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planemo upload for repository https://github.com/workflow4metabolomics/ascaw4m commit 7ea9b0f8abc5a60c2c04fd2098788497f14766b6
author marie-tremblay-metatoul
date Fri, 21 Sep 2018 05:51:14 -0400
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1 <tool id="asca" name="ASCA" version="1.0.0">
2 <description>Splitting of the total variance into independent blocks according to the experimental factors and multivariate analysis (SCA) of each block</description>
3
4 <requirements>
5 <requirement type="package" version="1.1_4">r-batch</requirement>
6 <requirement type="package" version="1.0">r-MetStaT</requirement>
7 <requirement type="package" version="1.70.0">bioconductor-pcamethods</requirement>
8 </requirements>
9
10 <stdio>
11 <exit_code range="1:" level="fatal" />
12 </stdio>
13
14 <command><![CDATA[
15 Rscript $__tool_directory__/asca_wrapper.R
16 dataMatrix_in "$dataMatrix_in"
17 sampleMetadata_in "$sampleMetadata_in"
18 variableMetadata_in "$variableMetadata_in"
19 factor1 "$factor1"
20 factor2 "$factor2"
21 scaling "$scaling"
22 nPerm "$nPerm"
23 threshold "$threshold"
24
25
26 sampleMetadata_out "$sampleMetadata_out"
27 variableMetadata_out "$variableMetadata_out"
28 figure "$figure"
29 information "$information"
30 ]]></command>
31
32 <inputs>
33 <param name="dataMatrix_in" type="data" label="Data matrix file" help="" format="tabular" />
34 <param name="sampleMetadata_in" type="data" label="Sample metadata file" help="" format="tabular" />
35 <param name="variableMetadata_in" type="data" label="Variable metadata file" help="" format="tabular" />
36 <param name="factor1" label="Name of the sampleMetadata column containing the 1st factor for A-SCA" type="text" value="none" help=""/>
37 <param name="factor2" label="Name of the sampleMetadata column containing the 2nd factor for A-SCA" type="text" value="none" help=""/>
38 <param name="scaling" label="Scaling to apply to dataMatrix" type="select" help="">
39 <option value="none" selected="true">None</option>
40 <option value="pareto">pareto</option>
41 <option value="uv">uv</option>
42 </param>
43 <param name="nPerm" label="Number of permutation to perform to compute factor significance" type="select" help="">
44 <option value="100" selected="true">100</option>
45 <option value="500">500</option>
46 <option value="1000">1000</option>
47 </param>
48 <param name="threshold" type="float" value="0.05" label="Threshold for factor significance (permutation test)" help="Must be between 0 and 1"/>
49 </inputs>
50
51 <outputs>
52 <data name="sampleMetadata_out" label="${tool.name}_${sampleMetadata_in.name}" format="tabular" ></data>
53 <data name="variableMetadata_out" label="${tool.name}_${variableMetadata_in.name}" format="tabular" ></data>
54 <data name="figure" label="${tool.name}_figure.pdf" format="pdf"/>
55 <data name="information" label="${tool.name}_information.txt" format="txt"/>
56 </outputs>
57
58 <tests>
59 <test>
60 <param name="dataMatrix_in" value="choo_datamatrix.txt"/>
61 <param name="sampleMetadata_in" value="choo_samplemetadata.txt"/>
62 <param name="variableMetadata_in" value="choo_variablemetadata.txt"/>
63 <param name="factor1" value="Date"/>
64 <param name="factor2" value="Treatment"/>
65 <param name="scaling" value="pareto"/>
66 <param name="threshold" value="0.05"/>
67 <param name="nPerm" value="1000"/>
68
69 <output name="sampleMetadata_out" file="ASCA_choo_samplemetadata.tsv" lines_diff="6"/>
70 </test>
71 </tests>
72
73
74 <help>
75
76 .. class:: infomark
77
78 **Tool updates**
79
80 See the **NEWS** section at the bottom of this page
81
82 ---------------------------------------------------
83
84 .. class:: infomark
85
86 **Authors** Marie Tremblay-Franco (W4M Core Development Team, MetaboHUB Toulouse, AXIOM) and Yann Guitton (W4M Core Development Team, Laberca, UM1329)
87
88 ---------------------------------------------------
89
90 .. class:: infomark
91
92 **References**
93 | R Core Team (2013). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria (http://www.r-project.org)
94 | Tim Dorscheidt (2013). MetStaT: Statistical metabolomics tools. R package version 1.0. https://CRAN.R-project.org/package=MetStaT
95 |
96
97 ============
98 A-SCA
99 ============
100
101 -----------
102 Description
103 -----------
104
105 | ASCA splits variance into independent blocks according to the experimental factors and performs multivariate analysis (SCA) of each block
106 |
107
108 -----------------
109 Workflow position
110 -----------------
111
112 .. image:: images/asca_workflowPositionImage.png
113 :width: 600
114
115
116 -----------
117 Input files
118 -----------
119
120 +----------------------------+---------+
121 | Parameter : num + label | Format |
122 +============================+=========+
123 | 1 : Data matrix file | tabular |
124 +----------------------------+---------+
125 | 2 : Sample metadata file | tabular |
126 +----------------------------+---------+
127 | 3 : Variable metadata file | tabular |
128 +----------------------------+---------+
129
130
131 | The **required formats** for the dataMatrix, sampleMetadata, and variableMetadata files are described in the **HowTo** entitled 'Format Data For Postprocessing' available on the main page of Workflow4Metabolomics.org (http://web11.sb-roscoff.fr/download/w4m/howto/w4m_HowToFormatDataForPostprocessing_v02.pdf)
132
133
134 ----------
135 Parameters
136 ----------
137
138 Data matrix file
139 | variable x sample **dataMatrix** tabular separated file of the numeric data matrix, with . as decimal, and NA for missing values; the table must not contain metadata apart from row and column names; the row and column names must be identical to the rownames of the sample and variable metadata, respectively (see below)
140 |
141
142 Sample metadata file
143 | sample x metadata **sampleMetadata** tabular separated file of the numeric and/or character sample metadata, with . as decimal and NA for missing values
144 |
145
146 Variable metadata file
147 | variable x metadata **variableMetadata** tabular separated file of the numeric and/or character variable metadata, with . as decimal and NA for missing values
148 |
149
150 Factor1
151 | Name of the sampleMetadata column containing the 1st factor for A-SCA
152 |
153
154 Factor2
155 | Name of the sampleMetadata column containing the 2nd factor for A-SCA
156 |
157
158 Scaling (default = none)
159 | Mean-centering followed either by pareto scaling (**pareto**), or unit-variance scaling (**UV**)
160 |
161
162 Permutation testing for A-SCA parameters: Number of permutations (default = 100)
163 | Number of random permutation on the results from ASCA. Calculate by repeating the ASCA analysis many times with permutated samples.
164 |
165
166 Threshold
167 | p-value significance threshold for permutation test
168 |
169
170 ------------
171 Output files
172 ------------
173
174 sampleMetadata_out.tabular
175 | sampleMetadata data file; may be identical to the input sampleMetadata in case no renaming of sample names nor re-ordering of samples (see the 'information' file for the presence/absence of modifications)
176 |
177
178 variableMetadata_out.tabular
179 | variableMetadata data file; may be identical to the input variableMetadata in case no renaming of variable names nor re-ordering of variables (see the 'information' file for the presence/absence of modifications)
180 |
181
182 figure.pdf
183 | Scree and score plots for significant parameter(s)
184 |
185
186 information.txt
187 | Text file with all messages when error(s) in formats are detected
188 |
189
190 ---------------------------------------------------
191
192 ---------------
193 Working example
194 ---------------
195
196 .. class:: infomark
197
198 | Data used in the following example comes from the Biosystems Data Analysis Group. They ayre included in the ASCA software(http://www.bdagroup.nl/content/Downloads/software/software.php).
199 | Two features were measured on 12 individuals, using a two factor-experimental design. The 1st factor has 2 levels and the 2nd factor has 3 levels.
200 |
201
202 Input files
203 -----------
204 +---------------------+----------+----------+----------+----------+----------+----------+----------+----------+----------+----------+----------+----------+
205 | Datamatrix | Ind1 | Ind2 | Ind3 | Ind4 | Ind5 | Ind6 | Ind7 | Ind8 | Ind9 | Ind10 | Ind11 | Ind12 |
206 +=====================+==========+==========+==========+==========+==========+==========+==========+==========+==========+==========+==========+==========+
207 | V1 | 1.00 | 3.00 | 2.00 | 1.00 | 2.00 | 2.00 | 4.00 | 6.00 | 5.00 | 5.00 | 6.00 | 5.00 |
208 +---------------------+----------+----------+----------+----------+----------+----------+----------+----------+----------+----------+----------+----------+
209 | V2 | 0.60 | 0.40 | 0.70 | 0.80 | 0.01 | 0.80 | 1.00 | 2.00 | 0.90 | 1.00 | 2.00 | 0.70 |
210 +---------------------+----------+----------+----------+----------+----------+----------+----------+----------+----------+----------+----------+----------+
211
212 ---------------------------------------------------
213
214 +--------------------+----------+----------+
215 | sampleMetadata | F1 | F2 |
216 +====================+==========+==========+
217 | Ind1 | 1 | 1 |
218 +--------------------+----------+----------+
219 | Ind2 | 1 | 1 |
220 +--------------------+----------+----------+
221 | Ind3 | 1 | 2 |
222 +--------------------+----------+----------+
223 | Ind4 | 1 | 2 |
224 +--------------------+----------+----------+
225 | Ind5 | 1 | 3 |
226 +--------------------+----------+----------+
227 | Ind6 | 1 | 3 |
228 +--------------------+----------+----------+
229 | Ind7 | 2 | 1 |
230 +--------------------+----------+----------+
231 | Ind8 | 2 | 1 |
232 +--------------------+----------+----------+
233 | Ind9 | 2 | 2 |
234 +--------------------+----------+----------+
235 | Ind10 | 2 | 2 |
236 +--------------------+----------+----------+
237 | Ind11 | 2 | 3 |
238 +--------------------+----------+----------+
239 | Ind11 | 2 | 3 |
240 +--------------------+----------+----------+
241
242 ---------------------------------------------------
243
244 +--------------------+----------+
245 | Variablemetadata | Number |
246 +====================+==========+
247 | V1 | 1 |
248 +--------------------+----------+
249 | V2 | 2 |
250 +--------------------+----------+
251
252 ---------------------------------------------------
253
254 Parameters
255 ----------
256 | Name of the sampleMetadata column containing the 1st factor for A-SCA: F1
257 | Name of the sampleMetadata column containing the 2nd factor for A-SCA: F2
258 | Scaling to apply to dataMatrix: none
259 | Number of permutation to perform to compute factor significance: 500
260 | Threshold for factor significance (permutation test): 0.05
261 |
262
263 Output files
264 ------------
265 | **1) Example of a ASCA_BDAGroup_ASCA_samplemetadata.tsv: tsv file** including PC1 and PC2 scores from F1 PCA, F2 PCA and F1xF2 PCA
266
267
268
269 +--------------------+----------+----------+-------------+-------------+-------------+-------------+-------------------+-------------------+
270 | sampleMetadata | F1 | F2 | F1_XSCOR-p1 | F1_XSCOR-p2 | F2_XSCOR-p1 | F2_XSCOR-p2 | Interact_XSCOR-p1 | Interact_XSCOR-p1 |
271 +====================+==========+==========+=============+=============+=============+=============+===================+===================+
272 | Ind1 | 1 | 1 | -2.66136390 | 0.307505352 | 0.986520075 | -0.25138715 | -0.31885686 | -0.77109078 |
273 +--------------------+----------+----------+-------------+-------------+-------------+-------------+-------------------+-------------------+
274 | Ind2 | 1 | 1 | -0.74779084 | -0.30750535 | -0.99758505 | 0.070057773 | 0.719240017 | 0.950058502 |
275 +--------------------+----------+----------+-------------+-------------+-------------+-------------+-------------------+-------------------+
276 | Ind3 | 1 | 2 | -1.22618411 | -0.15375267 | -0.24288670 | 0.124191016 | -0.00883820 | 0.465391498 |
277 +--------------------+----------+----------+-------------+-------------+-------------+-------------+-------------------+-------------------+
278
279
280
281 | **2) Example of a ASCA_BDAGroup_ASCA_variablemetadata.tsv: tsv file** including PC1 and PC2 loadings from F1 PCA, F2 PCA and F1xF2 PCA
282
283
284 +--------------------+----------+-------------+-------------+-------------+-------------+-------------------+--------------------+
285 | variableMetadata | Number | F1_XLOAD-p1 | F1_XLOAD-p2 | F2_XLOAD-p1 | F2_XLOAD-p2 | Interact_XLOAD-p1 | Interact_XLOAD-p1 |
286 +====================+==========+=============+=============+=============+=============+===================+====================+
287 | V1 | 1 | 0.977759467 | -0.20972940 | -0.99814337 | 0.060908126 | 0.428703939 | 0.903445035 |
288 +--------------------+----------+-------------+-------------+-------------+-------------+-------------------+--------------------+
289 | V2 | 2 | 0.977759467 | -0.30750535 | -0.06090812 | -0.99814337 | -0.90344503 | 0.428703939 |
290 +--------------------+----------+-------------+-------------+-------------+-------------+-------------------+--------------------+
291
292
293
294 | **3) Example of a ASCA_information.txt: txt file** including % of explained variance and p-value of permutation test
295
296
297 +----------------------+-------------------------+---------------------+
298 | ASCA_information.txt | % of explained variance | Permutation p-value |
299 +======================+=========================+=====================+
300 | F1 | 81.71 | 0.004 |
301 +----------------------+-------------------------+---------------------+
302 | F2 | 1.29 | 0.880 |
303 +----------------------+-------------------------+---------------------+
304 | Interaction | 1.33 | 0.962 |
305 +----------------------+-------------------------+---------------------+
306 | Residuals | 15.67 | - |
307 +----------------------+-------------------------+---------------------+
308
309
310 | **4) Example of ASCA_figure.pdf: pdf file** including Scree, Score plot and barplot of leverage values only for significant factor(s)/interaction**
311 | Leverage: importance of a variable in the PCA model (Nueda et al. 2007)
312
313
314 .. image:: BDAGroup_ASCA_figure.tif
315 :width: 600
316
317 ----
318 NEWS
319 ----
320
321
322 </help>
323
324 <citations>
325 <citation type="doi">10.1093/bioinformatics/bti476</citation>
326 <citation type="doi">10.1002/cem.952</citation>
327 <citation type="doi">10.1093/bioinformatics/btm251</citation>
328 </citations>
329
330 </tool>