Mercurial > repos > iuc > scanpy_cluster_reduce_dimension

changeset 5:6f2d2c7f77ee draft

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"planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/scanpy/ commit 6b5d0d6f038ebd0fae5dbca02ada51555518ed85"
author iuc
date Mon, 10 Feb 2020 05:27:02 -0500
parents 766be978777a
children 77b91b9bdf52
files cluster_reduce_dimension.xml
diffstat 1 files changed, 20 insertions(+), 20 deletions(-) [+]
line wrap: on
line diff
--- a/cluster_reduce_dimension.xml	Wed Dec 18 15:59:37 2019 -0500
+++ b/cluster_reduce_dimension.xml	Mon Feb 10 05:27:02 2020 -0500
@@ -1,5 +1,5 @@
-<tool id="scanpy_cluster_reduce_dimension" name="Cluster," version="@galaxy_version@" profile="@profile@">
-    <description>infer trajectories and embed with scanpy</description>
+<tool id="scanpy_cluster_reduce_dimension" name="Cluster, infer trajectories and embed" version="@galaxy_version@" profile="@profile@">
+    <description>with scanpy</description>
     <macros>
         <import>macros.xml</import>
         <xml name="pca_inputs">
@@ -540,8 +540,8 @@
 
 This requires to run `pp.neighbors`, first.
 
-More details on the `scanpy documentation
-<https://icb-scanpy.readthedocs-hosted.com/en/stable/api/scanpy.tl.louvain.html>`_
+More details on the `tl.louvain scanpy documentation
+<https://icb-scanpy.readthedocs-hosted.com/en/@version@/api/scanpy.tl.louvain.html>`_
 
 Cluster cells into subgroups (`tl.leiden`)
 ==========================================
@@ -550,24 +550,24 @@
 
 The Louvain algorithm has been proposed for single-cell analysis by Levine et al, 2015.
 
-More details on the `scanpy documentation
-<https://icb-scanpy.readthedocs-hosted.com/en/stable/api/scanpy.tl.leiden.html>`_
+More details on the `tl.leiden scanpy documentation
+<https://icb-scanpy.readthedocs-hosted.com/en/@version@/api/scanpy.tl.leiden.html>`_
 
 Computes PCA (principal component analysis) coordinates, loadings and variance decomposition, using `pp.pca`
 ============================================================================================================
 
 @CMD_pca_outputs@
 
-More details on the `scanpy documentation
-<https://icb-scanpy.readthedocs-hosted.com/en/stable/api/scanpy.pp.pca.html>`__
+More details on the `pp.pca scanpy documentation
+<https://icb-scanpy.readthedocs-hosted.com/en/@version@/api/scanpy.pp.pca.html>`__
 
 Computes PCA (principal component analysis) coordinates, loadings and variance decomposition, using `tl.pca`
 ============================================================================================================
 
 @CMD_pca_outputs@
 
-More details on the `scanpy documentation
-<https://icb-scanpy.readthedocs-hosted.com/en/stable/api/scanpy.tl.pca.html>`__
+More details on the `tl.pca scanpy documentation
+<https://icb-scanpy.readthedocs-hosted.com/en/@version@/api/scanpy.tl.pca.html>`__
 
 Diffusion Maps, using `tl.diffmap`
 ==================================
@@ -588,8 +588,8 @@
 observations annotation (obsm). It is the right eigen basis of the transition matrix with eigenvectors 
 as colum. It can be accessed using the inspect tool for AnnData
 
-More details on the `scanpy documentation
-<https://icb-scanpy.readthedocs-hosted.com/en/stable/api/scanpy.tl.diffmap.html>`__
+More details on the `tl.diffmap scanpy documentation
+<https://icb-scanpy.readthedocs-hosted.com/en/@version@/api/scanpy.tl.diffmap.html>`__
 
 t-distributed stochastic neighborhood embedding (tSNE), using `tl.tsne`
 =======================================================================
@@ -600,8 +600,8 @@
 
 It returns `X_tsne`, tSNE coordinates of data.
 
-More details on the `scanpy documentation
-<https://icb-scanpy.readthedocs-hosted.com/en/stable/api/scanpy.tl.tsne.html>`__
+More details on the `tl.tsne scanpy documentation
+<https://icb-scanpy.readthedocs-hosted.com/en/@version@/api/scanpy.tl.tsne.html>`__
 
 Embed the neighborhood graph using UMAP, using `tl.umap`
 ========================================================
@@ -620,8 +620,8 @@
 The UMAP coordinates of data are added to the return AnnData in the multi-dimensional 
 observations annotation (obsm). This data is accessible using the inspect tool for AnnData
 
-More details on the `scanpy documentation
-<https://icb-scanpy.readthedocs-hosted.com/en/stable/api/scanpy.tl.umap.html>`__
+More details on the `tl.umap scanpy documentation
+<https://icb-scanpy.readthedocs-hosted.com/en/@version@/api/scanpy.tl.umap.html>`__
 
 Force-directed graph drawing, using `tl.draw_graph`
 ===================================================
@@ -639,8 +639,8 @@
 The coordinates of graph layout are added to the return AnnData in the multi-dimensional 
 observations annotation (obsm). This data is accessible using the inspect tool for AnnData.
 
-More details on the `scanpy documentation
-<https://icb-scanpy.readthedocs-hosted.com/en/stable/api/scanpy.tl.draw_graph.html>`__
+More details on the `tl.draw_graph scanpy documentation
+<https://icb-scanpy.readthedocs-hosted.com/en/@version@/api/scanpy.tl.draw_graph.html>`__
 
 Infer progression of cells through geodesic distance along the graph (`tl.dpt`)
 ===============================================================================
@@ -669,7 +669,7 @@
 The tool is similar to the R package `destiny` of Angerer et al (2016).
 
 More details on the `tl.dpt scanpy documentation
-<https://icb-scanpy.readthedocs-hosted.com/en/stable/api/scanpy.tl.dpt.html>`_
+<https://icb-scanpy.readthedocs-hosted.com/en/@version@/api/scanpy.tl.dpt.html>`_
 
 
 Generate cellular maps of differentiation manifolds with complex topologies (`tl.paga`)
@@ -700,7 +700,7 @@
 These datasets are stored in the unstructured annotation (uns) and can be accessed using the inspect tool for AnnData objects
 
 More details on the `tl.paga scanpy documentation
-<https://icb-scanpy.readthedocs-hosted.com/en/stable/api/scanpy.tl.paga.html>`_
+<https://icb-scanpy.readthedocs-hosted.com/en/@version@/api/scanpy.tl.paga.html>`_
     ]]></help>
     <expand macro="citations"/>
 </tool>