Mercurial > repos > eschen42 > w4mcorcov

annotate w4mcorcov_calc.R @ 4:d3bb34e764fe draft

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planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 7a0b65df47977b9c7a62de7dc1587e5fb3e5abc1
author eschen42
date Mon, 15 Jan 2018 14:08:59 -0500
parents 61935618f92c
children 1d046f648b47
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1 # center with 'colMeans()' - ref: http://gastonsanchez.com/visually-enforced/how-to/2014/01/15/Center-data-in-R/
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2 center_colmeans <- function(x) {
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3 xcenter = colMeans(x)
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4 x - rep(xcenter, rep.int(nrow(x), ncol(x)))
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5 }
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6
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7 #### OPLS-DA
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8 algoC <- "nipals"
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9
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d3bb34e764fe planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 7a0b65df47977b9c7a62de7dc1587e5fb3e5abc1
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10 do_detail_plot <- function(x_dataMatrix, x_predictor, x_is_match, x_algorithm, x_prefix, x_show_labels, x_show_loado_labels, x_progress = print, x_env, x_crossval_i) {
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11 off <- function(x) if (x_show_labels == "0") 0 else x
0
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12 if (x_is_match && ncol(x_dataMatrix) > 0 && length(unique(x_predictor))> 1) {
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13 my_oplsda <- opls(
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14 x = x_dataMatrix
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15 , y = x_predictor
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16 , algoC = x_algorithm
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17 , predI = 1
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18 , orthoI = if (ncol(x_dataMatrix) > 1) 1 else 0
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19 , printL = FALSE
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20 , plotL = FALSE
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21 , crossvalI = x_crossval_i
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22 )
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23 my_oplsda_suppLs_y_levels <- levels(as.factor(my_oplsda@suppLs$y))
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24 fctr_lvl_1 <- my_oplsda_suppLs_y_levels[1]
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25 fctr_lvl_2 <- my_oplsda_suppLs_y_levels[2]
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26 my_cor_vs_cov <- cor_vs_cov(
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27 matrix_x = x_dataMatrix
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28 , ropls_x = my_oplsda
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29 )
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30 with(
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31 my_cor_vs_cov
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32 , {
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33 min_x <- min(covariance)
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34 max_x <- max(covariance)
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35 lim_x <- max(sapply(X=c(min_x, max_x), FUN=abs))
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36 covariance <- covariance / lim_x
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37 lim_x <- 1.2
3
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38 main_label <- sprintf("%s for level %s versus %s", x_prefix, fctr_lvl_1, fctr_lvl_2)
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39 main_cex <- min(1.0, 46.0/nchar(main_label))
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40 # "It is generally accepted that a variable should be selected if vj>1, [27–29],
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41 # but a proper threshold between 0.83 and 1.21 can yield more relevant variables according to [28]."
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42 # (Mehmood 2012 doi:10.1186/1748-7188-6-27)
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43 vipco <- pmax(0, pmin(1,(vip4p-0.83)/(1.21-0.83)))
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44 alpha <- 0.1 + 0.4 * vipco
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45 red <- as.numeric(correlation > 0) * vipco
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46 blue <- as.numeric(correlation < 0) * vipco
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47 plus_cor <- correlation
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48 plus_cov <- covariance
1
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49 cex <- 0.75
0
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50 plot(
2
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51 y = plus_cor
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52 , x = plus_cov
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53 , type="p"
3
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54 , xlim=c( -lim_x - off(0.2), lim_x + off(0.2) )
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55 , ylim=c( -1.0 - off(0.2), 1.0 + off(0.2) )
0
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56 , xlab = sprintf("relative covariance(feature,t1)")
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57 , ylab = sprintf("correlation(feature,t1)")
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58 , main = main_label
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59 , cex.main = main_cex
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60 , cex = cex
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61 , pch = 16
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62 , col = rgb(blue = blue, red = red, green = 0, alpha = alpha)
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63 )
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64 low_x <- -0.7 * lim_x
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65 high_x <- 0.7 * lim_x
2
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66 text(x = low_x, y = -0.05, labels = fctr_lvl_1, col = "blue")
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67 text(x = high_x, y = 0.05, labels = fctr_lvl_2, col = "red")
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68 if ( x_show_labels != "0" ) {
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69 my_loadp <- loadp
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70 my_loado <- loado
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71 names(my_loadp) <- tsv1$featureID
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72 names(my_loado) <- tsv1$featureID
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73 if ( x_show_labels == "ALL" ) {
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74 n_labels <- length(loadp)
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75 } else {
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76 n_labels <- as.numeric(x_show_labels)
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77 }
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78 n_labels <- min( n_labels, (1 + length(loadp)) / 2 )
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79 labels_to_show <- c(
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80 names(head(sort(my_loadp),n = n_labels))
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81 , names(tail(sort(my_loadp),n = n_labels))
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82 )
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83 if ( x_show_loado_labels ) {
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84 labels_to_show <- c(
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85 labels_to_show
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86 , names(head(sort(my_loado),n = n_labels))
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87 , names(tail(sort(my_loado),n = n_labels))
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88 )
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89 }
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90 labels <- unname(sapply( X = tsv1$featureID, FUN = function(x) if( x %in% labels_to_show ) x else "" ))
0
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91 text(
2
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92 y = plus_cor - 0.013
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93 , x = plus_cov + 0.020
3
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94 , cex = 0.4
2
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95 , labels = labels
3
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96 , col = rgb(blue = 0, red = 0, green = 0, alpha = 0.5) # rgb(blue = blue, red = red, green = 0, alpha = 0.2 + 0.8 * alpha)
0
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97 , srt = -30 # slant 30 degrees downward
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98 , adj = 0 # left-justified
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99 )
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100 }
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101 }
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102 )
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103 typeVc <- c("correlation", # 1
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104 "outlier", # 2
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105 "overview", # 3
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106 "permutation", # 4
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107 "predict-train", # 5
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108 "predict-test", # 6
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109 "summary", # 7 = c(2,3,4,9)
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110 "x-loading", # 8
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111 "x-score", # 9
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112 "x-variance", # 10
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113 "xy-score", # 11
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114 "xy-weight" # 12
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115 ) # [c(3,8,9)] # [c(4,3,8,9)]
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116 if ( length(my_oplsda@orthoVipVn) > 0 ) {
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117 my_typevc <- typeVc[c(9,3,8)]
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118 } else {
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119 my_typevc <- c("(dummy)","overview","(dummy)")
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120 }
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121 for (my_type in my_typevc) {
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122 if (my_type %in% typeVc) {
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123 # print(sprintf("plotting type %s", my_type))
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124 plot(
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125 x = my_oplsda
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126 , typeVc = my_type
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127 , parCexN = 0.4
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128 , parDevNewL = FALSE
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129 , parLayL = TRUE
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130 , parEllipsesL = TRUE
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131 )
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132 } else {
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133 # print("plotting dummy graph")
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134 plot(x=1, y=1, xaxt="n", yaxt="n", xlab="", ylab="", type="n")
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135 text(x=1, y=1, labels="no orthogonal projection is possible")
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136 }
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137 }
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138 return (my_cor_vs_cov)
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139 } else {
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140 # x_progress(sprintf("x_is_match = %s, ncol(x_dataMatrix) = %d, length(unique(x_predictor)) = %d",x_is_match, ncol(x_dataMatrix), length(unique(x_predictor))))
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141 return (NULL)
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142 }
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143 }
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144
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145 # S-PLOT and OPLS reference: Wiklund_2008 doi:10.1021/ac0713510
1
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146 corcov_calc <- function(calc_env, failure_action = stop, progress_action = function(x){}, corcov_tsv_action = function(t){}, salience_tsv_action = function(t){}) {
0
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147 if ( ! is.environment(calc_env) ) {
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148 failure_action("corcov_calc: fatal error - 'calc_env' is not an environment")
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149 return ( FALSE )
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150 }
1
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151 if ( ! is.function(corcov_tsv_action) ) {
0
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152 failure_action("corcov_calc: fatal error - 'corcov_tsv_action' is not a function")
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153 return ( FALSE )
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154 }
1
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155 if ( ! is.function(salience_tsv_action) ) {
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156 failure_action("salience_calc: fatal error - 'salience_tsv_action' is not a function")
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157 return ( FALSE )
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158 }
0
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159
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160 # extract parameters from the environment
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161 vrbl_metadata <- calc_env$vrbl_metadata
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162 vrbl_metadata_names <- vrbl_metadata[,1]
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163 smpl_metadata <- calc_env$smpl_metadata
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164 data_matrix <- calc_env$data_matrix
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165 pairSigFeatOnly <- calc_env$pairSigFeatOnly
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166 facC <- calc_env$facC
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167 tesC <- calc_env$tesC
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168 # extract the levels from the environment
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169 originalLevCSV <- levCSV <- calc_env$levCSV
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170 # matchingC is one of { "none", "wildcard", "regex" }
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171 matchingC <- calc_env$matchingC
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172 labelFeatures <- calc_env$labelFeatures
2
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173 labelOrthoFeatures <- calc_env$labelOrthoFeatures
0
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174
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175 # arg/env checking
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176 if (!(facC %in% names(smpl_metadata))) {
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177 failure_action(sprintf("bad parameter! Factor name '%s' not found in sampleMetadata", facC))
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178 return ( FALSE )
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179 }
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180
2
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181 mz <- vrbl_metadata$mz
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182 names(mz) <- vrbl_metadata$variableMetadata
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183 mz_lookup <- function(feature) unname(mz[feature])
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184
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185 rt <- vrbl_metadata$rt
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186 names(rt) <- vrbl_metadata$variableMetadata
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187 rt_lookup <- function(feature) unname(rt[feature])
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188
0
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189 # calculate salience_df as data.frame(feature, max_level, max_median, max_rcv, mean_median, salience, salient_rcv)
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190 salience_df <- calc_env$salience_df <- w4msalience(
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191 data_matrix = data_matrix
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192 , sample_class = smpl_metadata[,facC]
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193 , failure_action = failure_action
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194 )
1
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195 salience_tsv_action({
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196 my_df <- data.frame(
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197 featureID = salience_df$feature
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198 , salientLevel = salience_df$max_level
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199 , salientRCV = salience_df$salient_rcv
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200 , salience = salience_df$salience
2
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201 , mz = mz_lookup(salience_df$feature)
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202 , rt = rt_lookup(salience_df$feature)
1
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203 )
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204 my_df[order(-my_df$salience),]
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205 })
2
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206
0
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207 # transform wildcards to regexen
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208 if (matchingC == "wildcard") {
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209 # strsplit(x = "hello,wild,world", split = ",")
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210 levCSV <- gsub("[.]", "[.]", levCSV)
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211 levCSV <- strsplit(x = levCSV, split = ",")
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212 levCSV <- sapply(levCSV, utils::glob2rx, trim.tail = FALSE)
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213 levCSV <- paste(levCSV, collapse = ",")
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214 }
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215 # function to determine whether level is a member of levCSV
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216 isLevelSelected <- function(lvl) {
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217 matchFun <- if (matchingC != "none") grepl else `==`
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218 return(
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219 Reduce(
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220 f = "||"
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221 , x = sapply(
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222 X = strsplit(
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223 x = levCSV
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224 , split = ","
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225 , fixed = TRUE
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226 )[[1]]
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227 , FUN = matchFun
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228 , lvl
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229 )
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230 )
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231 )
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232 }
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233
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234 # transpose matrix because ropls matrix is the transpose of XCMS matrix
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235 # Wiklund_2008 centers and pareto-scales data before OPLS-DA S-plot
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236 # center
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237 cdm <- center_colmeans(t(data_matrix))
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238 # pareto-scale
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239 my_scale <- sqrt(apply(cdm, 2, sd, na.rm=TRUE))
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240 scdm <- sweep(cdm, 2, my_scale, "/")
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241
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242 # pattern to match column names like k10_kruskal_k4.k3_sig
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243 col_pattern <- sprintf('^%s_%s_(.*)[.](.*)_sig$', facC, tesC)
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244 # column name like k10_kruskal_sig
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245 intersample_sig_col <- sprintf('%s_%s_sig', facC, tesC)
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246 # get the facC column from sampleMetadata, dropping to one dimension
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247 smpl_metadata_facC <- smpl_metadata[,facC]
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248
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249 # allocate a slot in the environment for the contrast_list, each element of which will be a data.frame with this structure:
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250 # - feature ID
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251 # - value1
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252 # - value2
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253 # - Wiklund_2008 correlation
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254 # - Wiklund_2008 covariance
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255 # - Wiklund_2008 VIP
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256 calc_env$contrast_list <- list()
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257
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258
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259 did_plot <- FALSE
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260 if (tesC != "none") {
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261 # for each column name, extract the parts of the name matched by 'col_pattern', if any
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262 the_colnames <- colnames(vrbl_metadata)
1
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263 if ( ! Reduce( f = "||", x = grepl(tesC, the_colnames) ) ) {
0
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264 failure_action(sprintf("bad parameter! variableMetadata must contain results of W4M Univariate test '%s'.", tesC))
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265 return ( FALSE )
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266 }
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267 col_matches <- lapply(
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268 X = the_colnames,
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269 FUN = function(x) {
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270 regmatches( x, regexec(col_pattern, x) )[[1]]
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271 }
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272 )
1
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273 ## first contrast each selected level with all other levels combined into one "super-level" ##
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274 # process columns matching the pattern
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275 level_union <- c()
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276 for (i in 1:length(col_matches)) {
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277 col_match <- col_matches[[i]]
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278 if (length(col_match) > 0) {
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279 # it's an actual match; extract the pieces, e.g., k10_kruskal_k4.k3_sig
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280 vrbl_metadata_col <- col_match[1] # ^^^^^^^^^^^^^^^^^^^^^ # Column name
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281 fctr_lvl_1 <- col_match[2] # ^^ # Factor-level 1
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282 fctr_lvl_2 <- col_match[3] # ^^ # Factor-level 2
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283 # only process this column if both factors are members of lvlCSV
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284 is_match <- isLevelSelected(fctr_lvl_1) && isLevelSelected(fctr_lvl_2)
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285 if (is_match) {
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286 level_union <- c(level_union, col_match[2], col_match[3])
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287 }
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288 }
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289 }
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290 level_union <- unique(sort(level_union))
2
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291 overall_significant <- 1 == ( if (intersample_sig_col %in% colnames(vrbl_metadata)) vrbl_metadata[,intersample_sig_col] else TRUE )
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292 if ( length(level_union) > 2 ) {
1
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293 chosen_samples <- smpl_metadata_facC %in% level_union
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294 chosen_facC <- as.character(smpl_metadata_facC[chosen_samples])
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295 col_selector <- vrbl_metadata_names[ overall_significant ]
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296 my_matrix <- scdm[ chosen_samples, col_selector, drop = FALSE ]
2
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297 plot_action <- function(fctr_lvl_1, fctr_lvl_2) {
1
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298 progress_action(sprintf("calculating/plotting contrast of %s vs. %s", fctr_lvl_1, fctr_lvl_2))
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299 predictor <- sapply( X = chosen_facC, FUN = function(fac) if ( fac == fctr_lvl_1 ) fctr_lvl_1 else fctr_lvl_2 )
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300 my_cor_cov <- do_detail_plot(
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301 x_dataMatrix = my_matrix
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302 , x_predictor = predictor
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303 , x_is_match = is_match
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304 , x_algorithm = algoC
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305 , x_prefix = if (pairSigFeatOnly) "Significantly contrasting features" else "Significant features"
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306 , x_show_labels = labelFeatures
2
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307 , x_show_loado_labels = labelOrthoFeatures
0
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308 , x_progress = progress_action
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309 , x_crossval_i = min(7, length(chosen_samples))
0
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310 , x_env = calc_env
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311 )
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312 if ( is.null(my_cor_cov) ) {
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313 progress_action("NOTHING TO PLOT.")
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314 } else {
2
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315 my_tsv <- my_cor_cov$tsv1
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316 my_tsv$mz <- mz_lookup(my_tsv$featureID)
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317 my_tsv$rt <- rt_lookup(my_tsv$featureID)
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318 my_tsv["level1Level2Sig"] <- vrbl_metadata[ match(my_tsv$featureID, vrbl_metadata_names), vrbl_metadata_col ]
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319 tsv <<- my_tsv
0
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320 corcov_tsv_action(tsv)
2
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321 did_plot <<- TRUE
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322 }
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323 }
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324 if ( length(level_union) != 2 ) {
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325 fctr_lvl_2 <- "other"
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326 for ( fctr_lvl_1 in level_union[1:length(level_union)] ) {
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327 plot_action(fctr_lvl_1, fctr_lvl_2)
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328 }
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329 } else {
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330 plot_action(fctr_lvl_1 = level_union[1], fctr_lvl_2 = level_union[2])
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331 }
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332 }
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333
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334 if ( length(level_union) > 1 ) {
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335 ## next, contrast each selected level with each of the other levels individually ##
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336 # process columns matching the pattern
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337 for (i in 1:length(col_matches)) {
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338 # for each potential match of the pattern
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339 col_match <- col_matches[[i]]
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340 if (length(col_match) > 0) {
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341 # it's an actual match; extract the pieces, e.g., k10_kruskal_k4.k3_sig
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342 vrbl_metadata_col <- col_match[1] # ^^^^^^^^^^^^^^^^^^^^^ # Column name
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343 fctr_lvl_1 <- col_match[2] # ^^ # Factor-level 1
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344 fctr_lvl_2 <- col_match[3] # ^^ # Factor-level 2
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345 # only process this column if both factors are members of lvlCSV
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346 is_match <- isLevelSelected(fctr_lvl_1) && isLevelSelected(fctr_lvl_2)
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347 progress_action(sprintf("calculating/plotting contrast of %s vs. %s", fctr_lvl_1, fctr_lvl_2))
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348 # TODO delete next line displaying currently-processed column
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349 # cat(sprintf("%s %s %s %s\n", vrbl_metadata_col, fctr_lvl_1, fctr_lvl_2, is_match))
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350 # choose only samples with one of the two factors for this column
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351 chosen_samples <- smpl_metadata_facC %in% c(fctr_lvl_1, fctr_lvl_2)
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352 predictor <- smpl_metadata_facC[chosen_samples]
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353 # extract only the significantly-varying features and the chosen samples
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354 fully_significant <- 1 == vrbl_metadata[,vrbl_metadata_col] * ( if (intersample_sig_col %in% colnames(vrbl_metadata)) vrbl_metadata[,intersample_sig_col] else TRUE )
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355 col_selector <- vrbl_metadata_names[ if ( pairSigFeatOnly ) fully_significant else overall_significant ]
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356 my_matrix <- scdm[ chosen_samples, col_selector, drop = FALSE ]
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357 my_cor_cov <- do_detail_plot(
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358 x_dataMatrix = my_matrix
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359 , x_predictor = predictor
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360 , x_is_match = is_match
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361 , x_algorithm = algoC
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362 , x_prefix = if (pairSigFeatOnly) "Significantly contrasting features" else "Significant features"
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363 , x_show_labels = labelFeatures
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364 , x_show_loado_labels = labelOrthoFeatures
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365 , x_progress = progress_action
4
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366 , x_crossval_i = min(7, length(chosen_samples))
2
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367 , x_env = calc_env
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368 )
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369 if ( is.null(my_cor_cov) ) {
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370 progress_action("NOTHING TO PLOT.")
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371 } else {
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372 tsv <- my_cor_cov$tsv1
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373 tsv$mz <- mz_lookup(tsv$featureID)
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374 tsv$rt <- rt_lookup(tsv$featureID)
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375 tsv["level1Level2Sig"] <- vrbl_metadata[ match(tsv$featureID, vrbl_metadata_names), vrbl_metadata_col ]
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376 corcov_tsv_action(tsv)
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377 did_plot <- TRUE
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378 }
0
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379 }
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380 }
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381 }
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382 } else { # tesC == "none"
1
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383 level_union <- unique(sort(smpl_metadata_facC))
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384 if ( length(level_union) > 1 ) {
2
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385 if ( length(level_union) > 2 ) {
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386 ## pass 1 - contrast each selected level with all other levels combined into one "super-level" ##
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387 completed <- c()
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388 lapply(
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389 X = level_union
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390 , FUN = function(x) {
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391 fctr_lvl_1 <- x[1]
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392 fctr_lvl_2 <- {
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393 if ( fctr_lvl_1 %in% completed )
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394 return("DUMMY")
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395 # strF(completed)
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396 completed <<- c(completed, fctr_lvl_1)
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397 setdiff(level_union, fctr_lvl_1)
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398 }
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399 chosen_samples <- smpl_metadata_facC %in% c(fctr_lvl_1, fctr_lvl_2)
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400 fctr_lvl_2 <- "other"
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401 # print( sprintf("sum(chosen_samples) %d, factor_level_2 %s", sum(chosen_samples), fctr_lvl_2) )
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402 progress_action(sprintf("calculating/plotting contrast of %s vs. %s", fctr_lvl_1, fctr_lvl_2))
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403 if (length(unique(chosen_samples)) < 1) {
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404 progress_action("NOTHING TO PLOT...")
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405 } else {
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406 chosen_facC <- as.character(smpl_metadata_facC[chosen_samples])
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407 predictor <- sapply( X = chosen_facC, FUN = function(fac) if ( fac == fctr_lvl_1 ) fctr_lvl_1 else fctr_lvl_2 )
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408 my_matrix <- scdm[ chosen_samples, , drop = FALSE ]
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409 # only process this column if both factors are members of lvlCSV
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410 is_match <- isLevelSelected(fctr_lvl_1)
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411 my_cor_cov <- do_detail_plot(
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412 x_dataMatrix = my_matrix
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413 , x_predictor = predictor
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414 , x_is_match = is_match
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415 , x_algorithm = algoC
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416 , x_prefix = "Features"
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417 , x_show_labels = labelFeatures
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418 , x_show_loado_labels = labelOrthoFeatures
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419 , x_progress = progress_action
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420 , x_crossval_i = min(7, length(chosen_samples))
2
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421 , x_env = calc_env
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422 )
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423 if ( is.null(my_cor_cov) ) {
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424 progress_action("NOTHING TO PLOT")
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425 } else {
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426 tsv <- my_cor_cov$tsv1
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427 tsv$mz <- mz_lookup(tsv$featureID)
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428 tsv$rt <- rt_lookup(tsv$featureID)
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429 corcov_tsv_action(tsv)
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430 did_plot <<- TRUE
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431 }
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432 }
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433 #print("baz")
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434 "dummy" # need to return a value; otherwise combn fails with an error
1
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435 }
2
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436 )
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437 }
1
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438 ## pass 2 - contrast each selected level with each of the other levels individually ##
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439 completed <- c()
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440 utils::combn(
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441 x = level_union
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442 , m = 2
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443 , FUN = function(x) {
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444 fctr_lvl_1 <- x[1]
e25fd8a13665 planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit bd26542b811de06c1a877337a2840a9f899c2b94
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445 fctr_lvl_2 <- x[2]
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446 chosen_samples <- smpl_metadata_facC %in% c(fctr_lvl_1, fctr_lvl_2)
e25fd8a13665 planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit bd26542b811de06c1a877337a2840a9f899c2b94
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447 # print( sprintf("sum(chosen_samples) %d, factor_level_2 %s", sum(chosen_samples), fctr_lvl_2) )
e25fd8a13665 planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit bd26542b811de06c1a877337a2840a9f899c2b94
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448 progress_action(sprintf("calculating/plotting contrast of %s vs. %s", fctr_lvl_1, fctr_lvl_2))
e25fd8a13665 planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit bd26542b811de06c1a877337a2840a9f899c2b94
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449 if (length(unique(chosen_samples)) < 1) {
e25fd8a13665 planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit bd26542b811de06c1a877337a2840a9f899c2b94
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450 progress_action("NOTHING TO PLOT...")
e25fd8a13665 planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit bd26542b811de06c1a877337a2840a9f899c2b94
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451 } else {
e25fd8a13665 planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit bd26542b811de06c1a877337a2840a9f899c2b94
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452 chosen_facC <- as.character(smpl_metadata_facC[chosen_samples])
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453 predictor <- chosen_facC
e25fd8a13665 planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit bd26542b811de06c1a877337a2840a9f899c2b94
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454 my_matrix <- scdm[ chosen_samples, , drop = FALSE ]
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455 # only process this column if both factors are members of lvlCSV
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456 is_match <- isLevelSelected(fctr_lvl_1) && isLevelSelected(fctr_lvl_2)
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457 my_cor_cov <- do_detail_plot(
e25fd8a13665 planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit bd26542b811de06c1a877337a2840a9f899c2b94
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458 x_dataMatrix = my_matrix
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459 , x_predictor = predictor
e25fd8a13665 planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit bd26542b811de06c1a877337a2840a9f899c2b94
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460 , x_is_match = is_match
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461 , x_algorithm = algoC
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462 , x_prefix = "Features"
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463 , x_show_labels = labelFeatures
2
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464 , x_show_loado_labels = labelOrthoFeatures
1
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465 , x_progress = progress_action
4
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466 , x_crossval_i = min(7, length(chosen_samples))
1
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467 , x_env = calc_env
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468 )
e25fd8a13665 planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit bd26542b811de06c1a877337a2840a9f899c2b94
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469 if ( is.null(my_cor_cov) ) {
e25fd8a13665 planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit bd26542b811de06c1a877337a2840a9f899c2b94
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470 progress_action("NOTHING TO PLOT")
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471 } else {
e25fd8a13665 planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit bd26542b811de06c1a877337a2840a9f899c2b94
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472 tsv <- my_cor_cov$tsv1
2
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473 tsv$mz <- mz_lookup(tsv$featureID)
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474 tsv$rt <- rt_lookup(tsv$featureID)
1
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475 corcov_tsv_action(tsv)
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476 did_plot <<- TRUE
e25fd8a13665 planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit bd26542b811de06c1a877337a2840a9f899c2b94
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477 }
e25fd8a13665 planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit bd26542b811de06c1a877337a2840a9f899c2b94
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478 }
e25fd8a13665 planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit bd26542b811de06c1a877337a2840a9f899c2b94
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479 #print("baz")
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480 "dummy" # need to return a value; otherwise combn fails with an error
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481 }
e25fd8a13665 planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit bd26542b811de06c1a877337a2840a9f899c2b94
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482 )
e25fd8a13665 planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit bd26542b811de06c1a877337a2840a9f899c2b94
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483 } else {
e25fd8a13665 planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit bd26542b811de06c1a877337a2840a9f899c2b94
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484 progress_action("NOTHING TO PLOT....")
e25fd8a13665 planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit bd26542b811de06c1a877337a2840a9f899c2b94
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485 }
0
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486 }
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487 if (!did_plot) {
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488 failure_action(sprintf("bad parameter! sampleMetadata must have at least two levels of factor '%s' matching '%s'", facC, originalLevCSV))
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489 return ( FALSE )
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490 }
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491 return ( TRUE )
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492 }
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493
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494 # Calculate data for correlation-versus-covariance plot
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495 # Adapted from:
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496 # Wiklund_2008 doi:10.1021/ac0713510
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497 # Galindo_Prieto_2014 doi:10.1002/cem.2627
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498 # https://github.com/HegemanLab/extra_tools/blob/master/generic_PCA.R
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499 cor_vs_cov <- function(matrix_x, ropls_x) {
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500 x_class <- class(ropls_x)
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501 if ( !( as.character(x_class) == "opls" ) ) { # || !( attr(class(x_class),"package") == "ropls" ) )
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502 stop( "cor_vs_cov: Expected ropls_x to be of class ropls::opls but instead it was of class ", as.character(x_class) )
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503 }
50a07adddfbd planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 52e588e19fe93d83d221710bb75559c5700ba637
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504 result <- list()
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505 # suppLs$algoC - Character: algorithm used - "svd" for singular value decomposition; "nipals" for NIPALS
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506 if ( ropls_x@suppLs$algoC == "nipals") {
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507 # Equations (1) and (2) from *Supplement to* Wiklund 2008, doi:10.1021/ac0713510
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508 mag <- function(one_dimensional) sqrt(sum(one_dimensional * one_dimensional))
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509 mag_xi <- sapply(X = 1:ncol(matrix_x), FUN = function(x) mag(matrix_x[,x]))
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510 score_matrix <- ropls_x@scoreMN
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511 score_matrix_transposed <- t(score_matrix)
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512 score_matrix_magnitude <- mag(score_matrix)
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513 result$covariance <- score_matrix_transposed %*% matrix_x / ( score_matrix_magnitude * score_matrix_magnitude )
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514 result$correlation <- score_matrix_transposed %*% matrix_x / ( score_matrix_magnitude * mag_xi )
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515 } else {
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516 # WARNING - untested code - I don't have test data to exercise this branch
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517 # Equations (1) and (2) from Wiklund 2008, doi:10.1021/ac0713510
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518 # scoreMN - Numerical matrix of x scores (T; dimensions: nrow(x) x predI) X = TP' + E; Y = TC' + F
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519 score_matrix <- ropls_x@scoreMN
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520 score_matrix_transposed <- t(score_matrix)
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521 cov_divisor <- nrow(matrix_x) - 1
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522 result$covariance <- sapply(
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523 X = 1:ncol(matrix_x)
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diff changeset
524 , FUN = function(x) score_matrix_transposed %*% matrix_x[,x] / cov_divisor
50a07adddfbd planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 52e588e19fe93d83d221710bb75559c5700ba637
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parents:
diff changeset
525 )
50a07adddfbd planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 52e588e19fe93d83d221710bb75559c5700ba637
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diff changeset
526 score_sd <- sapply(
50a07adddfbd planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 52e588e19fe93d83d221710bb75559c5700ba637
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diff changeset
527 X = 1:ncol(score_matrix)
50a07adddfbd planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 52e588e19fe93d83d221710bb75559c5700ba637
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diff changeset
528 , FUN = function(x) sd(score_matrix[,x])
50a07adddfbd planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 52e588e19fe93d83d221710bb75559c5700ba637
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diff changeset
529 )
50a07adddfbd planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 52e588e19fe93d83d221710bb75559c5700ba637
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parents:
diff changeset
530 # xSdVn - Numerical vector: variable standard deviations of the 'x' matrix
50a07adddfbd planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 52e588e19fe93d83d221710bb75559c5700ba637
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diff changeset
531 xSdVn <- ropls_x@xSdVn
50a07adddfbd planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 52e588e19fe93d83d221710bb75559c5700ba637
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diff changeset
532 result$correlation <- sapply(
50a07adddfbd planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 52e588e19fe93d83d221710bb75559c5700ba637
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parents:
diff changeset
533 X = 1:ncol(matrix_x)
50a07adddfbd planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 52e588e19fe93d83d221710bb75559c5700ba637
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parents:
diff changeset
534 , FUN = function(x) {
50a07adddfbd planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 52e588e19fe93d83d221710bb75559c5700ba637
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diff changeset
535 ( score_matrix_transposed / score_sd ) %*% ( matrix_x[,x] / (xSdVn[x] * cov_divisor) )
50a07adddfbd planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 52e588e19fe93d83d221710bb75559c5700ba637
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parents:
diff changeset
536 }
50a07adddfbd planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 52e588e19fe93d83d221710bb75559c5700ba637
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parents:
diff changeset
537 )
50a07adddfbd planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 52e588e19fe93d83d221710bb75559c5700ba637
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parents:
diff changeset
538 }
50a07adddfbd planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 52e588e19fe93d83d221710bb75559c5700ba637
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parents:
diff changeset
539 result$correlation <- result$correlation[1,,drop = TRUE]
50a07adddfbd planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 52e588e19fe93d83d221710bb75559c5700ba637
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parents:
diff changeset
540 result$covariance <- result$covariance[1,,drop = TRUE]
50a07adddfbd planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 52e588e19fe93d83d221710bb75559c5700ba637
eschen42
parents:
diff changeset
541
50a07adddfbd planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 52e588e19fe93d83d221710bb75559c5700ba637
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parents:
diff changeset
542 # Variant 4 of Variable Influence on Projection for OPLS from Galindo_Prieto_2014
50a07adddfbd planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 52e588e19fe93d83d221710bb75559c5700ba637
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parents:
diff changeset
543 # Length = number of features; labels = feature identifiers. (The same is true for $correlation and $covariance.)
50a07adddfbd planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 52e588e19fe93d83d221710bb75559c5700ba637
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parents:
diff changeset
544 result$vip4p <- as.numeric(ropls_x@vipVn)
50a07adddfbd planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 52e588e19fe93d83d221710bb75559c5700ba637
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parents:
diff changeset
545 result$vip4o <- as.numeric(ropls_x@orthoVipVn)
2
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diff changeset
546 result$loadp <- as.numeric(ropls_x@loadingMN)
a06344808ffc planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit ce5178ce51b80f242d24db555044e6afc530ac99
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547 result$loado <- as.numeric(ropls_x@orthoLoadingMN)
0
50a07adddfbd planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 52e588e19fe93d83d221710bb75559c5700ba637
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parents:
diff changeset
548 # get the level names
50a07adddfbd planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 52e588e19fe93d83d221710bb75559c5700ba637
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549 level_names <- sort(levels(as.factor(ropls_x@suppLs$y)))
2
a06344808ffc planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit ce5178ce51b80f242d24db555044e6afc530ac99
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diff changeset
550 fctr_lvl_1 <- level_names[1]
a06344808ffc planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit ce5178ce51b80f242d24db555044e6afc530ac99
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diff changeset
551 fctr_lvl_2 <- level_names[2]
0
50a07adddfbd planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 52e588e19fe93d83d221710bb75559c5700ba637
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552 feature_count <- length(ropls_x@vipVn)
2
a06344808ffc planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit ce5178ce51b80f242d24db555044e6afc530ac99
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diff changeset
553 result$level1 <- rep.int(x = fctr_lvl_1, times = feature_count)
a06344808ffc planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit ce5178ce51b80f242d24db555044e6afc530ac99
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diff changeset
554 result$level2 <- rep.int(x = fctr_lvl_2, times = feature_count)
0
50a07adddfbd planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 52e588e19fe93d83d221710bb75559c5700ba637
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diff changeset
555 # print(sprintf("sd(covariance) = %f; sd(correlation) = %f", sd(result$covariance), sd(result$correlation)))
50a07adddfbd planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 52e588e19fe93d83d221710bb75559c5700ba637
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556 superresult <- list()
50a07adddfbd planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 52e588e19fe93d83d221710bb75559c5700ba637
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diff changeset
557 if (length(result$vip4o) == 0) result$vip4o <- NA
2
a06344808ffc planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit ce5178ce51b80f242d24db555044e6afc530ac99
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diff changeset
558 greaterLevel <- sapply( X = result$correlation, FUN = function(my_corr) if ( my_corr < 0 ) fctr_lvl_1 else fctr_lvl_2 )
0
50a07adddfbd planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 52e588e19fe93d83d221710bb75559c5700ba637
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parents:
diff changeset
559 superresult$tsv1 <- data.frame(
50a07adddfbd planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 52e588e19fe93d83d221710bb75559c5700ba637
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parents:
diff changeset
560 featureID = names(ropls_x@vipVn)
50a07adddfbd planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 52e588e19fe93d83d221710bb75559c5700ba637
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parents:
diff changeset
561 , factorLevel1 = result$level1
50a07adddfbd planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 52e588e19fe93d83d221710bb75559c5700ba637
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diff changeset
562 , factorLevel2 = result$level2
2
a06344808ffc planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit ce5178ce51b80f242d24db555044e6afc530ac99
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parents: 1
diff changeset
563 , greaterLevel = greaterLevel
0
50a07adddfbd planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 52e588e19fe93d83d221710bb75559c5700ba637
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parents:
diff changeset
564 , correlation = result$correlation
50a07adddfbd planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 52e588e19fe93d83d221710bb75559c5700ba637
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parents:
diff changeset
565 , covariance = result$covariance
50a07adddfbd planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 52e588e19fe93d83d221710bb75559c5700ba637
eschen42
parents:
diff changeset
566 , vip4p = result$vip4p
50a07adddfbd planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 52e588e19fe93d83d221710bb75559c5700ba637
eschen42
parents:
diff changeset
567 , vip4o = result$vip4o
2
a06344808ffc planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit ce5178ce51b80f242d24db555044e6afc530ac99
eschen42
parents: 1
diff changeset
568 , loadp = result$loadp
a06344808ffc planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit ce5178ce51b80f242d24db555044e6afc530ac99
eschen42
parents: 1
diff changeset
569 , loado = result$loado
0
50a07adddfbd planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 52e588e19fe93d83d221710bb75559c5700ba637
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parents:
diff changeset
570 , row.names = NULL
50a07adddfbd planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 52e588e19fe93d83d221710bb75559c5700ba637
eschen42
parents:
diff changeset
571 )
50a07adddfbd planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 52e588e19fe93d83d221710bb75559c5700ba637
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parents:
diff changeset
572 rownames(superresult$tsv1) <- superresult$tsv1$featureID
50a07adddfbd planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 52e588e19fe93d83d221710bb75559c5700ba637
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parents:
diff changeset
573 superresult$covariance <- result$covariance
50a07adddfbd planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 52e588e19fe93d83d221710bb75559c5700ba637
eschen42
parents:
diff changeset
574 superresult$correlation <- result$correlation
50a07adddfbd planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 52e588e19fe93d83d221710bb75559c5700ba637
eschen42
parents:
diff changeset
575 superresult$vip4p <- result$vip4p
50a07adddfbd planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 52e588e19fe93d83d221710bb75559c5700ba637
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parents:
diff changeset
576 superresult$vip4o <- result$vip4o
2
a06344808ffc planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit ce5178ce51b80f242d24db555044e6afc530ac99
eschen42
parents: 1
diff changeset
577 superresult$loadp <- result$loadp
a06344808ffc planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit ce5178ce51b80f242d24db555044e6afc530ac99
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parents: 1
diff changeset
578 superresult$loado <- result$loado
0
50a07adddfbd planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 52e588e19fe93d83d221710bb75559c5700ba637
eschen42
parents:
diff changeset
579 superresult$details <- result
50a07adddfbd planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 52e588e19fe93d83d221710bb75559c5700ba637
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parents:
diff changeset
580 # #print(superresult$tsv1)
50a07adddfbd planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 52e588e19fe93d83d221710bb75559c5700ba637
eschen42
parents:
diff changeset
581 result$superresult <- superresult
50a07adddfbd planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 52e588e19fe93d83d221710bb75559c5700ba637
eschen42
parents:
diff changeset
582 # Include thise in case future consumers of this routine want to use it in currently unanticipated ways
50a07adddfbd planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 52e588e19fe93d83d221710bb75559c5700ba637
eschen42
parents:
diff changeset
583 result$oplsda <- ropls_x
50a07adddfbd planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 52e588e19fe93d83d221710bb75559c5700ba637
eschen42
parents:
diff changeset
584 result$predictor <- ropls_x@suppLs$y # in case future consumers of this routine want to use it in currently unanticipated ways
50a07adddfbd planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 52e588e19fe93d83d221710bb75559c5700ba637
eschen42
parents:
diff changeset
585 return (superresult)
50a07adddfbd planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 52e588e19fe93d83d221710bb75559c5700ba637
eschen42
parents:
diff changeset
586 }
50a07adddfbd planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 52e588e19fe93d83d221710bb75559c5700ba637
eschen42
parents:
diff changeset
587
50a07adddfbd planemo upload for repository https://github.com/HegemanLab/w4mcorcov_galaxy_wrapper/tree/master commit 52e588e19fe93d83d221710bb75559c5700ba637
eschen42
parents:
diff changeset
588