 14, height = 14)
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446 print(heat_maps)
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447 print(box_plots)
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448 dev.off()
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449
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450 ## Generate output tables
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451 stats_prop <- lapply(grudat$spread$prop, function(x) {
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452 t(apply(x, 1, summary))})
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453 stats_scale <- lapply(grudat$spread$scale, function(x) {
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454 t(apply(x, 1, summary))})
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455
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456 ## Make the value table printable
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457 grudat_spread_melt$value.scale <- as.integer(grudat_spread_melt$value.scale) # nolint
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458 colnames(grudat_spread_melt) <- c("Sample", "Cell", "Bulk", "Factors",
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459 "CT Prop in Sample", "Number of Reads")
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460
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461 writable2(grudat_spread_melt, "values", "Data Table")
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462 writable2(summat$prop, "values", "Matrix of Cell Type Sample Proportions")
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463 writable2({
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464 aa <- as.matrix(summat$scaled); mode(aa) <- "integer"; aa
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465 }, "values", "Matrix of Cell Type Read Counts")
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466
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467 for (bname in names(stats_prop)) {
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468 writable2(stats_prop[[bname]], "stats", paste0(bname, ": Sample Props"))
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469 writable2(stats_scale[[bname]], "stats", paste0(bname, ": Read Props"))
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470 }