Mercurial > repos > iuc > scanpy_remove_confounders
comparison remove_confounders.xml @ 11:73ab2ac53d06 draft
planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/scanpy/ commit aba2a85f5da6e1094f382d1f0d94c4b8f2544a7d
author | iuc |
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date | Wed, 08 Nov 2023 14:45:35 +0000 |
parents | bf2017df9837 |
children | 458e8f43a775 |
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10:bf2017df9837 | 11:73ab2ac53d06 |
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1 <tool id="scanpy_remove_confounders" name="Remove confounders" version="@galaxy_version@" profile="@profile@"> | 1 <tool id="scanpy_remove_confounders" name="Remove confounders" version="@galaxy_version@" profile="@profile@"> |
2 <description>with scanpy</description> | 2 <description>with scanpy</description> |
3 <expand macro="bio_tools"/> | |
4 <macros> | 3 <macros> |
5 <import>macros.xml</import> | 4 <import>macros.xml</import> |
6 </macros> | 5 </macros> |
6 <expand macro="bio_tools"/> | |
7 <expand macro="requirements"/> | 7 <expand macro="requirements"/> |
8 <command detect_errors="exit_code"><![CDATA[ | 8 <command detect_errors="exit_code"><![CDATA[ |
9 @CMD@ | 9 @CMD@ |
10 ]]></command> | 10 ]]></command> |
11 <configfiles> | 11 <configfiles> |
120 </inputs> | 120 </inputs> |
121 <outputs> | 121 <outputs> |
122 <expand macro="anndata_outputs"/> | 122 <expand macro="anndata_outputs"/> |
123 </outputs> | 123 </outputs> |
124 <tests> | 124 <tests> |
125 <test> | 125 <test expect_num_outputs="2"> |
126 <!-- test 0 --> | 126 <!-- test 0 --> |
127 <param name="adata" value="krumsiek11.h5ad" /> | 127 <param name="adata" value="krumsiek11.h5ad" /> |
128 <conditional name="method"> | 128 <conditional name="method"> |
129 <param name="method" value="pp.regress_out"/> | 129 <param name="method" value="pp.regress_out"/> |
130 <param name="keys" value="cell_type"/> | 130 <param name="keys" value="cell_type"/> |
138 <has_text_matching expression="keys=\['cell_type'\]"/> | 138 <has_text_matching expression="keys=\['cell_type'\]"/> |
139 </assert_contents> | 139 </assert_contents> |
140 </output> | 140 </output> |
141 <output name="anndata_out" file="pp.regress_out.krumsiek11.h5ad" ftype="h5ad" compare="sim_size"/> | 141 <output name="anndata_out" file="pp.regress_out.krumsiek11.h5ad" ftype="h5ad" compare="sim_size"/> |
142 </test> | 142 </test> |
143 <!--<test> | 143 <!--<test expect_num_outputs="2"> |
144 < test 2 > | 144 < test 2 > |
145 <param name="adata" value="krumsiek11.h5ad" /> | 145 <param name="adata" value="krumsiek11.h5ad" /> |
146 <conditional name="method"> | 146 <conditional name="method"> |
147 <param name="method" value="pp.mnn_correct"/> | 147 <param name="method" value="pp.mnn_correct"/> |
148 <param name="reg_keys" value="cell_type"/> | 148 <param name="reg_keys" value="cell_type"/> |
151 <has_text_matching expression="sc.pp.mnn_correct"/> | 151 <has_text_matching expression="sc.pp.mnn_correct"/> |
152 <has_text_matching expression="keys='cell_type'"/> | 152 <has_text_matching expression="keys='cell_type'"/> |
153 </assert_stdout> | 153 </assert_stdout> |
154 <output name="anndata_out" file="pp.mnn_correct.krumsiek11.h5ad" ftype="h5ad" compare="sim_size"/> | 154 <output name="anndata_out" file="pp.mnn_correct.krumsiek11.h5ad" ftype="h5ad" compare="sim_size"/> |
155 </test>--> | 155 </test>--> |
156 <test> | 156 <test expect_num_outputs="2"> |
157 <!-- test 1 --> | 157 <!-- test 1 --> |
158 <param name="adata" value="blobs.h5ad" /> | 158 <param name="adata" value="blobs.h5ad" /> |
159 <conditional name="method"> | 159 <conditional name="method"> |
160 <param name="method" value="pp.combat"/> | 160 <param name="method" value="pp.combat"/> |
161 <param name="key" value="blobs"/> | 161 <param name="key" value="blobs"/> |
178 | 178 |
179 Regress out unwanted sources of variation, using simple linear regression. This is | 179 Regress out unwanted sources of variation, using simple linear regression. This is |
180 inspired by Seurat's `regressOut` function in R. | 180 inspired by Seurat's `regressOut` function in R. |
181 | 181 |
182 More details on the `scanpy documentation | 182 More details on the `scanpy documentation |
183 <https://icb-scanpy.readthedocs-hosted.com/en/@version@/api/scanpy.pp.regress_out.html>`__ | 183 <https://icb-scanpy.readthedocs-hosted.com/en/stable/api/scanpy.pp.regress_out.html>`__ |
184 | 184 |
185 Correct batch effects by matching mutual nearest neighbors, using `pp.mnn_correct` | 185 Correct batch effects by matching mutual nearest neighbors, using `pp.mnn_correct` |
186 ================================================================================== | 186 ================================================================================== |
187 | 187 |
188 This uses the implementation of mnnpy. Depending on do_concatenate, it returns AnnData objects in the | 188 This uses the implementation of mnnpy. Depending on do_concatenate, it returns AnnData objects in the |
189 original order containing corrected expression values or a concatenated matrix or AnnData object. | 189 original order containing corrected expression values or a concatenated matrix or AnnData object. |
190 | 190 |
191 Be reminded that it is not advised to use the corrected data matrices for differential expression testing. | 191 Be reminded that it is not advised to use the corrected data matrices for differential expression testing. |
192 | 192 |
193 More details on the `scanpy documentation | 193 More details on the `scanpy documentation |
194 <https://icb-scanpy.readthedocs-hosted.com/en/@version@/api/scanpy.api.pp.mnn_correct.html>`__ | 194 <https://scanpy.readthedocs.io/en/stable/generated/scanpy.external.pp.mnn_correct.html>`__ |
195 | 195 |
196 | 196 |
197 Correct batch effects with ComBat function (`pp.combat`) | 197 Correct batch effects with ComBat function (`pp.combat`) |
198 ======================================================== | 198 ======================================================== |
199 | 199 |
200 Corrects for batch effects by fitting linear models, gains statistical power via an EB framework where information is borrowed across genes. This uses the implementation of ComBat | 200 Corrects for batch effects by fitting linear models, gains statistical power via an EB framework where information is borrowed across genes. This uses the implementation of ComBat |
201 | 201 |
202 More details on the `scanpy documentation | 202 More details on the `scanpy documentation |
203 <https://icb-scanpy.readthedocs-hosted.com/en/@version@/api/scanpy.pp.combat.html>`__ | 203 <https://icb-scanpy.readthedocs-hosted.com/en/stable/api/scanpy.pp.combat.html>`__ |
204 | 204 |
205 | 205 |
206 ]]></help> | 206 ]]></help> |
207 <expand macro="citations"/> | 207 <expand macro="citations"/> |
208 </tool> | 208 </tool> |