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date Thu, 20 May 2021 08:52:23 +0000
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1 <tool id="SPIA" name="SPIA (Signaling Pathway Impact Analysis)" version="0.1.0" >
2 <description>A method based on over-representation and signaling perturbation accumulation to analyze KEGG signaling pathways.</description>
3
4 <requirements>
5 <requirement type="package" version="1.20.3">r-getopt</requirement>
6 <requirement type="package" version="2.42.0">bioconductor-SPIA</requirement>
7 <requirement type="package" version="2.14.0">bioconductor-chipenrich.data</requirement>
8 </requirements>
9
10 <command detect_errors="exit_code"><![CDATA[
11 Rscript '$__tool_directory__/SPIA.R'
12 -D '$input_data'
13 -O '$organism'
14 -R '$sigP_output'
15
16 -P '$adv.P_value_threshold'
17
18 -N '$adv.Number_bootstrap'
19 -C '$adv.method_combine_pvalue'
20 #if $adv.plot_perturbation=="True":
21 -W
22 -L '$SPIA_Perturbation_Plots'
23 #end if
24
25 #if $adv.pathwayId !="":
26 -I '$adv.pathwayId'
27 #end if
28
29 ]]></command>
30
31 <inputs>
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"/>
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" />
34
35 <section name="adv" title="Advanced Options" expanded="false">
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"/>
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." />
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.">
39 <option value="fisher" selected="True">fisher</option>
40 <option value="norminv">norminv</option>
41 </param>
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." />
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."/>
44 </section>
45
46 </inputs>
47
48 <outputs>
49 <data name="sigP_output" format="csv" label="SPIA_enrich_kegg" />
50 <data format="pdf" name="SPIA_Perturbation_Plots" label="SPIA_Perturbation_Plots">
51 <filter>adv['plot_perturbation'] == True</filter>
52 </data>
53 </outputs>
54
55 <tests>
56 <test>
57 <param name="input_data" value="SPIA_input.csv" ftype="csv" />
58 <output name="sigP_output" file="x.csv" ftype="csv" />
59 </test>
60 </tests>
61
62 <help><![CDATA[
63
64 .. class:: infomark
65
66 **What it does**
67
68 SPIA (Signaling pathway impact analysis) combines the evidence obtained from the
69 classical enrichment analysis with a novel type of evidence, which measures the actual
70 perturbation on a given pathway under a given condition.
71
72 A bootstap procedure is used to assess the significance of the observed total pathway perturbation.
73
74 Then we can calculate a global pathway significance P-value, which combines the enrichment and perturbation P-values.
75
76 SPIA tool analyzes KEGG signaling pathways.
77
78 -------
79
80 =========
81 **Input**
82 =========
83
84 Basic options
85 --------------
86
87 **Input data**
88
89 The input data is a csv file, which includes the columns `ENTREZ`, `logFC` and `adj.P.Val`.
90 This file contains all genes of your dataset.
91
92 ====== ========== ======= ========== ========= ==== ========
93 logFC AveExpr t P.Value adj.P.Val B ENTREZ
94 ====== ========== ======= ========== ========= ==== ========
95 5.96 6.23 23.9 1.79e-17 9.78e-13 25.4 3491
96 5.14 7.49 17.4 1.56e-14 2.84e-10 21.0 2353
97 4.15 7.04 16.5 5.15e-14 7.04e-10 20.1 1958
98 2.43 9.59 14.1 1.29e-12 1.41e- 8 17.7 1843
99 1.53 8.22 11.0 1.69e-10 1.15e- 6 13.6 3725
100 1.43 5.33 10.5 4.27e-10 2.42e- 6 12.8 23645
101 ====== ========== ======= ========== ========= ==== ========
102
103 **Organism**
104
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.
106
107 ------
108
109 Advanced Options
110 -----------------
111
112 **P value threshold to select DEgenes**
113
114 Set a threshold value to define differentially expressed genes. Default is 0.05.
115
116 **Bootstrap iterations**
117
118 Number of bootstrap iterations used to compute the `pPERT` value. Should be larger than 100. A recommended value is 2000.
119
120 **Method to combine P values**
121
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.
123
124 **Plot perturbation**
125
126 If set to `Yes`, plots the gene perturbation accumulation vs log2 fold change for every gene on each pathway. Default is `No`.
127
128 **Pathway IDs -- default as NULL and analysis all pathway.**
129
130 if you want special one or more pathway to analysis, Input pathway id at here. for example: `03018, 03320`.
131
132 ------
133
134 ==========
135 **Output**
136 ==========
137
138 **CSV file**
139
140 This file contains the ranked pathways and various statistics:
141 - **Name** is the pathway name;
142 - **ID** is the pathway ID;
143 - **pSize** is the number of genes on the pathway;
144 - **NDE** is the number of DE genes per pathway;
145 - **tA** is the observed total perturbation accumulation in the pathway;
146 - **pNDE** is the probability to observe at least NDE genes on the pathway using a hypergeometric model;
147 - **pPERT** is the probability to observe a total accumulation more extreme than tA only by chance;
148 - **pG** is the p-value obtained by combining pNDE and pPERT;
149 - **pGFdr** and **pGFWER** are the False Discovery Rate and Bonferroni adjusted global p-values;
150 - **Status** gives the direction in which the pathway is perturbed (activated or inhibited).
151 - **KEGGLINK** gives a web link to the KEGG website that displays the pathway image with the differentially expressed genes highlighted in red.
152
153 **PDF file**
154
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.
156
157 ------
158
159 Please cite SPIA_ appropriately if you use them.
160
161 .. _SPIA: https://pubmed.ncbi.nlm.nih.gov/18990722/
162
163 ]]></help>
164
165 <citations>
166 <citation type="doi">10.1093/bioinformatics/btn577</citation>
167 </citations>
168
169 </tool>