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comparison macros.xml @ 0:540a34575492 draft

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"planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/anndata/ commit dc9d19d1f902f3ed54009cd0e68c8518c284b856"
author iuc
date Mon, 06 Jan 2020 18:40:26 +0000
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children c215b77c1129
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-1:000000000000 0:540a34575492
1 <macros>
2 <token name="@VERSION@">0.6.22.post1</token>
3 <token name="@GALAXY_VERSION@">galaxy1</token>
4 <xml name="requirements">
5 <requirements>
6 <requirement type="package" version="@VERSION@">anndata</requirement>
7 <requirement type="package" version="2.0.17">loompy</requirement>
8 <requirement type="package" version="2.9.0">h5py</requirement>
9 <yield />
10 </requirements>
11 </xml>
12 <xml name="citations">
13 <citations>
14 <citation type="doi">10.1186/s13059-017-1382-0</citation>
15 </citations>
16 </xml>
17 <xml name="version_command">
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>
19 </xml>
20 <token name="@CMD@"><![CDATA[
21 cat '$script_file' &&
22 python '$script_file'
23 ]]>
24 </token>
25 <token name="@LOOMCMD@"><![CDATA[
26 mkdir ./output &&
27 mkdir ./attributes &&
28 python '$__tool_directory__/loompy_to_tsv.py' -f '${hd5_format.input}'
29 ]]>
30 </token>
31 <token name="@CMD_imports@"><![CDATA[
32 import anndata as ad
33 ]]>
34 </token>
35 <token name="@HELP@"><![CDATA[
36 **AnnData**
37
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.
39
40 AnnData stores a data matrix `X` together with annotations of observations `obs`, variables `var` and unstructured annotations `uns`.
41
42 .. image:: https://falexwolf.de/img/scanpy/anndata.svg
43
44
45 AnnData stores observations (samples) of variables (features) in the rows of a matrix. This is the convention of the modern classics
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
47 and machine learning packages in Python (statsmodels, scikit-learn).
48
49 More details on the `AnnData documentation
50 <https://anndata.readthedocs.io/en/latest/anndata.AnnData.html>`__
51
52
53 **Loom data**
54
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.
56
57 .. image:: https://linnarssonlab.org/loompy/_images/Loom_components.png
58
59
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
61 and cells, such as Name, Chromosome, Position (for genes), and Strain, Sex, Age (for cells).
62
63 ]]>
64 </token>
65 <xml name="params_chunk_X">
66 <conditional name="chunk">
67 <param name="info" type="select" label="How to select the chunk?">
68 <option value="random">Random chunk of defined size</option>
69 <option value="specified">Specified indices</option>
70 </param>
71 <when value="random">
72 <param name="size" type="integer" value="1000" label="Size of chunk to randomly select"/>
73 <param name="replace" type="boolean" truevalue="True" falsevalue="False" checked="true" label="Random sampling of indices with replacement?"/>
74 </when>
75 <when value="specified">
76 <param name="list" type="text" value="" label="List of comma-separated indices to return"/>
77 </when>
78 </conditional>
79 </xml>
80 </macros>