annotate macros.xml @ 4:70f5f1fee692 draft

"planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/anndata/ commit 41e70af176ea64ef0bd45a6e980e21bdba80e739"
author iuc
date Sat, 18 Jan 2020 03:37:23 -0500
parents 286a24ac079c
children b9fac48532eb
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1 <macros>
1
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2 <token name="@VERSION@">0.6.22.post1</token>
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3 <token name="@GALAXY_VERSION@">galaxy2</token>
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4 <xml name="requirements">
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5 <requirements>
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6 <requirement type="package" version="@VERSION@">anndata</requirement>
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7 <requirement type="package" version="2.0.17">loompy</requirement>
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8 <requirement type="package" version="2.9.0">h5py</requirement>
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9 <yield />
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10 </requirements>
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11 </xml>
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12 <xml name="citations">
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13 <citations>
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14 <citation type="doi">10.1186/s13059-017-1382-0</citation>
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15 </citations>
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16 </xml>
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17 <xml name="version_command">
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18 <version_command><![CDATA[python -c "import anndata as ad;print('anndata version: %s' % ad.__version__); import loompy;print('\nloompy version: %s' % loompy.__version__)"]]></version_command>
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19 </xml>
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20 <token name="@CMD@"><![CDATA[
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21 cat '$script_file' &&
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22 python '$script_file'
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23 ]]>
b2a6ce371781 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/anndata/ commit 2e16aca90c4fc6f13bd024eed43bc4adbf5967da
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24 </token>
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25 <token name="@LOOMCMD@"><![CDATA[
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26 mkdir ./output &&
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27 mkdir ./attributes &&
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28 python '$__tool_directory__/loompy_to_tsv.py' -f '${hd5_format.input}'
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29 ]]>
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30 </token>
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31 <token name="@CMD_imports@"><![CDATA[
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32 import anndata as ad
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33 ]]>
b2a6ce371781 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/anndata/ commit 2e16aca90c4fc6f13bd024eed43bc4adbf5967da
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34 </token>
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35 <token name="@HELP@"><![CDATA[
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36 **AnnData**
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37
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38 AnnData provides a scalable way of keeping track of data together with learned annotations. It is used within `Scanpy <https://github.com/theislab/scanpy>`__, for which it was initially developed.
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39
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40 AnnData stores a data matrix `X` together with annotations of observations `obs`, variables `var` and unstructured annotations `uns`.
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41
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42 .. image:: https://falexwolf.de/img/scanpy/anndata.svg
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44
3
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45 AnnData stores observations (samples) of variables (features) in the rows of a matrix. This is the convention of the modern classics
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46 of statistics (`Hastie et al., 2009 <https://web.stanford.edu/~hastie/ElemStatLearn/>`__) and machine learning (Murphy, 2012), the convention of dataframes both in R and Python and the established statistics
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47 and machine learning packages in Python (statsmodels, scikit-learn).
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48
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49 More details on the `AnnData documentation
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50 <https://anndata.readthedocs.io/en/latest/anndata.AnnData.html>`__
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51
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52
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53 **Loom data**
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54
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55 Loom files are an efficient file format for very large omics datasets, consisting of a main matrix, optional additional layers, a variable number of row and column annotations, and sparse graph objects.
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56
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57 .. image:: https://linnarssonlab.org/loompy/_images/Loom_components.png
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60 Loom files to store single-cell gene expression data: the main matrix contains the actual expression values (one column per cell, one row per gene); row and column annotations contain metadata for genes
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61 and cells, such as Name, Chromosome, Position (for genes), and Strain, Sex, Age (for cells).
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62
0
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63 ]]>
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64 </token>
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65 <xml name="params_chunk_X">
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66 <conditional name="chunk">
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67 <param name="info" type="select" label="How to select the chunk?">
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68 <option value="random">Random chunk of defined size</option>
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69 <option value="specified">Specified indices</option>
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70 </param>
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71 <when value="random">
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72 <param name="size" type="integer" value="1000" label="Size of chunk to randomly select"/>
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73 <param name="replace" type="boolean" truevalue="True" falsevalue="False" checked="true" label="Random sampling of indices with replacement?"/>
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74 </when>
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75 <when value="specified">
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76 <param name="list" type="text" value="" label="List of comma-separated indices to return"/>
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77 </when>
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78 </conditional>
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79 </xml>
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80 </macros>