Mercurial > repos > matces > carpet_toolsuite

annotate carpet-src-1/tools/CARPET/norm_rep.xml @ 0:cdd489d98766

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Migrated tool version 1.0.0 from old tool shed archive to new tool shed repository
author matces
date Tue, 07 Jun 2011 16:50:41 -0400
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0
cdd489d98766 Migrated tool version 1.0.0 from old tool shed archive to new tool shed repository
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1 <tool id="normalization" name="PreProcess for Tiling" version="1.0.0">
cdd489d98766 Migrated tool version 1.0.0 from old tool shed archive to new tool shed repository
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2 <description>normalizing data</description>
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3 <command interpreter="bash">r_wrapper2.sh $script_file</command>
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4
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5 <inputs>
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6 <param name="type" type="select" label="Normalization">
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7 <option value="bwm" selected="true">Bi-weight function</option>
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8 <option value="quantile">Quantile</option>
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9 <option value="none">None</option>
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10 </param>
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11 <param name="sum" type="select" label="Summarization">
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12 <option value="mean" selected="true">Mean</option>
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13 <option value="median">Median</option>
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14 <option value="none">None</option>
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15 </param>
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16 <repeat name="series" title="Chip">
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17 <param name="input" type="data" format="tabular" label="Dataset"/>
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18 <param name="header" type="select" label="Headers">
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19 <option value="T" selected="true">TRUE</option>
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20 <option value="F">FALSE</option>
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21 </param>
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22 <param name="chrom_col" type="data_column" data_ref="input" label="Column for chr value (chr1,etc)"/>
cdd489d98766 Migrated tool version 1.0.0 from old tool shed archive to new tool shed repository
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23 <param name="start_col" type="data_column" data_ref="input" label="Column for start position"/>
cdd489d98766 Migrated tool version 1.0.0 from old tool shed archive to new tool shed repository
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24
cdd489d98766 Migrated tool version 1.0.0 from old tool shed archive to new tool shed repository
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25 <conditional name="fine_col">
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26 <param name="si_o_no" type="select" label="End column">
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27 <option value="si_ce" selected="true">End column present</option>
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28 <option value="no_ce">End column NOT present</option>
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29 </param>
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30 <when value="si_ce">
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31 <param name="end_col" type="data_column" data_ref="input" label="Column for end position"/>
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32 </when>
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33 <when value="no_ce">
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34 <param name="end_col" type="text" value="50" size="4" label="average length of the probes"/>
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35 </when>
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36 </conditional>
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37
cdd489d98766 Migrated tool version 1.0.0 from old tool shed archive to new tool shed repository
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38 <conditional name="data">
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39 <param name="data_type" type="select" label="Data type">
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40 <option value="log" selected="true">log2(ratio)</option>
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41 <option value="no_log">one color raw data</option>
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42 <option value="raw">Cy3-Cy5 raw data</option>
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43 </param>
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44 <when value="log">
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45 <param name="value_col" type="data_column" data_ref="input" label="Column for log2(ratio)"/>
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46 <param name="value_col_cy3" type="text" value="NOT-NEEDED" size="12" label="Column for Cy3"/>
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47 <param name="value_col_cy5" type="text" value="NOT-NEEDED" size="12" label="Column for Cy5"/>
cdd489d98766 Migrated tool version 1.0.0 from old tool shed archive to new tool shed repository
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48 </when>
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49 <when value="no_log">
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50 <param name="value_col" type="data_column" data_ref="input" label="Column for raw data"/>
cdd489d98766 Migrated tool version 1.0.0 from old tool shed archive to new tool shed repository
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51 <param name="value_col_cy3" type="text" value="NOT-NEEDED" size="12" label="Column for Cy3"/>
cdd489d98766 Migrated tool version 1.0.0 from old tool shed archive to new tool shed repository
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52 <param name="value_col_cy5" type="text" value="NOT-NEEDED" size="12" label="Column for Cy5"/>
cdd489d98766 Migrated tool version 1.0.0 from old tool shed archive to new tool shed repository
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53 </when>
cdd489d98766 Migrated tool version 1.0.0 from old tool shed archive to new tool shed repository
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54 <when value="raw">
cdd489d98766 Migrated tool version 1.0.0 from old tool shed archive to new tool shed repository
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55 <param name="value_col" type="text" value="NOT-NEEDED" size="12" label="Column for log2(ratio)"/>
cdd489d98766 Migrated tool version 1.0.0 from old tool shed archive to new tool shed repository
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56 <param name="value_col_cy3" type="data_column" data_ref="input" label="Column for Cy3"/>
cdd489d98766 Migrated tool version 1.0.0 from old tool shed archive to new tool shed repository
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57 <param name="value_col_cy5" type="data_column" data_ref="input" label="Column for Cy5"/>
cdd489d98766 Migrated tool version 1.0.0 from old tool shed archive to new tool shed repository
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58 </when>
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59 </conditional>
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60 <param name="col" type="select" label="Line Color">
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61 <option value="1">Black</option>
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62 <option value="2">Red</option>
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63 <option value="3">Green</option>
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64 <option value="4">Blue</option>
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65 <option value="5">Cyan</option>
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66 <option value="6">Magenta</option>
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67 <option value="7">Yellow</option>
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68 <option value="8">Gray</option>
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69 </param>
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70 </repeat>
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71 </inputs>
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72
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73 <configfiles>
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74 <configfile name="script_file">
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75 ## Setup R error handling to go to stderr
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76 options( show.error.messages=F,
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77 error = function () { cat( geterrmessage(), file=stderr() ); q( "no", 1, F ) } )
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78 ## Determine range of all series in the plot
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79 options(scipen=999)
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80 ciccioo=library(Ringo)
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81 pdf( "${out_file1}" )
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82 xrange = c( NULL, NULL )
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83 xrange_norm = c( NULL, NULL )
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84 #for $i, $s in enumerate( $series )
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85 s${i} = read.table( "${s.input.file_name}",sep="\t",header=$s.header)
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86 #if $i == 0
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87 firma=matrix(c("GALAXY","CARPET"),length(s${i}[,${s.chrom_col}]),2,byrow=T)
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88 fine=matrix(c(".",".","Cesaroni_et_al."),length(s${i}[,${s.chrom_col}]),3,byrow=T)
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89
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90 if ("${s.fine_col.si_o_no}"== "no_ce"){
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91 coord_gff=cbind(as.character(s${i}[,${s.chrom_col}]),firma,s${i}[,${s.start_col}],as.numeric(s${i}[,${s.start_col}])+${s.fine_col.end_col})
cdd489d98766 Migrated tool version 1.0.0 from old tool shed archive to new tool shed repository
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92 }
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93 if ("${s.fine_col.si_o_no}"== "si_ce"){
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94 coord_gff=cbind(as.character(s${i}[,${s.chrom_col}]),firma,s${i}[,${s.start_col}],s${i}[,${s.fine_col.end_col}])
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95 }
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96 if ("${s.data.data_type}" == "raw") {
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97 totali=log2(as.numeric(s${i}[,${s.data.value_col_cy5}])/as.numeric(s${i}[,${s.data.value_col_cy3}]))
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98 }
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99 if ("${s.data.data_type}" == "log") {
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100 totali=s${i}[,${s.data.value_col}]
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101 }
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102 if ("${s.data.data_type}" == "no_log") {
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103 totali=log2(as.numeric(s${i}[,${s.data.value_col}]))
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104 }
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105
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106 #elif $i >0
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107 if ("${s.data.data_type}" == "raw") {
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108 totali=cbind(totali,log2(as.numeric(s${i}[,${s.data.value_col_cy5}])/as.numeric(s${i}[,${s.data.value_col_cy3}])))
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109 }
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110 if ("${s.data.data_type}" == "log") {
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111 totali=cbind(totali,s${i}[,${s.data.value_col}])
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112 }
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113 if ("${s.data.data_type}" == "no_log") {
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114 totali=cbind(totali,log2(as.numeric(s${i}[,${s.data.value_col}])))
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115 }
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116 #end if
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117 #end for
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118
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119
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120
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121 print (paste("number of chips =",$i+1,sep=" "),quote=F)
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122 tukey.biweight = function(x, c = 5, epsilon = 1e-04) {
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123 m = median(x)
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124 s = median(abs(x - m))
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125 u = (x - m)/(c * s + epsilon)
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126 w = rep(0, length(x))
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127 ii = abs(u) &lt;= 1
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128 w[ii] = ((1 - u^2)^2)[ii]
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129 t.bi = sum(w * x)/sum(w)
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130 return(t.bi)
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131 }
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132 totali=as.data.frame(totali)
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133 if ("${type}" == "bwm"){
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134 totali.tbw = apply(totali, 2, tukey.biweight)
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135 totali_norm = totali - matrix(totali.tbw, nrow = nrow(totali), ncol = ncol(totali), byrow = TRUE)
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136 for (i in 1:length(totali.tbw)){
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137 print(paste("bi-weight_mean rep",i,"=",format(totali.tbw[i],digits=3),sep=" "),quote=F)
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138 }
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139 }
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140 if ("${type}" == "quantile"){
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141 if (length(totali) == 1) {
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142 print ("Quantile normalization is not feasible with one sample",quote=F)
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143 q()
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144 }
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145 totali_norm=normalizeBetweenArrays(as.matrix(totali), method="quantile")
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146 }
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147 if ("${type}" == "none"){
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148 totali_norm=totali
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149 }
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150
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151 for (j in 1:length(as.data.frame(totali_norm)))
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152 xrange_norm=range(totali_norm[,j],xrange_norm)
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153
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154 for (jj in 1:length(totali))
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155 xrange=range(totali[,jj],xrange)
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156
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157 plot( NULL, type="n", xlim=xrange, ylim=c(0,1.2), main="Raw signal distribution", xlab="log2(ratio)",ylab="Density")
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158 ## Plot each series
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159 #for $i, $s in enumerate( $series )
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160 lines(density(totali[,${i}+1]), col="${s.col}" )
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161 #if $i == 0
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162 colori="${s.col}"
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163 #elif $i >0
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164 colori=rbind(colori,"${s.col}")
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165 #end if
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166 #end for
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167 legend((xrange[1]), 1.2,pch="-", col=as.vector(colori),legend=paste("rep",c(1:(${i}+1)),sep="_"))
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168
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169
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170 plot( NULL, type="n", xlim=xrange_norm, ylim=c(0,1.2), main="Normalized signal distribution", xlab="log2(ratio)",ylab="Density")
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171 ## Plot each series
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172 #for $i, $s in enumerate( $series )
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173 lines(density(totali_norm[,${i}+1]), col="${s.col}" )
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174 #end for
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175 legend((xrange_norm[1]), 1.2,pch="-", col=as.vector(colori),legend=paste("rep",c(1:(${i}+1)),"norm",sep="_"))
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176
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177
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178
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179 if (${i} > 0){
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180 corPlot(as.matrix(totali_norm),grouping=paste("rep",c(1:(${i}+1)),"norm",sep="_"))
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181 }
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182 devname = dev.off()
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183 totali_norm=as.data.frame(totali_norm)
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184 if ("${sum}" == "mean"){
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185 total_sum=apply(totali_norm,1,mean)
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186 }
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187 if ("${sum}" == "median"){
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188 total_sum=apply(totali_norm,1,median)
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189 }
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190 if ("${sum}" == "none"){
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191 total_sum=totali_norm
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192 }
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193 total_sum=round(total_sum,digits=3)
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194 total_gff=cbind(coord_gff,total_sum,fine)
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195 cazzolina=sub("CHR","chr",total_gff[,1])
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196 total_gff[,1]=as.vector(cazzolina)
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197 write.table(total_gff,"${out_file2}",sep="\t",quote=F,col.names=F,row.names=F)
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198
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199 </configfile>
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200 </configfiles>
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201
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202 <outputs>
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203 <data format="pdf" name="out_file1" />
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204 <data format="tabular" name="out_file2" />
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205 </outputs>
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206
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207 <help>
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208 .. class:: infomark
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209
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210 **What it does**
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211
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212 PPT normalizes single ChIP-chip or multi ChIP-chip experiments.
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213 PPT also compares the correlation between replicates and produces different plot to better understand the goodness of the experiment and creates a GFF file suitable for PeakPicker analysis.
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214
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215 PLEASE, for more detailed information refer to the CARPET user Manual:
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216 click to download_ it.
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217
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218 .. _download: /static/example_file/CARPET_userManual.zip
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219
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220 --------
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221
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222 **Parameters:**
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223
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224 - **Normalization:**
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225 - **Bi-weight function:** bi-weight function is used to scale all the chips (Standard Nimblegen normalization).
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226 - **Quantile:** quantile normalization is performed between all the chips.
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227 - **None:** no normalization is performed.
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228
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229 - **Summarization:**
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230 - **Mean:** the final value of each probe is the mean between all the chips.
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231 - **Median:** the final value of each probe is the median between all the chips.
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232 - **None:** all the values of each probe are given back.
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233 - **Chips:**
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234 - **Dataset:** input data file.
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235 - **Headers:** if headers are present or not in the dataset file.
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236 - **Column for chr value:** the column with the probe Chromosome numbers.
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237 - **Column for start position:** the column with the probe start positions.
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238 - **End column:** if the end position of the probes is present or not.
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239 - **Column for end position:** the column with the probe end positions.
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240 - **average length of the probes:** the average length of the probes (only for custom chip).
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241 - **Data type:** choose between log2(ratio) or raw value (NOT log trasformaed) or Cy3-Cy5 raw values according to data format.
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242 - **Column for log2(ratio):** the column with probe log2(ratio) values.
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243 - **Column for raw data:** the column with probe raw values (NOT log trasformed).
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244 - **Column for Cy3:** the column with probe Cy3 raw value.
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245 - **Column for Cy5:** the column with probe Cy5 raw value.
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246 - **Line Color:** the line colors for graphs create by the script.
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247
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248
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249
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250 -----
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251
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252 .. class:: warningmark
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253
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254 This tool requires at least the following fields in each file or dataset:
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255 - Chromosome number in this format : chr1 , chr2, etc etc.
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256 - Start position
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257 - one column with log2(ratio) or two columns with Cy3 and Cy5 raw values
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258
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259 --------
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260
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261
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262
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263 **INPUT FILE**
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264
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265 This tool accepts any kind of file, with at least the fields described above.
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266
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267 Click here (pair_file_) to download a Cy3-Cy5 pair file example.
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268
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269 .. _pair_file: /static/example_file/all_pair.txt.zip
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270
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271 Click here (raw_value_file_) to download an one color example.
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272
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273 .. _raw_value_file: /static/example_file/raw_value.txt.zip
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274
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275 Click here (GFF_file_) to download a GFF log2(ratio) file example.
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276
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277 .. _GFF_file: /static/example_file/log2ratio_file.txt.zip
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278
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279
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280 ---------
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281
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282 .. class:: infomark
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283
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284 **How does it work?**
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285
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286 For each chip the log2 of Cy5/Cy3 is calculated (if not already present).
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287 All the chips are then normalized, according to the type of normalization selected.
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288
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289 - **bi-weight** procedure scales all the probe log2ratio to center the data around zero. Scaling is performed by subtracting the bi-weight mean for the log2(ratio) values for all features on the array from each log2-ratio value.
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290 - **quantile** procedure normalizes the ditributions of the probe log2ratio of each chip with a quantile normalization.
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291
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292 Moreover, the correlations between chips are calculated and graphs are produced as shown in the following figures.
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293
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294 .. image:: static/images/CARPET/distribution.png
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295
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296 .. image:: static/images/CARPET/correlation.png
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297
cdd489d98766 Migrated tool version 1.0.0 from old tool shed archive to new tool shed repository
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298 The first two graphs are produced using the density function implemented in R.
cdd489d98766 Migrated tool version 1.0.0 from old tool shed archive to new tool shed repository
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299 The last graph is produced using the corPlot function implemented in Ringo package.
cdd489d98766 Migrated tool version 1.0.0 from old tool shed archive to new tool shed repository
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300 (The last graph is created only if more than one chip is uploaded.)
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301
cdd489d98766 Migrated tool version 1.0.0 from old tool shed archive to new tool shed repository
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302
cdd489d98766 Migrated tool version 1.0.0 from old tool shed archive to new tool shed repository
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303 **OUTPUT FILE**
cdd489d98766 Migrated tool version 1.0.0 from old tool shed archive to new tool shed repository
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304
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305 - If a summarization method is selected or only one chip is uploaded, a GFF file (ready to be used with PeakPicker) is created.
cdd489d98766 Migrated tool version 1.0.0 from old tool shed archive to new tool shed repository
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306 - if NO summarization methods are selected and more than one file is uploaded, the output will be like in the table below:
cdd489d98766 Migrated tool version 1.0.0 from old tool shed archive to new tool shed repository
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307
cdd489d98766 Migrated tool version 1.0.0 from old tool shed archive to new tool shed repository
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308 .. image:: static/images/CARPET/output_no_sum.png
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309 </help>
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310 </tool>