diff macros.xml @ 0:c8e4d0b9ae8c draft

"planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/anndata/ commit dc9d19d1f902f3ed54009cd0e68c8518c284b856"
author iuc
date Mon, 06 Jan 2020 13:43:38 -0500
parents
children 81a28c2705b0
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--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/macros.xml	Mon Jan 06 13:43:38 2020 -0500
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+<macros>
+    <token name="@VERSION@">0.6.22.post1</token>
+    <token name="@GALAXY_VERSION@">galaxy1</token>
+    <xml name="requirements">
+        <requirements>
+            <requirement type="package" version="@VERSION@">anndata</requirement>
+            <requirement type="package" version="2.0.17">loompy</requirement>
+            <requirement type="package" version="2.9.0">h5py</requirement>
+            <yield />
+        </requirements>
+    </xml>
+    <xml name="citations">
+        <citations>
+            <citation type="doi">10.1186/s13059-017-1382-0</citation>
+        </citations>
+    </xml>
+    <xml name="version_command">
+        <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>
+    </xml>
+    <token name="@CMD@"><![CDATA[
+cat '$script_file' &&
+python '$script_file'
+    ]]>
+    </token>
+    <token name="@LOOMCMD@"><![CDATA[
+mkdir ./output &&
+mkdir ./attributes &&
+python '$__tool_directory__/loompy_to_tsv.py' -f '${hd5_format.input}'
+    ]]>
+    </token>
+    <token name="@CMD_imports@"><![CDATA[
+import anndata as ad
+    ]]>
+    </token>
+    <token name="@HELP@"><![CDATA[
+**AnnData**
+
+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.
+
+AnnData stores a data matrix `X` together with annotations of observations `obs`, variables `var` and unstructured annotations `uns`.
+
+.. image:: https://falexwolf.de/img/scanpy/anndata.svg
+
+
+AnnData stores observations (samples) of variables (features) in the rows of a matrix. This is the convention of the modern classics
+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
+and machine learning packages in Python (statsmodels, scikit-learn).
+
+More details on the `AnnData documentation
+<https://anndata.readthedocs.io/en/latest/anndata.AnnData.html>`__
+
+
+**Loom data**
+
+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.
+
+.. image:: https://linnarssonlab.org/loompy/_images/Loom_components.png
+
+
+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
+and cells, such as Name, Chromosome, Position (for genes), and Strain, Sex, Age (for cells).
+
+    ]]>
+    </token>
+    <xml name="params_chunk_X">
+        <conditional name="chunk">
+            <param name="info" type="select" label="How to select the chunk?">
+                <option value="random">Random chunk of defined size</option>
+                <option value="specified">Specified indices</option>
+            </param>
+            <when value="random">
+                <param name="size" type="integer" value="1000" label="Size of chunk to randomly select"/>
+                <param name="replace" type="boolean" truevalue="True" falsevalue="False" checked="true" label="Random sampling of indices with replacement?"/>
+            </when>
+            <when value="specified">
+                <param name="list" type="text" value="" label="List of comma-separated indices to return"/>
+            </when>
+        </conditional>
+    </xml>
+</macros>