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planemo upload for repository https://github.com/bernt-matthias/mb-galaxy-tools/tree/master/tools/proteomicsr commit a73787be689a9af5641ff1b594c9a35d29093247-dirty
author mbernt
date Tue, 19 Dec 2023 15:50:51 +0000
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1 <tool id="proteomicsr_fc_workflow" name="proteomicsr: fold change workflow" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="21.05">
2 <macros>
3 <import>macros.xml</import>
4 </macros>
5 <expand macro="requirements"/>
6 <command detect_errors="exit_code"><![CDATA[
7 Rscript '$rscript'
8 && mv Rdata/dat_calculated.csv .
9 ]]></command>
10 <configfiles>
11 <configfile name="rscript"><![CDATA[
12 library(proteomicsr)
13
14 @READ_INPUTS@
15
16 null <- run_FC_workflow(
17 @COMMON_WF_PARAMETERS@
18 )
19 ]]></configfile>
20 </configfiles>
21 <inputs>
22 <expand macro="common_wf_paramerters"/>
23 <param name="out_select" type="select" multiple="true" optional="true" label="Optional outputs">
24 <option value="tables">Detailed tables</option>
25 <option value="plots">Plots</option>
26 </param>
27 </inputs>
28 <outputs>
29 <data name="dat_calculated" format="csv" from_work_dir="dat_calculated.csv"/>
30 <collection name="output" type="list" label="${tool.name} on ${on_string}: additional tables">
31 <discover_datasets pattern="__name_and_ext__" directory="Rdata"/>
32 <filter>out_select and "tables" in out_select</filter>
33 </collection>
34 <collection name="plots" type="list" label="${tool.name} on ${on_string}: plots">
35 <discover_datasets pattern="__name_and_ext__" directory="Plots"/>
36 <filter>out_select and "plots" in out_select</filter>
37 </collection>
38 </outputs>
39 <tests>
40 <test expect_num_outputs="1">
41 <param name="sampleTable" value="sampleTable.csv" ftype="csv"/>
42 <output name="dat_calculated" value="dat_calculated.csv">
43 <assert_contents>
44 <has_n_lines n="4269"/>
45 <has_n_columns sep="," n="35"/>
46 </assert_contents>
47 </output>
48 </test>
49 <test expect_num_outputs="3">
50 <param name="sampleTable" value="sampleTable.csv" ftype="csv"/>
51 <param name="out_select" value="tables,plots"/>
52 <output name="dat_calculated">
53 <assert_contents>
54 <has_n_lines n="4269"/>
55 <has_n_columns sep="," n="35"/>
56 </assert_contents>
57 </output>
58 <output_collection name="output" count="7" type="list">
59 <element name="Mahalanobis_Outliers" ftype="csv">
60 <assert_contents>
61 <has_n_lines n="25"/>
62 <has_n_columns sep="," n="3"/>
63 </assert_contents>
64 </element>
65 <element name="dat_log2" ftype="csv">
66 <assert_contents>
67 <has_n_lines n="5058"/>
68 <has_n_columns sep="," n="25"/>
69 </assert_contents>
70 </element>
71 <element name="dat_reliable" ftype="csv">
72 <assert_contents>
73 <has_n_lines n="4269"/>
74 <has_n_columns sep="," n="25"/>
75 </assert_contents>
76 </element>
77
78 </output_collection>
79 <output_collection name="plots" count="19" type="list"/>
80 </test>
81 <!-- tests with optional sampleGenes input -->
82 <test expect_num_outputs="3">
83 <param name="sampleTable" value="sampleTable.csv" ftype="csv"/>
84 <param name="sampleGenes" value="sampleGenes.csv" ftype="csv"/>
85 <param name="out_select" value="tables,plots"/>
86 <output name="dat_calculated">
87 <assert_contents>
88 <has_n_lines n="4269"/>
89 <has_n_columns sep="," n="35"/>
90 </assert_contents>
91 </output>
92 <output_collection name="output" count="9" type="list">
93 <element name="Mahalanobis_Outliers" ftype="csv">
94 <assert_contents>
95 <has_n_lines n="25"/>
96 <has_n_columns sep="," n="3"/>
97 </assert_contents>
98 </element>
99 <element name="dat_log2" ftype="csv">
100 <assert_contents>
101 <has_n_lines n="5058"/>
102 <has_n_columns sep="," n="25"/>
103 </assert_contents>
104 </element>
105 <element name="dat_reliable" ftype="csv">
106 <assert_contents>
107 <has_n_lines n="4269"/>
108 <has_n_columns sep="," n="25"/>
109 </assert_contents>
110 </element>
111
112 </output_collection>
113 <output_collection name="plots" count="19" type="list"/>
114 </test>
115 <!-- tests with both optional inputs -->
116 <test expect_num_outputs="3">
117 <param name="sampleTable" value="sampleTable.csv" ftype="csv"/>
118 <param name="sampleGenes" value="sampleGenes.csv" ftype="csv"/>
119 <param name="sampleMapping" value="sampleMapping.csv" ftype="csv"/>
120 <param name="out_select" value="tables,plots"/>
121 <output name="dat_calculated">
122 <assert_contents>
123 <has_n_lines n="4269"/>
124 <has_n_columns sep="," n="35"/>
125 </assert_contents>
126 </output>
127 <output_collection name="output" count="9" type="list">
128 <element name="Mahalanobis_Outliers" ftype="csv">
129 <assert_contents>
130 <has_n_lines n="25"/>
131 <has_n_columns sep="," n="3"/>
132 </assert_contents>
133 </element>
134 <element name="dat_log2" ftype="csv">
135 <assert_contents>
136 <has_n_lines n="5058"/>
137 <has_n_columns sep="," n="25"/>
138 </assert_contents>
139 </element>
140 <element name="dat_reliable" ftype="csv">
141 <assert_contents>
142 <has_n_lines n="4269"/>
143 <has_n_columns sep="," n="25"/>
144 </assert_contents>
145 </element>
146
147 </output_collection>
148 <output_collection name="plots" count="19" type="list"/>
149 </test>
150 </tests>
151 <help><![CDATA[
152
153 Fold change workflow
154
155 1. Evaluating data quality
156 2. Identification (and removal) of outliers (param: remove_outliers)
157 3. Log2 transformation
158 4. Optional: median normalization (param: median_normalize)
159 5. Filtering for reliably identified candidates (param: number_replicates_reliable, reliable_all_comparisons)
160 6. Principal component analysis of processed data
161 7. Calculation of average log2 fold changes and (adjusted) p-values (param: alternative, var.equal, paired, pvalue_adjustment)
162 8. Visualization of the results (param: pvalue_decision, significance_cutoff, color_up, color_none, color_down)
163
164 sampleMapping
165
166 A dataframe, which can be used to relate different
167 conditions to ggplot facets. The treatments, which should
168 also appear in the sampleTable, have to be the rownames. The
169 following columns should be present: "Xname" (the sample
170 name, which will be shown on the X-axis), "Order" (numbers
171 indicating the preferred order of the treatments/comparisons
172 on the X-axis - from left to right), Condition1 (character,
173 which will be used for the first level ggplot facet),
174 Condition2 (character, which will be used for the second
175 level ggplot facet). If no sampleMapping dataframe is
176 available, use sampleMapping = NULL, which is also the
177 default.
178 ]]></help>
179 <expand macro="citations"/>
180 </tool>