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1 <tool id="SPIA" name="SPIA (Signaling Pathway Impact Analysis)" version="0.1.0" >
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2 <description>A method based on over-representation and signaling perturbation accumulation to analyze KEGG signaling pathways.</description>
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3
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4 <requirements>
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5 <requirement type="package" version="1.20.3">r-getopt</requirement>
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6 <requirement type="package" version="2.42.0">bioconductor-SPIA</requirement>
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7 <requirement type="package" version="2.14.0">bioconductor-chipenrich.data</requirement>
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8 </requirements>
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9
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10 <command detect_errors="exit_code"><![CDATA[
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11 Rscript '$__tool_directory__/SPIA.R'
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12 -D '$input_data'
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13 -O '$organism'
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14 -R '$sigP_output'
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15
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16 -P '$adv.P_value_threshold'
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17
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18 -N '$adv.Number_bootstrap'
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19 -C '$adv.method_combine_pvalue'
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20 #if $adv.plot_perturbation=="True":
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21 -W
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22 -L '$SPIA_Perturbation_Plots'
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23 #end if
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24
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25 #if $adv.pathwayId !="":
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26 -I '$adv.pathwayId'
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27 #end if
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28
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29 ]]></command>
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30
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31 <inputs>
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32 <param type="data" name="input_data" format="csv" multiple="false" label="Input data" help="A csv file including the columns ENTREZ, logFC, and adj.P.Val"/>
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33 <param type="text" name="organism" value="hsa" label="Organism" help="A three letter character designating the organism. Default is `hsa` (human). See a full list at https://www.genome.jp/kegg/catalog/org_list.html" />
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34
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35 <section name="adv" title="Advanced Options" expanded="false">
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36 <param type="float" name="P_value_threshold" label="P value threshold to select DEgenes" value="0.05" min="0.00" max="1.00" help="Set a threshold value to define differentially expressed genes"/>
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37 <param type="integer" name="Number_bootstrap" value="2000" min="100" label="Bootstrap iterations" help="Number of bootstrap iterations used to compute the P PERT value. Should be larger than 100. A recommended value is 2000." />
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38 <param type="select" name="method_combine_pvalue" label="Method to combine P values" help="Method used to combine the two types of p-values. If set to 'fisher' it will use Fisher's method. If set to 'norminv' it will use the normal inversion method.">
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39 <option value="fisher" selected="True">fisher</option>
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40 <option value="norminv">norminv</option>
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41 </param>
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42 <param type="boolean" name="plot_perturbation" truevalue="True" falsevalue="False" checked="False" label="Plot perturbation" help="If set to Yes, plot the gene perturbation accumulation vs log2 fold change for every gene on each pathway. Default is No." />
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43 <param type="text" name="pathwayId" value="" label="Pathway IDs -- default as NULL and analysis all pathway. " help="Special one or more pathway to analysis, input pathway ID at here. For example: 03018, 03320."/>
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44 </section>
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45
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46 </inputs>
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47
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48 <outputs>
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49 <data name="sigP_output" format="csv" label="SPIA_enrich_kegg" />
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50 <data format="pdf" name="SPIA_Perturbation_Plots" label="SPIA_Perturbation_Plots">
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51 <filter>adv['plot_perturbation'] == True</filter>
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52 </data>
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53 </outputs>
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54
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55 <tests>
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56 <test>
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57 <param name="input_data" value="SPIA_input.csv" ftype="csv" />
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58 <output name="sigP_output" file="x.csv" ftype="csv" />
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59 </test>
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60 </tests>
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61
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62 <help><![CDATA[
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63
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64 .. class:: infomark
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65
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66 **What it does**
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67
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68 SPIA (Signaling pathway impact analysis) combines the evidence obtained from the
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69 classical enrichment analysis with a novel type of evidence, which measures the actual
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70 perturbation on a given pathway under a given condition.
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71
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72 A bootstap procedure is used to assess the significance of the observed total pathway perturbation.
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73
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74 Then we can calculate a global pathway significance P-value, which combines the enrichment and perturbation P-values.
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75
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76 SPIA tool analyzes KEGG signaling pathways.
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77
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78 -------
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79
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80 =========
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81 **Input**
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82 =========
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83
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84 Basic options
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85 --------------
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86
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87 **Input data**
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88
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89 The input data is a csv file, which includes the columns `ENTREZ`, `logFC` and `adj.P.Val`.
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90 This file contains all genes of your dataset.
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91
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92 ====== ========== ======= ========== ========= ==== ========
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93 logFC AveExpr t P.Value adj.P.Val B ENTREZ
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94 ====== ========== ======= ========== ========= ==== ========
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95 5.96 6.23 23.9 1.79e-17 9.78e-13 25.4 3491
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96 5.14 7.49 17.4 1.56e-14 2.84e-10 21.0 2353
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97 4.15 7.04 16.5 5.15e-14 7.04e-10 20.1 1958
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98 2.43 9.59 14.1 1.29e-12 1.41e- 8 17.7 1843
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99 1.53 8.22 11.0 1.69e-10 1.15e- 6 13.6 3725
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100 1.43 5.33 10.5 4.27e-10 2.42e- 6 12.8 23645
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101 ====== ========== ======= ========== ========= ==== ========
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102
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103 **Organism**
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104
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105 A three letter word designating the organism of your data. Default is `hsa` (Human). See a full list of options at https://www.genome.jp/kegg/catalog/org_list.html.
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106
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107 ------
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108
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109 Advanced Options
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110 -----------------
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111
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112 **P value threshold to select DEgenes**
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113
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114 Set a threshold value to define differentially expressed genes. Default is 0.05.
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115
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116 **Bootstrap iterations**
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117
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118 Number of bootstrap iterations used to compute the `pPERT` value. Should be larger than 100. A recommended value is 2000.
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119
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120 **Method to combine P values**
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121
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122 Method used to combine the two types of p-values. If set to 'fisher' it will use Fisher's method. If set to 'norminv' it will use the normal inversion method.
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123
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124 **Plot perturbation**
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125
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126 If set to `Yes`, plots the gene perturbation accumulation vs log2 fold change for every gene on each pathway. Default is `No`.
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127
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128 **Pathway IDs -- default as NULL and analysis all pathway.**
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129
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130 if you want special one or more pathway to analysis, Input pathway id at here. for example: `03018, 03320`.
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131
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132 ------
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133
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134 ==========
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135 **Output**
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136 ==========
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137
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138 **CSV file**
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139
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140 This file contains the ranked pathways and various statistics:
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141 - **Name** is the pathway name;
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142 - **ID** is the pathway ID;
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143 - **pSize** is the number of genes on the pathway;
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144 - **NDE** is the number of DE genes per pathway;
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145 - **tA** is the observed total perturbation accumulation in the pathway;
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146 - **pNDE** is the probability to observe at least NDE genes on the pathway using a hypergeometric model;
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147 - **pPERT** is the probability to observe a total accumulation more extreme than tA only by chance;
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148 - **pG** is the p-value obtained by combining pNDE and pPERT;
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149 - **pGFdr** and **pGFWER** are the False Discovery Rate and Bonferroni adjusted global p-values;
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150 - **Status** gives the direction in which the pathway is perturbed (activated or inhibited).
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151 - **KEGGLINK** gives a web link to the KEGG website that displays the pathway image with the differentially expressed genes highlighted in red.
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152
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153 **PDF file**
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154
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155 If the plot argument is set to `Yes`, it will output the plots for the gene perturbation accumulation vs log2 fold change for every gene on each pathway.
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156
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157 ------
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158
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159 Please cite SPIA_ appropriately if you use them.
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160
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161 .. _SPIA: https://pubmed.ncbi.nlm.nih.gov/18990722/
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162
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163 ]]></help>
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164
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165 <citations>
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166 <citation type="doi">10.1093/bioinformatics/btn577</citation>
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167 </citations>
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168
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169 </tool>
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