# HG changeset patch
# User iuc
# Date 1571221825 14400
# Node ID a89ee42625ada8b7d5038185b7272e23cff48bdf
# Parent  9ca360dde8e3c4a7aefebaa8b861c805d2843929
"planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/scanpy/ commit 8ef5f7c6f8728608a3f05bb51e11b642b84a05f5"

diff -r 9ca360dde8e3 -r a89ee42625ad README.md
--- a/README.md	Mon Mar 04 10:16:47 2019 -0500
+++ b/README.md	Wed Oct 16 06:30:25 2019 -0400
@@ -1,138 +1,115 @@
 Scanpy
 ======
 
-## Classification of methods into steps
+1. Inspect & Manipulate (`inspect.xml`)
 
-Steps:
+    Methods | Description
+    --- | ---
+    `pp.calculate_qc_metrics` | Calculate quality control metrics
+    `pp.neighbors` | Compute a neighborhood graph of observations
+    `tl.score_genes` | Score a set of genes
+    `tl.score_genes_cell_cycle` | Score cell cycle gene
+    `tl.rank_genes_groups` | Rank genes for characterizing groups
+    `tl.marker_gene_overlap` | Calculate an overlap score between data-deriven marker genes and provided markers (**not working for now**)
+    `pp.log1p` | Logarithmize the data matrix.
+    `pp.scale` | Scale data to unit variance and zero mean
+    `pp.sqrt` | Square root the data matrix
 
-1. Filtering
+2. Filter (`filter.xml`)
 
     Methods | Description
     --- | ---
     `pp.filter_cells` | Filter cell outliers based on counts and numbers of genes expressed.
     `pp.filter_genes` | Filter genes based on number of cells or counts.
-    `pp.filter_genes_dispersion` | Extract highly variable genes
+    `tl.filter_rank_genes_groups` | Filters out genes based on fold change and fraction of genes expressing the gene within and outside the groupby categories (**to fix**)
     `pp.highly_variable_genes` | Extract highly variable genes
     `pp.subsample` | Subsample to a fraction of the number of observations
-    `queries.gene_coordinates` | (Could not find...)
-    `queries.mitochondrial_genes` | Retrieves Mitochondrial gene symbols for specific organism through BioMart for filtering
-
-2. Quality Plots
-
-   These are in-between stages used to measure the effectiveness of a Filtering/Normalisation/Conf.Removal stage either after processing or prior to.
+    `pp.downsample_counts` | Downsample counts so that each cell has no more than target_counts
 
-    Methods | Description | Notes
-    --- | --- | ---
-    `pp.calculate_qc_metrics` | Calculate quality control metrics
-    `pl.violin` | violin plot of features, lib. size, or subsets of. 
-    `pl.stacked_violin` | Same as above but for multiple series of features or cells
-
-3. Normalization
+3. Normalize (`normalize.xml`)
 
     Methods | Description
     --- | ---
-    `pp.normalize_per_cell` | Normalize total counts per cell
+    `pp.normalize_total` | Normalize counts per cell
     `pp.recipe_zheng17` | Normalization and filtering as of [Zheng17]
     `pp.recipe_weinreb17` | Normalization and filtering as of [Weinreb17]
     `pp.recipe_seurat` | Normalization and filtering as of Seurat [Satija15]
-    `pp.log1p` | Logarithmize the data matrix.
-    `pp.scale` | Scale data to unit variance and zero mean
-    `pp.sqrt` | 
-    `pp.downsample_counts` | Downsample counts so that each cell has no more than target_counts
 
-4. Conf. removal
+4. Remove confounders (`remove_confounder.xml`)
 
     Methods | Description
     --- | ---
    `pp.regress_out` | Regress out unwanted sources of variation
    `pp.mnn_correct` | Correct batch effects by matching mutual nearest neighbors
-   `pp.dca` | Deep count autoencoder to denoise the data
-   `pp.magic` | Markov Affinity-based Graph Imputation of Cells (MAGIC) API to denoise
-   `tl.sim` | Simulate dynamic gene expression data [Wittman09]
-   `pp.calculate_qc_metrics` | Calculate quality control metrics
-   `tl.score_genes` | Score a set of genes
-   `tl.score_genes_cell_cycle` | Score cell cycle genes
-   `tl.cyclone` | Assigns scores and predicted class to observations based on cell-cycle genes [Scialdone15]
-   `tl.sandbag` | Calculates pairs of genes serving as markers for each cell-cycle phase [Scialdone15]
+   `pp.combat` | ComBat function for batch effect correction
 
-5. Clustering and Heatmaps
+5. Clustering, embedding and trajectory inference (`cluster_reduce_dimension.xml`)
 
     Methods | Description
     --- | ---
-    `tl.leiden` | Cluster cells into subgroups [Traag18] [Levine15]
-    `tl.louvain` | Cluster cells into subgroups [Blondel08] [Levine15] [Traag17]
+    `tl.louvain` | Cluster cells into subgroups
+    `tl.leiden` | Cluster cells into subgroups
     `tl.pca` | Principal component analysis
     `pp.pca` | Principal component analysis (appears to be the same func...)
     `tl.diffmap` | Diffusion Maps
     `tl.tsne` | t-SNE
     `tl.umap` | Embed the neighborhood graph using UMAP
-    `tl.phate` | PHATE
-    `pp.neighbors` | Compute a neighborhood graph of observations
-    `tl.rank_genes_groups` | Rank genes for characterizing groups
-    `pl.rank_genes_groups` | 
-    `pl.rank_genes_groups_dotplot` | 
-    `pl.rank_genes_groups_heatmap` | 
-    `pl.rank_genes_groups_matrixplot` | 
-    `pl.rank_genes_groups_stacked_violin` | 
-    `pl.rank_genes_groups_violin` | 
-    `pl.matrix_plot` | 
-    `pl.heatmap` | 
-    `pl.highest_expr_genes` | 
-    `pl.diffmap` | 
+    `tl.draw_graph` | Force-directed graph drawing
+    `tl.dpt` | Infer progression of cells through geodesic distance along the graph
+    `tl.paga` | Mapping out the coarse-grained connectivity structures of complex manifolds
+
+6. Plot (`plot.xml`)
+
+    1. Generic
+
+        Methods | Description
+        --- | ---
+        `pl.scatter` | Scatter plot along observations or variables axes
+        `pl.heatmap` | Heatmap of the expression values of set of genes
+        `pl.dotplot` | Makes a dot plot of the expression values
+        `pl.violin` | Violin plot
+        `pl.stacked_violin` | Stacked violin plots
+        `pl.matrixplot` | Heatmap of the mean expression values per cluster
+        `pl.clustermap` | Hierarchically-clustered heatmap
     
-6. Cluster Inspection and plotting
+    2. Preprocessing
 
-    Methods that draw out the clusters computed in the previous stage, not heatmap or pseudotime related.
+        Methods | Description
+        --- | ---
+        `pl.highest_expr_genes` | Plot the fraction of counts assigned to each gene over all cells
+        `pl.highly_variable_genes` | Plot dispersions versus means for genes
+
+    3. PCA
 
-    Methods | Description 
-    --- | --- 
-    `pl.clustermap` |
-    `pl.phate` | 
-    `pl.dotplot` | 
-    `pl.draw_graph` | (really general purpose, would not implement directly)
-    `pl.filter_genes_dispersion` | (depreciated for 'highly_variable_genes')
-    `pl.matrix` | (could not find in API)
-    `pl.pca` | 
-    `pl.pca_loadings` | 
-    `pl.pca_overview` | 
-    `pl.pca_variance_ratio` | 
-    `pl.ranking` | (not sure what this does...)
-    `pl.scatter` | ([very general purpose](https://icb-scanpy.readthedocs-hosted.com/en/latest/api/scanpy.api.pl.scatter.html), would not implement directly)
-    `pl.set_rcParams_defaults` | 
-    `pl.set_rcParams_scanpy` | 
-    `pl.sim` | 
-    `pl.tsne` | 
-    `pl.umap` | 
+        Methods | Description
+        --- | ---
+        `pl.pca` | Scatter plot in PCA coordinates
+        `pl.pca_loadings` | Rank genes according to contributions to PCs
+        `pl.pca_variance_ratio` | Scatter plot in PCA coordinates
+        `pl.pca_overview` | Plot PCA results
 
-7. Branch/Between-Cluster Inspection
+    4. Embeddings
 
-    Pseudotime analysis, relies on initial clustering.
+        Methods | Description
+        --- | ---
+        `pl.tsne` | Scatter plot in tSNE basis
+        `pl.umap` | Scatter plot in UMAP basis
+        `pl.diffmap` | Scatter plot in Diffusion Map basis
+        `pl.draw_graph` | Scatter plot in graph-drawing basis
 
-    Methods | Description
-    --- | ---
-    `tl.dpt` | Infer progression of cells through geodesic distance along the graph [Haghverdi16] [Wolf17i]
-    `pl.dpt_groups_pseudotime` | 
-    `pl.dpt_timeseries` | 
-    `tl.paga_compare_paths` | 
-    `tl.paga_degrees` | 
-    `tl.paga_expression_entropies` | 
-    `tl.paga` | Generate cellular maps of differentiation manifolds with complex topologies [Wolf17i]
-    `pl.paga` | 
-    `pl.paga_adjacency` | 
-    `pl.paga_compare` | 
-    `pl.paga_path` | 
-    `pl.timeseries` | 
-    `pl.timeseries_as_heatmap` | 
-    `pl.timeseries_subplot` | 
+    5. Branching trajectories and pseudotime, clustering
 
+        Methods | Description
+        --- | ---
+        `pl.dpt_groups_pseudotime` | Plot groups and pseudotime
+        `pl.dpt_timeseries` | Heatmap of pseudotime series
+        `pl.paga` | Plot the abstracted graph through thresholding low-connectivity edges
+        `pl.paga_compare` | Scatter and PAGA graph side-by-side
+        `pl.paga_path` | Gene expression and annotation changes along paths
 
-Methods to sort | Description
---- | --- 
-`tl.ROC_AUC_analysis` | (could not find in API)
-`tl.correlation_matrix` | (could not find in API)
-`rtools.mnn_concatenate` | (could not find in API)
-`utils.compute_association_matrix_of_groups` | (could not find in API) 
-`utils.cross_entropy_neighbors_in_rep` | (could not find in API)
-`utils.merge_groups` | (could not find in API)
-`utils.plot_category_association` | (could not find in API)
-`utils.select_groups` | (could not find in API)
\ No newline at end of file
+    6. Marker genes
+
+        Methods | Description
+        --- | ---
+        `pl.rank_genes_groups` | Plot ranking of genes using dotplot plot
+        `pl.rank_genes_groups_violin` | Plot ranking of genes for all tested comparisons
diff -r 9ca360dde8e3 -r a89ee42625ad README.rst
--- a/README.rst	Mon Mar 04 10:16:47 2019 -0500
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,105 +0,0 @@
-The different methods from Scanpy have been grouped by themes:
-
-1. Filter in `filter.xml`
-  - Filter cell outliers based on counts and numbers of genes expressed, using `pp.filter_cells`
-  - Filter genes based on number of cells or counts, using `pp.filter_genes`
-  - Extract highly variable genes, using `pp.filter_genes_dispersion`
-  - `tl.highly_variable_genes` (need to be added)
-  - Subsample to a fraction of the number of observations, using `pp.subsample`
-  - `queries.gene_coordinates` (need to be added)
-  - `queries.mitochondrial_genes` (need to be added)
-
-2. Normalize in `normalize.xml`
-  - Normalize total counts per cell, using `pp.normalize_per_cell`
-  - Normalization and filtering as of Zheng et al. (2017), using `pp.recipe_zheng17`
-  - Normalization and filtering as of Weinreb et al (2017), using `pp.recipe_weinreb17`
-  - Normalization and filtering as of Seurat et al (2015), using `pp.recipe_seurat`
-  - Logarithmize the data matrix, using `pp.log1p`
-  - Scale data to unit variance and zero mean, using `pp.scale`
-  - Square root the data matrix, using `pp.sqrt`
-  - Downsample counts, using `pp.downsample_counts`
-
-3. Remove confounder in `remove_confounders.xml`
-  - Regress out unwanted sources of variation, using `pp.regress_out`
-  - `pp.mnn_correct` (need to be added)
-  - `pp.mnn_correct` (need to be added)
-  - `pp.magic` (need to be added)
-  - `tl.sim` (need to be added)
-  - `pp.calculate_qc_metrics` (need to be added)
-  - Score a set of genes, using `tl.score_genes`
-  - Score cell cycle genes, using `tl.score_genes_cell_cycle`
-  - `tl.cyclone` (need to be added)
-  - `tl.andbag` (need to be added)
-
-4. Cluster and reduce dimension in `cluster_reduce_dimension.xml`
-  - `tl.leiden` (need to be added)
-  - Cluster cells into subgroups, using `tl.louvain`
-  - Computes PCA (principal component analysis) coordinates, loadings and variance decomposition, using `pp.pca`
-  - Computes PCA (principal component analysis) coordinates, loadings and variance decomposition, using `tl.pca`
-  - Diffusion Maps, using `tl.diffmap`
-  - t-distributed stochastic neighborhood embedding (tSNE), using `tl.tsne`
-  - Embed the neighborhood graph using UMAP, using `tl.umap`
-  - `tl.phate` (need to be added)
-  - Compute a neighborhood graph of observations, using `pp.neighbors`
-  - Rank genes for characterizing groups, using `tl.rank_genes_groups`
-
-4. Inspect
-  - `tl.paga_compare_paths` (need to be added)
-  - `tl.paga_degrees` (need to be added)
-  - `tl.paga_expression_entropies` (need to be added)
-  - Generate cellular maps of differentiation manifolds with complex topologies, using `tl.paga`
-  - Infer progression of cells through geodesic distance along the graph, using `tl.dpt`
-
-5. Plot
-  1. Generic
-    - Scatter plot along observations or variables axes, using `pl.scatter`
-    - Heatmap of the expression values of set of genes, using `pl.heatmap`
-    - Makes a dot plot of the expression values, using `pl.dotplot`
-    - Violin plot, using `pl.violin`
-    - `pl.stacked_violin` (need to be added)
-    - Heatmap of the mean expression values per cluster, using `pl.matrixplot`
-    - Hierarchically-clustered heatmap, using `pl.clustermap`
-    - `pl.ranking` 
-
-  2. Preprocessing
-    - Plot the fraction of counts assigned to each gene over all cells, using `pl.highest_expr_genes`
-    - Plot dispersions versus means for genes, using `pl.filter_genes_dispersion`
-    - `pl.highly_variable_genes` (need to be added)
-    - `pl.calculate_qc_metrics` (need to be added)
-  
-  3. PCA
-    - Scatter plot in PCA coordinates, using `pl.pca`
-    - Rank genes according to contributions to PCs, using `pl.pca_loadings`
-    - Scatter plot in PCA coordinates, using `pl.pca_variance_ratio`
-    - Plot PCA results, using `pl.pca_overview`
-  
-  4. Embeddings
-    - Scatter plot in tSNE basis, using `pl.tsne`
-    - Scatter plot in UMAP basis, using `pl.umap`
-    - Scatter plot in Diffusion Map basis, using `pl.diffmap`
-    - `pl.draw_graph` (need to be added)
-
-  5. Branching trajectories and pseudotime, clustering
-    - Plot groups and pseudotime, using `pl.dpt_groups_pseudotime`
-    - Heatmap of pseudotime series, using `pl.dpt_timeseries`
-    - Plot the abstracted graph through thresholding low-connectivity edges, using `pl.paga`
-    - `pl.paga_compare` (need to be added)
-    - `pl.paga_path` (need to be added)
-
-  6. Marker genes: 
-    - Plot ranking of genes using dotplot plot, using `pl.rank_gene_groups`
-    - `pl.rank_genes_groups_dotplot` (need to be added)
-    - `pl.rank_genes_groups_heatmap` (need to be added)
-    - `pl.rank_genes_groups_matrixplot` (need to be added)
-    - `pl.rank_genes_groups_stacked_violin` (need to be added)
-    - `pl.rank_genes_groups_violin` (need to be added)
-
-  7. Misc
-    - `pl.phate` (need to be added)
-    - `pl.matrix` (need to be added)
-    - `pl.paga_adjacency` (need to be added)
-    - `pl.timeseries` (need to be added)
-    - `pl.timeseries_as_heatmap` (need to be added)
-    - `pl.timeseries_subplot` (need to be added)
-    
-  
\ No newline at end of file
diff -r 9ca360dde8e3 -r a89ee42625ad macros.xml
--- a/macros.xml	Mon Mar 04 10:16:47 2019 -0500
+++ b/macros.xml	Wed Oct 16 06:30:25 2019 -0400
@@ -1,10 +1,12 @@
 <macros>
-    <token name="@version@">1.4</token>
+    <token name="@version@">1.4.4</token>
     <token name="@galaxy_version@"><![CDATA[@version@+galaxy0]]></token>
     <xml name="requirements">
         <requirements>
             <requirement type="package" version="@version@">scanpy</requirement>
             <requirement type="package" version="2.0.17">loompy</requirement>
+            <requirement type="package" version="2.9.0">h5py</requirement>
+            <requirement type="package" version="0.7.0">leidenalg</requirement>
             <yield />
         </requirements>
     </xml>
@@ -14,102 +16,33 @@
         </citations>
     </xml>
     <xml name="version_command">
-        <version_command><![CDATA[python -c "import scanpy.api as sc;print('scanpy version: %s' % sc.__version__)"]]></version_command>
+        <version_command><![CDATA[python -c "import scanpy as sc;print('scanpy version: %s' % sc.__version__)"]]></version_command>
     </xml>
     <token name="@CMD@"><![CDATA[
+cp '$adata' 'anndata.h5ad' &&
 cat '$script_file' &&
-python '$script_file'
+python '$script_file' &&
+ls .
     ]]>
     </token>
     <token name="@CMD_imports@"><![CDATA[
-import scanpy.api as sc
+import scanpy as sc
 import pandas as pd
 import numpy as np
     ]]>
     </token>
     <xml name="inputs_anndata">
-        <conditional name="input">
-            <param name="format" type="select" label="Format for the annotated data matrix">
-                <option value="loom">loom</option>
-                <option value="h5ad">h5ad-formatted hdf5 (anndata)</option>
-            </param>
-            <when value="loom">
-                <param name="adata" type="data" format="loom" label="Annotated data matrix"/>
-                <param name="sparse" type="boolean" truevalue="True" falsevalue="False" checked="true" label="Is the data matrix to read sparse?"/>
-                <param name="cleanup" type="boolean" truevalue="True" falsevalue="False" checked="false" label="Cleanup?"/>
-                <param name="x_name" type="text" value="spliced" label="X_name"/>
-                <param name="obs_names" type="text" value="CellID" label="obs_names"/>
-                <param name="var_names" type="text" value="Gene" label="var_names"/>
-            </when>
-            <when value="h5ad">
-                <param name="adata" type="data" format="h5" label="Annotated data matrix"/>
-            </when>
-        </conditional>
+        <param name="adata" type="data" format="h5ad" label="Annotated data matrix"/>
     </xml>
     <token name="@CMD_read_inputs@"><![CDATA[
-#if $input.format == 'loom'
-adata = sc.read_loom(
-    '$input.adata',
-    sparse=$input.sparse,
-    cleanup=$input.cleanup,
-    X_name='$input.x_name',
-    obs_names='$input.obs_names',
-    var_names='$input.var_names')
-#else if $input.format == 'h5ad'
-adata = sc.read_h5ad('$input.adata')
-#end if
+adata = sc.read('anndata.h5ad')
 ]]>
     </token>
-    <xml name="anndata_output_format">
-        <param name="anndata_output_format" type="select" label="Format to write the annotated data matrix">
-            <option value="loom">loom</option>
-            <option value="h5ad">h5ad-formatted hdf5 (anndata)</option>
-        </param>
-    </xml>
-    <xml name="anndata_modify_output_input">
-        <conditional name="modify_anndata">
-            <param name="modify_anndata" type="select" label="Return modify annotate data matrix?">
-                <option value="true">Yes</option>
-                <option value="false">No</option>
-            </param>
-            <when value="true">
-                <expand macro="anndata_output_format"/>
-            </when>
-            <when value="false"/>
-        </conditional>
-    </xml>
     <xml name="anndata_outputs">
-        <data name="anndata_out_h5ad" format="h5" from_work_dir="anndata.h5ad" label="${tool.name} on ${on_string}: Annotated data matrix">
-            <filter>anndata_output_format == 'h5ad'</filter>
-        </data>
-        <data name="anndata_out_loom" format="loom" from_work_dir="anndata.loom" label="${tool.name} on ${on_string}: Annotated data matrix">
-            <filter>anndata_output_format == 'loom'</filter>
-        </data>
-    </xml>
-    <xml name="anndata_modify_outputs">
-        <data name="anndata_out_h5ad" format="h5" from_work_dir="anndata.h5ad" label="${tool.name} on ${on_string}: Annotated data matrix">
-            <filter>modify_anndata['modify_anndata'] == 'true' and modify_anndata['anndata_output_format'] == 'h5ad'</filter>
-        </data>
-        <data name="anndata_out_loom" format="loom" from_work_dir="anndata.loom" label="${tool.name} on ${on_string}: Annotated data matrix">
-            <filter>modify_anndata['modify_anndata'] == 'true' and modify_anndata['anndata_output_format'] == 'loom'</filter>
-        </data>
+        <data name="anndata_out" format="h5ad" from_work_dir="anndata.h5ad" label="${tool.name} (${method.method}) on ${on_string}: Annotated data matrix"/>
     </xml>
     <token name="@CMD_anndata_write_outputs@"><![CDATA[
-#if $anndata_output_format == 'loom'
-adata.write_loom('anndata.loom')
-#else if $anndata_output_format == 'h5ad'
 adata.write('anndata.h5ad')
-#end if
-]]>
-    </token>
-    <token name="@CMD_anndata_write_modify_outputs@"><![CDATA[
-#if $modify_anndata.modify_anndata == 'true'
-    #if $modify_anndata.anndata_output_format == 'loom'
-adata.write_loom('anndata.loom')
-    #elif $modify_anndata.anndata_output_format == 'h5ad'
-adata.write('anndata.h5ad')
-    #end if
-#end if
 ]]>
     </token>
     <xml name="svd_solver">
@@ -423,7 +356,7 @@
         <param argument="use_raw" type="boolean" truevalue="True" falsevalue="False" checked="false" label="Use `raw` attribute of input if present" help=""/>
     </xml>
     <xml name="param_log">
-        <param argument="log" type="boolean" truevalue="True" falsevalue="False" checked="false" label="Use the log of the values?" help=""/>
+        <param argument="log" type="boolean" truevalue="True" falsevalue="False" checked="false" label="Use the log of the values?"/>
     </xml>
     <xml name="pl_figsize">
         <conditional name="figsize">
@@ -473,7 +406,7 @@
         <param argument="layer" type="text" value="" label="Name of the AnnData object layer that wants to be plotted" help="By default `adata.raw.X` is plotted. If `use_raw=False` is set, then `adata.X` is plotted. If layer is set to a valid layer name, then the layer is plotted. layer takes precedence over `use_raw`."/>
     </xml>
     <token name="@CMD_param_plot_inputs@"><![CDATA[
-    adata=adata,
+    adata,
     save='.$format',
     show=False,
     ]]></token>
@@ -512,9 +445,6 @@
         #end for
     var_group_positions=$var_group_positions,
     var_group_labels=$var_group_labels,
-    #else
-    var_group_positions=None,
-    var_group_labels=None,
     #end if
 #if $method.var_group_rotation
     var_group_rotation=$method.var_group_rotation,
@@ -729,44 +659,42 @@
     linewidths=$method.matplotlib_pyplot_scatter.linewidths,
     edgecolors='$method.matplotlib_pyplot_scatter.edgecolors'
     ]]></token>
-    <xml name="section_violin_plots">
-        <section name="violin_plot" title="Violin plot attributes">
-            <conditional name="stripplot">
-                <param argument="stripplot" type="select" label="Add a stripplot on top of the violin plot" help="">
-                    <option value="True">Yes</option>
-                    <option value="False">No</option>
-                </param>
-                <when value="True">
-                    <conditional name="jitter">
-                        <param argument="jitter" type="select" label="Add a jitter to the stripplot" help="">
-                            <option value="True">Yes</option>
-                            <option value="False">No</option>
-                        </param>
-                        <when value="True">
-                            <param argument="size" type="integer" min="0" value="1" label="Size of the jitter points" help=""/>
-                        </when>
-                        <when value="False"/>
-                    </conditional>
-                </when>
-                <when value="False"/>
-            </conditional>
-            <conditional name="multi_panel">
-                <param argument="multi_panel" type="select" label="Display keys in multiple panels" help="Also when `groupby is not provided">
-                    <option value="True">Yes</option>
-                    <option value="False" selected="true">No</option>
-                </param>
-                <when value="True">
-                    <param argument="width" type="integer" min="0" value="" optional="true" label="Width of the figure" help=""/>
-                    <param argument="height" type="integer" min="0" value="" optional="true" label="Height of the figure" help=""/>
-                </when>
-                <when value="False"/>
-            </conditional>
-            <param argument="scale" type="select" label="Method used to scale the width of each violin">
-                <option value="area">area: each violin will have the same area</option>
-                <option value="count">count: the width of the violins will be scaled by the number of observations in that bin</option>
-                <option value="width" selected="true">width: each violin will have the same width</option>
+    <xml name="conditional_stripplot">
+        <conditional name="stripplot">
+            <param argument="stripplot" type="select" label="Add a stripplot on top of the violin plot" help="">
+                <option value="True">Yes</option>
+                <option value="False">No</option>
             </param>
-        </section>
+            <when value="True">
+                <conditional name="jitter">
+                    <param argument="jitter" type="select" label="Add a jitter to the stripplot" help="">
+                        <option value="True">Yes</option>
+                        <option value="False">No</option>
+                    </param>
+                    <when value="True">
+                        <param argument="size" type="integer" min="0" value="1" label="Size of the jitter points" help=""/>
+                    </when>
+                    <when value="False"/>
+                </conditional>
+            </when>
+            <when value="False"/>
+        </conditional>
+    </xml>
+    <token name="@CMD_conditional_stripplot@"><![CDATA[
+    stripplot=$method.violin_plot.stripplot.stripplot,
+#if $method.violin_plot.stripplot.stripplot == "True"
+    jitter=$method.violin_plot.stripplot.jitter.jitter,
+    #if $method.violin_plot.stripplot.jitter.jitter == "True"
+    size=$method.violin_plot.stripplot.jitter.size,
+    #end if
+#end if
+    ]]></token>
+    <xml name="param_scale">
+        <param argument="scale" type="select" label="Method used to scale the width of each violin">
+            <option value="area">area: each violin will have the same area</option>
+            <option value="count">count: the width of the violins will be scaled by the number of observations in that bin</option>
+            <option value="width" selected="true">width: each violin will have the same width</option>
+        </param>
     </xml>
     <token name="@CMD_params_violin_plots@"><![CDATA[
     stripplot=$method.violin_plot.stripplot.stripplot,
@@ -777,7 +705,7 @@
     #end if
 #end if
     multi_panel=$method.violin_plot.multi_panel.multi_panel, 
-#if $method.multi_panel.violin_plot.multi_panel == "True" and $method.violin_plot.multi_panel.width and $method.violin_plot.multi_panel.height
+#if $method.multi_panel.violin_plot.multi_panel == "True" and str($method.violin_plot.multi_panel.width) != '' and str($method.violin_plot.multi_panel.height) != ''
     figsize=($method.violin_plot.multi_panel.width, $method.violin_plot.multi_panel.height)
 #end if
     scale='$method.violin_plot.scale',
@@ -813,14 +741,12 @@
     saturation=$method.seaborn_violinplot.saturation,
     ]]></token>
     <xml name="param_color">
-        <param argument="color" type="text" value="" optional="true" label="Keys for annotations of observations/cells or variables/genes`" help="One or a list of comma-separated index or key from either `.obs` or `.var`"/>
+        <param argument="color" type="text" value="" optional="true" label="Keys for annotations of observations/cells or variables/genes" help="One or a list of comma-separated index or key from either `.obs` or `.var`"/>
     </xml>
     <token name="@CMD_param_color@"><![CDATA[
 #if str($method.color) != ''
     #set $color = ([x.strip() for x in str($method.color).split(',')])
     color=$color,
-#else
-    color=None,
 #end if
     ]]></token>
     <xml name="pl_groups">
@@ -830,8 +756,6 @@
 #if str($method.groups) != ''
     #set $groups=([x.strip() for x in str($method.groups).split(',')])
     groups=$groups,
-#else
-    groups=None,
 #end if
     ]]></token>
     <xml name="pl_components">
@@ -847,8 +771,6 @@
         #silent $components.append(str($s.axis1) + ',' + str($s.axis2))
     #end for
     components=$components,
-#else
-    components=None,
 #end if
     ]]>
     </token>
@@ -877,7 +799,7 @@
         </param>
     </xml>
     <xml name="param_legend_fontsize">
-        <param argument="legend_fontsize" type="integer" min="0" value="1" label="Legend font size" help=""/>
+        <param argument="legend_fontsize" type="integer" optional="true" value="" label="Legend font size" help=""/>
     </xml>
     <xml name="param_legend_fontweight">
         <param argument="legend_fontweight" type="select" label="Legend font weight" help="">
@@ -910,7 +832,7 @@
         <param argument="left_margin" type="float" value="1" label="Width of the space left of each plotting panel" help=""/>
     </xml>
     <xml name="param_size">
-        <param argument="size" type="float" value="1" label="Point size" help=""/>
+        <param argument="size" type="float" optional="true" value="" label="Point size" help=""/>
     </xml>
     <xml name="param_title">
         <param argument="title" type="text" value="" optional="true" label="Title for panels" help="Titles must be separated by a comma"/>
@@ -937,8 +859,8 @@
                 <option value="False" selected="true">No</option>
             </param>
             <when value="True">
-                <param name="edges_width" type="float" min="0" value="0.1" label="Width of edges"/>
-                <param name="edges_color" type="select" label="Color of edges">
+                <param argument="edges_width" type="float" min="0" value="0.1" label="Width of edges"/>
+                <param argument="edges_color" type="select" label="Color of edges">
                     <expand macro="matplotlib_color"/>
                 </param>
             </when>
@@ -956,7 +878,7 @@
     ]]>
     </token>
     <xml name="param_arrows">
-        <param name="arrows" type="boolean" truevalue="True" falsevalue="False" checked="false" label="Show arrows?" help="It requires to run `tl.rna_velocity` before."/>
+        <param argument="arrows" type="boolean" truevalue="True" falsevalue="False" checked="false" label="Show arrows?" help="It requires to run `tl.rna_velocity` before."/>
     </xml>
     <xml name="param_cmap">
         <param argument="cmap" type="select" label="Colors to use for plotting categorical annotation groups" help="">
@@ -982,9 +904,13 @@
     <token name="@CMD_pl_attribute_section@"><![CDATA[
     projection='$method.plot.projection',
     legend_loc='$method.plot.legend_loc',
+    #if str($method.plot.legend_fontsize) != ''
     legend_fontsize=$method.plot.legend_fontsize,
+    #end if
     legend_fontweight='$method.plot.legend_fontweight',
+    #if str($method.plot.size) != ''
     size=$method.plot.size,
+    #end if
     palette='$method.plot.palette',
     frameon=$method.plot.frameon,
     ncols=$method.plot.ncols,
@@ -995,24 +921,39 @@
     #end if
     ]]>
     </token>
+    <xml name="options_layout">
+        <option value="fa">fa: ForceAtlas2</option>
+        <option value="fr">fr: Fruchterman-Reingold</option>
+        <option value="grid_fr">grid_fr: Grid Fruchterman Reingold, faster than "fr"</option>
+        <option value="kk">kk: Kamadi Kawai’, slower than "fr"</option>
+        <option value="drl">drl: Distributed Recursive Layout, pretty fast</option>
+        <option value="rt">rt: Reingold Tilford tree layout</option>
+        <option value="eq_tree">eq_tree: Equally spaced tree</option>
+    </xml>
+    <xml name="param_layout">
+        <param argument="layout" type="select" label="Plotting layout" help="">
+            <expand macro="options_layout"/>
+        </param>
+    </xml>
+    <xml name="param_root">
+        <param argument="root" type="text" value="" label="Comma-separated roots" help="If choosing a tree layout, this is the index of the root node or a list of root node indices. If this is a non-empty vector then the supplied node IDs are used as the roots of the trees (or a single tree if the graph is connected). If this is `None` or an empty list, the root vertices are automatically calculated based on topological sorting."/>
+    </xml>
+    <xml name="param_random_state">
+        <param argument="random_state" type="integer" value="0" label="Random state" help="For layouts with random initialization like 'fr', change this to use different intial states for the optimization. If `None`, the initial state is not reproducible."/>
+    </xml>
     <xml name="inputs_paga">
         <param argument="threshold" type="float" min="0" value="0.01" label="Threshold to draw edges" help="Do not draw edges for weights below this threshold. Set to 0 if you want all edges. Discarding low-connectivity edges helps in getting a much clearer picture of the graph."/>
         <expand macro="pl_groups"/>
         <param argument="color" type="text" value="" label="The node colors" help="Gene name or obs. annotation, and also plots the degree of the abstracted graph when passing 'degree_dashed', 'degree_solid'."/>
         <param argument="pos" type="data" format="tabular,csv,tsv" optional="true" label="Two-column tabular file storing the x and y coordinates for drawing" help=""/>
         <param argument="labels" type="text" value="" label="Comma-separated node labels" help="If none is provided, this defaults to the group labels stored in the categorical for which `tl.paga` has been computed."/>
-        <param argument="layout" type="select" value="" label="Plotting layout" help="">
-            <option value="fa">fa: ForceAtlas2</option>
-            <option value="fr">fr: Fruchterman-Reingold</option>
-            <option value="fr">rt: stands for Reingold Tilford</option>
-            <option value="fr">eq_tree: equally spaced tree</option>
-        </param>
+        <expand macro="param_layout"/>
         <param argument="init_pos" type="data" format="tabular,csv,tsv" optional="true" label="Two-column tabular file storing the x and y coordinates for initializing the layout" help=""/>
-        <param argument="random_state" type="integer" value="0" label="Random state" help="For layouts with random initialization like 'fr', change this to use different intial states for the optimization. If `None`, the initial state is not reproducible."/>
-        <param argument="root" type="text" value="" label="Comma-separated roots" help="If choosing a tree layout, this is the index of the root node or a list of root node indices. If this is a non-empty vector then the supplied node IDs are used as the roots of the trees (or a single tree if the graph is connected). If this is `None` or an empty list, the root vertices are automatically calculated based on topological sorting."/>
+        <expand macro="param_random_state"/>
+        <expand macro="param_root"/>
         <param argument="transitions" type="text" value="" label="Key corresponding to the matrix storing the arrows" help="Key for `.uns['paga']`, e.g. 'transistions_confidence'"/>
-        <param argument="solid_edges" type="text" value="paga_connectivities" label="Key corresponding to the matrix storing the edges to be drawn solid black" help="Key for `.uns['paga']`"/>
-        <param argument="dashed_edges" type="text" value="" optional="true" label="Key corresponding to the matrix storing the edges to be drawn dashed grey" help="Key for `.uns['paga']`. If not set, no dashed edges are drawn."/>
+        <param argument="solid_edges" type="text" value="connectivities" label="Key corresponding to the matrix storing the edges to be drawn solid black" help="Key for uns/paga"/>
+        <param argument="dashed_edges" type="text" value="" optional="true" label="Key corresponding to the matrix storing the edges to be drawn dashed grey" help="Key for uns/paga. If not set, no dashed edges are drawn."/>
         <param argument="single_component" type="boolean" truevalue="True" falsevalue="False" checked="false" label="Restrict to largest connected component?" help=""/>
         <param argument="fontsize" type="integer" min="0" value="1" label="Font size for node labels" help=""/>
         <param argument="node_size_scale" type="float" min="0" value="1.0" label="Size of the nodes" help=""/>
@@ -1031,10 +972,11 @@
 #if str($method.groups) != ''
     #set $groups=([x.strip() for x in str($method.groups).split(',')])
     groups=$groups,
-#else
-    groups=None,
 #end if
-    color='$method.color',
+#if str($method.color) != ''
+    #set $color=([x.strip() for x in str($method.color).split(',')])
+    color=$color,
+#end if
 #if $method.pos
     pos=np.fromfile($method.pos, dtype=dt),
 #end if
@@ -1081,4 +1023,10 @@
     <xml name="param_swap_axes">
         <param argument="swap_axes" type="boolean" truevalue="True" falsevalue="False" checked="false" label="Swap axes?" help="By default, the x axis contains `var_names` (e.g. genes) and the y axis the `groupby` categories (if any). By setting `swap_axes` then x are the `groupby` categories and y the `var_names`."/>
     </xml>
+    <xml name="gene_symbols">
+        <param argument="gene_symbols" type="text" value="" optional="true" label="Key for field in `.var` that stores gene symbols"/>
+    </xml>
+    <xml name="n_genes">
+        <param argument="n_genes" type="integer" min="0" value="20" label="Number of genes to show" help=""/>
+    </xml>               
 </macros>
diff -r 9ca360dde8e3 -r a89ee42625ad remove_confounders.xml
--- a/remove_confounders.xml	Mon Mar 04 10:16:47 2019 -0500
+++ b/remove_confounders.xml	Wed Oct 16 06:30:25 2019 -0400
@@ -1,18 +1,7 @@
-<tool id="scanpy_remove_confounders" name="Remove confounders with scanpy" version="@version@">
-    <description></description>
+<tool id="scanpy_remove_confounders" name="Remove confounders" version="@version@">
+    <description>with scanpy</description>
     <macros>
         <import>macros.xml</import>
-        <xml name="score_genes_params">
-            <param argument="n_bins" type="integer" value="25" label="Number of expression level bins for sampling" help=""/>
-            <param argument="random_state" type="integer" value="0" label="Random seed for sampling" help=""/>
-            <expand macro="param_use_raw"/>
-        </xml>
-        <token name="@CMD_score_genes_inputs@"><![CDATA[
-    n_bins=$method.n_bins,
-    random_state=$method.random_state,
-    use_raw=$method.use_raw,
-    copy=False
-        ]]></token>
     </macros>
     <expand macro="requirements"/>
     <command detect_errors="exit_code"><![CDATA[
@@ -26,30 +15,49 @@
 #if $method.method == "pp.regress_out"
 sc.pp.regress_out(
    adata=adata,
-   keys='$method.reg_keys',
+   #set $keys = [str(x.strip()) for x in str($method.keys).split(',')]
+   keys=$keys,
    copy=False)
-#elif $method.method == "tl.score_genes"
-sc.tl.score_genes(
-    adata=adata,
-    #set $gene_list = [str(x.strip()) for x in str($method.gene_list).split(',')]
-    gene_list=$gene_list,
-    ctrl_size=$method.ctrl_size,
-    score_name='$method.score_name',
-    #if $method.gene_pool
-        #set $gene_pool = [str(x.strip()) for x in $method.gene_pool.split(',')]
-    gene_pool=$gene_pool,
+
+#else if $method.method == "pp.mnn_correct"
+    #for i, filepath in enumerate($methods.extra_adata)
+adata_$i = ad.read('$filepath')
+    #end for
+
+sc.pp.mnn_correct(
+    adata,
+    #for i, filepath in enumerate($methods.extra_adata)
+    adata_$i,
+    #end for
+    #if str($methods.var_subset) != ''
+    #set $var_subset=([x.strip() for x in str($method.var_subset).split(',')])
+    var_subset=$var_subset,
     #end if
-    @CMD_score_genes_inputs@)
-adata.obs.to_csv('$obs', sep='\t')
-#elif $method.method == "tl.score_genes_cell_cycle"
-sc.tl.score_genes_cell_cycle(
-    adata=adata,
-    #set $s_genes = [str(x.strip()) for x in $method.s_genes.split(',')]
-    s_genes=$s_genes,
-    #set $g2m_genes = [str(x.strip()) for x in $method.g2m_genes.split(',')]
-    g2m_genes=$g2m_genes,
-    @CMD_score_genes_inputs@)
-adata.obs.to_csv('$obs', sep='\t')
+    batch_key='$method.batch_key',
+    index_unique='$method.index_unique'
+    #if str($methods.batch_categories) != ''
+    #set $batch_categories=([x.strip() for x in str($method.batch_categories).split(',')])
+    batch_categories=$batch_categories,
+    #end if
+    k=$method.k,
+    sigma=$method.sigma,
+    cos_norm_in=$method.cos_norm_in,
+    cos_norm_out=$method.cos_norm_out,
+    svd_dim=$method.svd_dim,
+    var_adj=$method.var_adj,
+    compute_angle=$method.compute_angle,
+    mnn_order='$method.mnn_order',
+    svd_mode='$method.svd_mode',
+    do_concatenate=True,
+    save_raw=True,
+    n_jobs=\${GALAXY_SLOTS:-4})
+
+#else if $method.method == "pp.combat"
+sc.pp.combat(
+    adata,
+    key='$method.key',
+    inplace=True)
+
 #end if
 
 @CMD_anndata_write_outputs@
@@ -60,111 +68,84 @@
         <conditional name="method">
             <param argument="method" type="select" label="Method used for plotting">
                 <option value="pp.regress_out">Regress out unwanted sources of variation, using `pp.regress_out`</option>
-                <!--<option value="pp.mnn_correct">, using `pp.mnn_correct`</option>!-->
-                <!--<option value="pp.dca">, using `pp.mnn_correct`</option>!-->
-                <!--<option value="pp.magic">, using `pp.magic`</option>!-->
-                <!--<option value="tl.sim">, using `tl.sim`</option>!-->
-                <!--<option value="pp.calculate_qc_metrics">, using `pp.calculate_qc_metrics`</option>!-->
-                <option value="tl.score_genes">Score a set of genes, using `tl.score_genes`</option>
-                <option value="tl.score_genes_cell_cycle">Score cell cycle genes, using `tl.score_genes_cell_cycle`</option>
-                <!--<option value="tl.cyclone">, using `tl.cyclone`</option>!-->
-                <!--<option value="tl.andbag">, using `tl.andbag`</option>!-->
+                <option value="pp.mnn_correct">Correct batch effects by matching mutual nearest neighbors, using `pp.mnn_correct`</option>
+                <option value="pp.combat">Correct batch effects with ComBat function, using `pp.combat`</option>
             </param>
             <when value="pp.regress_out">
-                <param argument="reg_keys" type="text" value="" label="Keys for observation annotation on which to regress on" help=""/>
+                <param argument="keys" type="text" value="" label="Keys for observation annotation on which to regress on" help="Keys separated by a comma"/>
             </when>
-            <when value="tl.score_genes">
-                <param argument="gene_list" type="text" value="" label="The list of gene names used for score calculation" help="Genes separated by a comma"/>
-                <param argument="ctrl_size" type="integer" value="50" label="Number of reference genes to be sampled"
-                    help="If `len(gene_list)` is not too low, you can set `ctrl_size=len(gene_list)`."/>
-                <param argument="gene_pool" type="text" value="" optional="true" label="Genes for sampling the reference set"
-                    help="Default is all genes. Genes separated by a comma"/>
-                <expand macro="score_genes_params"/>
-                <param argument="score_name" type="text" value="score" label="Name of the field to be added in `.obs`" help=""/>
+            <when value="pp.mnn_correct">
+                <param name="extra_adata" type="data" multiple="true" optional="true" format="h5ad" label="Extra annotated data matrix" help="They should have same number of variables."/>
+                <param argument="var_subset" type="text" value="" optional="true" label="The subset of vars to be used when performing MNN correction" help="List of comma-separated key from `.var_names`. If not set, all vars are used"/>
+                <param argument="batch_key" type="text" value="batch" label="Batch key for the concatenate"/>
+                <param name="index_unique" type="select" label="Separator to join the existing index names with the batch category" help="Leave it empty to keep existing indices">
+                    <option value="-">-</option>
+                    <option value="_">_</option>
+                    <option value=" "> </option>
+                    <option value="/">/</option>
+                </param>
+                <param argument="batch_categories" type="text" value="" optional="true" label="Batch categories for the concatenate" help="List of comma-separated key"/>
+                <param argument="k" type="integer" value="20" label="Number of mutual nearest neighbors"/>
+                <param argument="sigma" type="float" value="1" label="The bandwidth of the Gaussian smoothing kernel used to compute the correction vectors"/>
+                <param argument="cos_norm_in" type="boolean" truevalue="True" falsevalue="False" checked="true" label="Should cosine normalization be performed on the input data prior to calculating distances between cells?"/>
+                <param argument="cos_norm_out" type="boolean" truevalue="True" falsevalue="False" checked="true" label="Should cosine normalization be performed prior to computing corrected expression values?"/>
+                <param argument="svd_dim" type="integer" value="" optional="true" label="Number of dimensions to use for summarizing biological substructure within each batch" help="If not set, biological components will not be removed from the correction vectors."/>
+                <param argument="var_adj" type="boolean" truevalue="True" falsevalue="False" checked="true" label="Adjust variance of the correction vectors?" help="This step takes most computing time."/>
+                <param argument="compute_angle" type="boolean" truevalue="True" falsevalue="False" checked="false" label="compute the angle between each cell’s correction vector and the biological subspace of the reference batch?"/>
+                <param argument="mnn_order" type="text" value="" optional="true" label="The order in which batches are to be corrected" help="List of comma-separated key. If not set, datas are corrected sequentially"/>
+                <param name="svd_mode" type="select" label="SVD mode">
+                    <option value="svd">svd: SVD using a non-randomized SVD-via-ID algorithm</option>
+                    <option value="rsvd" selected="true">rsvd: SVD using a randomized SVD-via-ID algorithm</option>
+                    <option value="irlb">irlb: truncated SVD by implicitly restarted Lanczos bidiagonalization</option>
+                </param>
             </when>
-            <when value="tl.score_genes_cell_cycle">
-                <param name="s_genes" type="text" value="" label="List of genes associated with S phase" help="Genes separated by a comma"/>
-                <param name="g2m_genes" type="text" value="" label="List of genes associated with G2M phase" help="Genes separated by a comma"/>
-                <expand macro="score_genes_params"/>
+            <when value="pp.combat">
+                <param argument="key" type="text" value="batch" label="Key to a categorical annotation from adata.obs that will be used for batch effect removal"/>
             </when>
         </conditional>
-        <expand macro="anndata_output_format"/>
     </inputs>
     <outputs>
         <expand macro="anndata_outputs"/>
-        <data name="obs" format="tabular" label="${tool.name} on ${on_string}: Observations annotation">
-            <filter>method['method'] == 'tl.score_genes' or method['method'] == 'tl.score_genes_cell_cycle'</filter>
-        </data>
     </outputs>
     <tests>
         <test>
-            <conditional name="input">
-                <param name="format" value="h5ad" />
-                <param name="adata" value="krumsiek11.h5ad" />
-            </conditional>
+            <!-- test 1 -->
+            <param name="adata" value="krumsiek11.h5ad" />
             <conditional name="method">
                 <param name="method" value="pp.regress_out"/>
+                <param name="keys" value="cell_type"/>
+            </conditional>
+            <assert_stdout>
+                <has_text_matching expression="sc.pp.regress_out"/>
+                <has_text_matching expression="keys=\['cell_type'\]"/>
+            </assert_stdout>
+            <output name="anndata_out" file="pp.regress_out.krumsiek11.h5ad" ftype="h5ad" compare="sim_size"/>
+        </test>
+        <!--<test>
+            < test 2 >
+            <param name="adata" value="krumsiek11.h5ad" />
+            <conditional name="method">
+                <param name="method" value="pp.mnn_correct"/>
                 <param name="reg_keys" value="cell_type"/>
             </conditional>
-            <param name="anndata_output_format" value="h5ad" />
             <assert_stdout>
-                <has_text_matching expression="sc.pp.regress_out"/>
+                <has_text_matching expression="sc.pp.mnn_correct"/>
                 <has_text_matching expression="keys='cell_type'"/>
             </assert_stdout>
-            <output name="anndata_out_h5ad" file="pp.regress_out.krumsiek11.h5ad" ftype="h5" compare="sim_size"/>
-        </test>
+            <output name="anndata_out" file="pp.mnn_correct.krumsiek11.h5ad" ftype="h5ad" compare="sim_size"/>
+        </test>-->
         <test>
-            <conditional name="input">
-                <param name="format" value="h5ad" />
-                <param name="adata" value="krumsiek11.h5ad" />
-            </conditional>
+            <!-- test 2 -->
+            <param name="adata" value="blobs.h5ad" />
             <conditional name="method">
-                <param name="method" value="tl.score_genes"/>
-                <param name="gene_list" value="Gata2, Fog1"/>
-                <param name="ctrl_size" value="2"/>
-                <param name="n_bins" value="2"/>
-                <param name="random_state" value="2"/>
-                <param name="use_raw" value="False"/>
-                <param name="score_name" value="score"/>
+                <param name="method" value="pp.combat"/>
+                <param name="key" value="blobs"/>
             </conditional>
-            <param name="anndata_output_format" value="h5ad"/>
             <assert_stdout>
-                <has_text_matching expression="sc.tl.score_genes" />
-                <has_text_matching expression="gene_list=\['Gata2', 'Fog1'\]" />
-                <has_text_matching expression="ctrl_size=2" />
-                <has_text_matching expression="score_name='score'" />
-                <has_text_matching expression="n_bins=2" />
-                <has_text_matching expression="random_state=2" />
-                <has_text_matching expression="use_raw=False" />
-                <has_text_matching expression="copy=False" />
+                <has_text_matching expression="sc.pp.combat"/>
+                <has_text_matching expression="key='blobs'"/>
             </assert_stdout>
-            <output name="anndata_out_h5ad" file="tl.score_genes.krumsiek11.h5ad" ftype="h5" compare="sim_size"/>
-            <output name="obs" file="tl.score_genes.krumsiek11.obs.tabular" ftype="tabular" compare="sim_size"/>
-        </test>
-        <test>
-            <conditional name="input">
-                <param name="format" value="h5ad" />
-                <param name="adata" value="krumsiek11.h5ad" />
-            </conditional>
-            <conditional name="method">
-                <param name="method" value="tl.score_genes_cell_cycle"/>
-                <param name="s_genes" value="Gata2, Fog1, EgrNab"/>
-                <param name="g2m_genes" value="Gata2, Fog1, EgrNab"/>
-                <param name="n_bins" value="2"/>
-                <param name="random_state" value="1"/>
-                <param name="use_raw" value="False"/>
-            </conditional>
-            <param name="anndata_output_format" value="h5ad"/>
-            <assert_stdout>
-                <has_text_matching expression="sc.tl.score_genes_cell_cycle"/>
-                <has_text_matching expression="s_genes=\['Gata2', 'Fog1', 'EgrNab'\]"/>
-                <has_text_matching expression="g2m_genes=\['Gata2', 'Fog1', 'EgrNab'\]"/>
-                <has_text_matching expression="n_bins=2"/>
-                <has_text_matching expression="random_state=1"/>
-                <has_text_matching expression="use_raw=False"/>
-            </assert_stdout>
-            <output name="anndata_out_h5ad" file="tl.score_genes_cell_cycle.krumsiek11.h5ad" ftype="h5" compare="sim_size"/>
-            <output name="obs" file="tl.score_genes_cell_cycle.krumsiek11.obs.tabular" ftype="tabular" compare="sim_size"/>
+            <output name="anndata_out" file="pp.combat.blobs.h5ad" ftype="h5ad" compare="sim_size"/>
         </test>
     </tests>
     <help><![CDATA[
@@ -175,30 +156,29 @@
 inspired by Seurat's `regressOut` function in R.
 
 More details on the `scanpy documentation
-<https://scanpy.readthedocs.io/en/latest/api/scanpy.api.pp.regress_out.html#scanpy.api.pp.regress_out>`__
+<https://icb-scanpy.readthedocs-hosted.com/en/stable/api/scanpy.pp.regress_out.html>`__
 
-Score a set of genes, using `tl.score_genes`
-============================================
+Correct batch effects by matching mutual nearest neighbors, using `pp.mnn_correct`
+==================================================================================
 
-The score is the average expression of a set of genes subtracted with the
-average expression of a reference set of genes. The reference set is
-randomly sampled from the `gene_pool` for each binned expression value.
+This uses the implementation of mnnpy. Depending on do_concatenate, it returns AnnData objects in the 
+original order containing corrected expression values or a concatenated matrix or AnnData object.
 
-This reproduces the approach in Seurat (Satija et al, 2015) and has been implemented
-for Scanpy by Davide Cittaro.
+Be reminded that it is not advised to use the corrected data matrices for differential expression testing.
 
 More details on the `scanpy documentation
-<https://scanpy.readthedocs.io/en/latest/api/scanpy.api.tl.score_genes.html#scanpy.api.tl.score_genes>`__
+<https://icb-scanpy.readthedocs-hosted.com/en/stable/api/scanpy.api.pp.mnn_correct.html>`__
+
 
-Score cell cycle genes, using `tl.score_genes_cell_cycle`
-=========================================================
+Correct batch effects with ComBat function (`pp.combat`)
+========================================================
 
-Given two lists of genes associated to S phase and G2M phase, calculates
-scores and assigns a cell cycle phase (G1, S or G2M). See
-`score_genes` for more explanation.
+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
 
 More details on the `scanpy documentation
-<https://scanpy.readthedocs.io/en/latest/api/scanpy.api.tl.score_genes_cell_cycle.html#scanpy.api.tl.score_genes_cell_cycle>`__
+<https://icb-scanpy.readthedocs-hosted.com/en/stable/api/scanpy.pp.combat.html>`__
+
+
     ]]></help>
     <expand macro="citations"/>
 </tool>
diff -r 9ca360dde8e3 -r a89ee42625ad test-data/blobs.h5ad
Binary file test-data/blobs.h5ad has changed
diff -r 9ca360dde8e3 -r a89ee42625ad test-data/pl.clustermap.krumsiek11.png
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diff -r 9ca360dde8e3 -r a89ee42625ad test-data/pl.dotplot.krumsiek11.png
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diff -r 9ca360dde8e3 -r a89ee42625ad test-data/pl.draw_graph.png
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diff -r 9ca360dde8e3 -r a89ee42625ad test-data/pl.highly_variable_genes.seurat.blobs.png
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diff -r 9ca360dde8e3 -r a89ee42625ad test-data/pl.pca_overview.pp.pca.krumsiek11.png
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diff -r 9ca360dde8e3 -r a89ee42625ad test-data/pl.rank_genes_groups.rank_genes_groups.krumsiek11.png
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diff -r 9ca360dde8e3 -r a89ee42625ad test-data/pl.rank_genes_groups_violin.Ery.png
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diff -r 9ca360dde8e3 -r a89ee42625ad test-data/pl.rank_genes_groups_violin.Mk.png
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diff -r 9ca360dde8e3 -r a89ee42625ad test-data/pl.rank_genes_groups_violin.Mo.png
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diff -r 9ca360dde8e3 -r a89ee42625ad test-data/pl.rank_genes_groups_violin.Neu.png
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diff -r 9ca360dde8e3 -r a89ee42625ad test-data/pl.rank_genes_groups_violin.progenitor.png
Binary file test-data/pl.rank_genes_groups_violin.progenitor.png has changed
diff -r 9ca360dde8e3 -r a89ee42625ad test-data/pl.scatter.krumsiek11.png
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diff -r 9ca360dde8e3 -r a89ee42625ad test-data/pl.scatter.umap.pbmc68k_reduced.png
Binary file test-data/pl.scatter.umap.pbmc68k_reduced.png has changed
diff -r 9ca360dde8e3 -r a89ee42625ad test-data/pl.stacked_violin.krumsiek11.png
Binary file test-data/pl.stacked_violin.krumsiek11.png has changed
diff -r 9ca360dde8e3 -r a89ee42625ad test-data/pp.calculate_qc_metrics.sparce_csr_matrix.h5ad
Binary file test-data/pp.calculate_qc_metrics.sparce_csr_matrix.h5ad has changed
diff -r 9ca360dde8e3 -r a89ee42625ad test-data/pp.combat.blobs.h5ad
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diff -r 9ca360dde8e3 -r a89ee42625ad test-data/pp.downsample_counts.random-randint.h5ad
Binary file test-data/pp.downsample_counts.random-randint.h5ad has changed
diff -r 9ca360dde8e3 -r a89ee42625ad test-data/pp.filter_cells.krumsiek11-max_genes.h5ad
Binary file test-data/pp.filter_cells.krumsiek11-max_genes.h5ad has changed
diff -r 9ca360dde8e3 -r a89ee42625ad test-data/pp.filter_cells.krumsiek11-min_counts.h5ad
Binary file test-data/pp.filter_cells.krumsiek11-min_counts.h5ad has changed
diff -r 9ca360dde8e3 -r a89ee42625ad test-data/pp.filter_cells.number_per_cell.krumsiek11-max_genes.tabular
--- a/test-data/pp.filter_cells.number_per_cell.krumsiek11-max_genes.tabular	Mon Mar 04 10:16:47 2019 -0500
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,641 +0,0 @@
-	cell_subset	number_per_cell
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-618	True	7
-619	True	6
-620	True	6
-621	True	7
-622	True	7
-623	True	7
-624	True	8
-625	True	6
-626	True	7
-627	True	7
-628	True	7
-629	True	6
-630	True	5
-631	True	7
-632	True	6
-633	True	6
-634	True	7
-635	True	6
-636	True	8
-637	True	8
-638	True	6
-639	True	8
diff -r 9ca360dde8e3 -r a89ee42625ad test-data/pp.filter_genes.krumsiek11-min_counts.h5ad
Binary file test-data/pp.filter_genes.krumsiek11-min_counts.h5ad has changed
diff -r 9ca360dde8e3 -r a89ee42625ad test-data/pp.filter_genes.number_per_gene.krumsiek11-min_counts.tabular
--- a/test-data/pp.filter_genes.number_per_gene.krumsiek11-min_counts.tabular	Mon Mar 04 10:16:47 2019 -0500
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,12 +0,0 @@
-index	n_counts
-Gata2	163.95355
-Gata1	203.95117
-Fog1	83.94181
-EKLF	70.69286
-Fli1	57.56072
-SCL	202.67444
-Cebpa	469.87094
-Pu.1	250.78569
-cJun	188.10158
-EgrNab	164.99693
-Gfi1	159.99155
diff -r 9ca360dde8e3 -r a89ee42625ad test-data/pp.filter_genes.number_per_gene.pbmc68k_reduced-max_cells.tabular
--- a/test-data/pp.filter_genes.number_per_gene.pbmc68k_reduced-max_cells.tabular	Mon Mar 04 10:16:47 2019 -0500
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,222 +0,0 @@
-	gene_subset	number_per_gene
-0	True	34
-1	True	123
-2	True	281
-3	True	54
-4	True	253
-5	True	63
-6	True	9
-7	True	266
-8	True	101
-9	True	233
-10	True	267
-11	True	285
-12	True	332
-13	True	197
-14	True	158
-15	True	64
-16	True	285
-17	True	229
-18	True	43
-19	True	199
-20	True	271
-21	True	318
-22	True	132
-23	True	83
-24	True	88
-25	True	87
-26	True	71
-27	True	258
-28	True	58
-29	True	348
-30	True	280
-31	True	150
-32	True	121
-33	True	237
-34	True	29
-35	True	220
-36	True	103
-37	True	87
-38	True	115
-39	True	100
-40	True	139
-41	True	23
-42	True	162
-43	True	76
-44	True	180
-45	True	51
-46	True	244
-47	True	132
-48	True	244
-49	True	82
-50	True	172
-51	True	27
-52	True	100
-53	True	327
-54	True	277
-55	True	282
-56	True	245
-57	True	21
-58	True	52
-59	True	19
-60	True	227
-61	True	288
-62	True	274
-63	True	301
-64	True	316
-65	True	314
-66	True	271
-67	True	270
-68	True	283
-69	True	245
-70	True	263
-71	True	312
-72	True	285
-73	True	228
-74	True	170
-75	True	11
-76	True	228
-77	True	192
-78	True	140
-79	True	15
-80	True	22
-81	True	10
-82	True	233
-83	True	129
-84	True	12
-85	True	297
-86	True	295
-87	True	127
-88	True	208
-89	True	281
-90	True	265
-91	True	254
-92	True	122
-93	True	76
-94	True	237
-95	True	74
-96	True	65
-97	True	45
-98	True	90
-99	True	147
-100	True	189
-101	True	170
-102	True	207
-103	True	14
-104	True	307
-105	True	267
-106	True	111
-107	True	94
-108	True	306
-109	True	126
-110	True	269
-111	True	116
-112	True	140
-113	True	260
-114	True	201
-115	True	198
-116	True	155
-117	True	256
-118	True	214
-119	True	70
-120	True	304
-121	True	336
-122	True	201
-123	True	305
-124	True	301
-125	True	301
-126	True	338
-127	True	81
-128	True	256
-129	True	277
-130	True	237
-131	True	173
-132	True	228
-133	True	64
-134	True	52
-135	True	34
-136	True	333
-137	True	285
-138	True	132
-139	True	32
-140	True	275
-141	True	31
-142	True	244
-143	True	15
-144	True	54
-145	True	289
-146	True	186
-147	True	283
-148	True	333
-149	True	53
-150	True	26
-151	True	173
-152	True	19
-153	True	109
-154	True	138
-155	True	264
-156	True	293
-157	True	225
-158	True	150
-159	True	62
-160	True	350
-161	True	13
-162	True	341
-163	True	223
-164	True	177
-165	True	15
-166	True	202
-167	True	101
-168	True	203
-169	True	271
-170	True	305
-171	True	45
-172	True	322
-173	True	164
-174	True	213
-175	True	55
-176	True	143
-177	True	112
-178	True	266
-179	True	168
-180	True	9
-181	True	300
-182	True	249
-183	True	101
-184	True	55
-185	True	312
-186	True	181
-187	True	256
-188	True	27
-189	True	242
-190	True	210
-191	True	12
-192	True	203
-193	True	41
-194	True	205
-195	True	315
-196	True	94
-197	True	262
-198	True	316
-199	True	13
-200	True	94
-201	True	204
-202	True	245
-203	True	11
-204	True	238
-205	True	301
-206	True	219
-207	True	106
-208	True	253
-209	True	134
-210	True	262
-211	True	222
-212	True	82
-213	True	153
-214	True	122
-215	True	211
-216	True	49
-217	True	211
-218	True	176
-219	True	329
-220	True	8
diff -r 9ca360dde8e3 -r a89ee42625ad test-data/pp.filter_genes_dispersion.krumsiek11-seurat.h5ad
Binary file test-data/pp.filter_genes_dispersion.krumsiek11-seurat.h5ad has changed
diff -r 9ca360dde8e3 -r a89ee42625ad test-data/pp.filter_genes_dispersion.per_gene.krumsiek11-cell_ranger.tabular
--- a/test-data/pp.filter_genes_dispersion.per_gene.krumsiek11-cell_ranger.tabular	Mon Mar 04 10:16:47 2019 -0500
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,12 +0,0 @@
-	gene_subset	means	dispersions	dispersions_norm
-0	False	0.22807331	-1.513815	
-1	False	0.27662647	-0.6374868	
-2	False	0.12324284	-1.1931922	
-3	True	0.10477218	-0.8270577	0.67448974
-4	True	0.08612139	-0.880823	0.67448974
-5	False	0.2751125	-0.6042374	
-6	False	0.55053085	-1.5924454	
-7	False	0.3306357	-0.91260546	
-8	False	0.25766766	-0.86990273	
-9	False	0.22937028	-0.7354343	
-10	False	0.223133	-0.96748924	
diff -r 9ca360dde8e3 -r a89ee42625ad test-data/pp.filter_genes_dispersion.per_gene.krumsiek11-seurat.tabular
--- a/test-data/pp.filter_genes_dispersion.per_gene.krumsiek11-seurat.tabular	Mon Mar 04 10:16:47 2019 -0500
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,9 +0,0 @@
-index	means	dispersions	dispersions_norm
-Fog1	0.12324284	-1.1931922	1.0
-EKLF	0.10477218	-0.8270577	0.70710677
-SCL	0.2751125	-0.6042374	0.707108
-Cebpa	0.55053085	-1.5924454	1.0
-Pu.1	0.3306357	-0.91260546	1.0
-cJun	0.25766766	-0.86990273	1.0
-EgrNab	0.22937028	-0.7354343	0.7071069
-Gfi1	0.223133	-0.96748924	1.0
diff -r 9ca360dde8e3 -r a89ee42625ad test-data/pp.filter_rank_genes_groups.h5ad
Binary file test-data/pp.filter_rank_genes_groups.h5ad has changed
diff -r 9ca360dde8e3 -r a89ee42625ad test-data/pp.highly_variable_genes.krumsiek11-cell_ranger.h5ad
Binary file test-data/pp.highly_variable_genes.krumsiek11-cell_ranger.h5ad has changed
diff -r 9ca360dde8e3 -r a89ee42625ad test-data/pp.highly_variable_genes.seurat.blobs.h5ad
Binary file test-data/pp.highly_variable_genes.seurat.blobs.h5ad has changed
diff -r 9ca360dde8e3 -r a89ee42625ad test-data/pp.log1p.krumsiek11.h5ad
Binary file test-data/pp.log1p.krumsiek11.h5ad has changed
diff -r 9ca360dde8e3 -r a89ee42625ad test-data/pp.neighbors_gauss_braycurtis.recipe_weinreb17.paul15_subsample.h5ad
Binary file test-data/pp.neighbors_gauss_braycurtis.recipe_weinreb17.paul15_subsample.h5ad has changed
diff -r 9ca360dde8e3 -r a89ee42625ad test-data/pp.neighbors_umap_euclidean.recipe_weinreb17.paul15_subsample.h5ad
Binary file test-data/pp.neighbors_umap_euclidean.recipe_weinreb17.paul15_subsample.h5ad has changed
diff -r 9ca360dde8e3 -r a89ee42625ad test-data/pp.normalize_per_cell.obs.krumsiek11.tabular
--- a/test-data/pp.normalize_per_cell.obs.krumsiek11.tabular	Mon Mar 04 10:16:47 2019 -0500
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,641 +0,0 @@
-index	cell_type
-0	progenitor
-1	progenitor
-2	progenitor
-3	progenitor
-4	progenitor
-5	progenitor
-6	progenitor
-7	progenitor
-8	progenitor
-9	progenitor
-10	progenitor
-11	progenitor
-12	progenitor
-13	progenitor
-14	progenitor
-15	progenitor
-16	progenitor
-17	progenitor
-18	progenitor
-19	progenitor
-20	progenitor
-21	progenitor
-22	progenitor
-23	progenitor
-24	progenitor
-25	progenitor
-26	progenitor
-27	progenitor
-28	progenitor
-29	progenitor
-30	progenitor
-31	progenitor
-32	progenitor
-33	progenitor
-34	progenitor
-35	progenitor
-36	progenitor
-37	progenitor
-38	progenitor
-39	progenitor
-40	progenitor
-41	progenitor
-42	progenitor
-43	progenitor
-44	progenitor
-45	progenitor
-46	progenitor
-47	progenitor
-48	progenitor
-49	progenitor
-50	progenitor
-51	progenitor
-52	progenitor
-53	progenitor
-54	progenitor
-55	progenitor
-56	progenitor
-57	progenitor
-58	progenitor
-59	progenitor
-60	progenitor
-61	progenitor
-62	progenitor
-63	progenitor
-64	progenitor
-65	progenitor
-66	progenitor
-67	progenitor
-68	progenitor
-69	progenitor
-70	progenitor
-71	progenitor
-72	progenitor
-73	progenitor
-74	progenitor
-75	progenitor
-76	progenitor
-77	progenitor
-78	progenitor
-79	progenitor
-80	Mo
-81	Mo
-82	Mo
-83	Mo
-84	Mo
-85	Mo
-86	Mo
-87	Mo
-88	Mo
-89	Mo
-90	Mo
-91	Mo
-92	Mo
-93	Mo
-94	Mo
-95	Mo
-96	Mo
-97	Mo
-98	Mo
-99	Mo
-100	Mo
-101	Mo
-102	Mo
-103	Mo
-104	Mo
-105	Mo
-106	Mo
-107	Mo
-108	Mo
-109	Mo
-110	Mo
-111	Mo
-112	Mo
-113	Mo
-114	Mo
-115	Mo
-116	Mo
-117	Mo
-118	Mo
-119	Mo
-120	Mo
-121	Mo
-122	Mo
-123	Mo
-124	Mo
-125	Mo
-126	Mo
-127	Mo
-128	Mo
-129	Mo
-130	Mo
-131	Mo
-132	Mo
-133	Mo
-134	Mo
-135	Mo
-136	Mo
-137	Mo
-138	Mo
-139	Mo
-140	Mo
-141	Mo
-142	Mo
-143	Mo
-144	Mo
-145	Mo
-146	Mo
-147	Mo
-148	Mo
-149	Mo
-150	Mo
-151	Mo
-152	Mo
-153	Mo
-154	Mo
-155	Mo
-156	Mo
-157	Mo
-158	Mo
-159	Mo
-0	progenitor
-1	progenitor
-2	progenitor
-3	progenitor
-4	progenitor
-5	progenitor
-6	progenitor
-7	progenitor
-8	progenitor
-9	progenitor
-10	progenitor
-11	progenitor
-12	progenitor
-13	progenitor
-14	progenitor
-15	progenitor
-16	progenitor
-17	progenitor
-18	progenitor
-19	progenitor
-20	progenitor
-21	progenitor
-22	progenitor
-23	progenitor
-24	progenitor
-25	progenitor
-26	progenitor
-27	progenitor
-28	progenitor
-29	progenitor
-30	progenitor
-31	progenitor
-32	progenitor
-33	progenitor
-34	progenitor
-35	progenitor
-36	progenitor
-37	progenitor
-38	progenitor
-39	progenitor
-40	progenitor
-41	progenitor
-42	progenitor
-43	progenitor
-44	progenitor
-45	progenitor
-46	progenitor
-47	progenitor
-48	progenitor
-49	progenitor
-50	progenitor
-51	progenitor
-52	progenitor
-53	progenitor
-54	progenitor
-55	progenitor
-56	progenitor
-57	progenitor
-58	progenitor
-59	progenitor
-60	progenitor
-61	progenitor
-62	progenitor
-63	progenitor
-64	progenitor
-65	progenitor
-66	progenitor
-67	progenitor
-68	progenitor
-69	progenitor
-70	progenitor
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-73	progenitor
-74	progenitor
-75	progenitor
-76	progenitor
-77	progenitor
-78	progenitor
-79	progenitor
-80	Ery
-81	Ery
-82	Ery
-83	Ery
-84	Ery
-85	Ery
-86	Ery
-87	Ery
-88	Ery
-89	Ery
-90	Ery
-91	Ery
-92	Ery
-93	Ery
-94	Ery
-95	Ery
-96	Ery
-97	Ery
-98	Ery
-99	Ery
-100	Ery
-101	Ery
-102	Ery
-103	Ery
-104	Ery
-105	Ery
-106	Ery
-107	Ery
-108	Ery
-109	Ery
-110	Ery
-111	Ery
-112	Ery
-113	Ery
-114	Ery
-115	Ery
-116	Ery
-117	Ery
-118	Ery
-119	Ery
-120	Ery
-121	Ery
-122	Ery
-123	Ery
-124	Ery
-125	Ery
-126	Ery
-127	Ery
-128	Ery
-129	Ery
-130	Ery
-131	Ery
-132	Ery
-133	Ery
-134	Ery
-135	Ery
-136	Ery
-137	Ery
-138	Ery
-139	Ery
-140	Ery
-141	Ery
-142	Ery
-143	Ery
-144	Ery
-145	Ery
-146	Ery
-147	Ery
-148	Ery
-149	Ery
-150	Ery
-151	Ery
-152	Ery
-153	Ery
-154	Ery
-155	Ery
-156	Ery
-157	Ery
-158	Ery
-159	Ery
-0	progenitor
-1	progenitor
-2	progenitor
-3	progenitor
-4	progenitor
-5	progenitor
-6	progenitor
-7	progenitor
-8	progenitor
-9	progenitor
-10	progenitor
-11	progenitor
-12	progenitor
-13	progenitor
-14	progenitor
-15	progenitor
-16	progenitor
-17	progenitor
-18	progenitor
-19	progenitor
-20	progenitor
-21	progenitor
-22	progenitor
-23	progenitor
-24	progenitor
-25	progenitor
-26	progenitor
-27	progenitor
-28	progenitor
-29	progenitor
-30	progenitor
-31	progenitor
-32	progenitor
-33	progenitor
-34	progenitor
-35	progenitor
-36	progenitor
-37	progenitor
-38	progenitor
-39	progenitor
-40	progenitor
-41	progenitor
-42	progenitor
-43	progenitor
-44	progenitor
-45	progenitor
-46	progenitor
-47	progenitor
-48	progenitor
-49	progenitor
-50	progenitor
-51	progenitor
-52	progenitor
-53	progenitor
-54	progenitor
-55	progenitor
-56	progenitor
-57	progenitor
-58	progenitor
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-60	progenitor
-61	progenitor
-62	progenitor
-63	progenitor
-64	progenitor
-65	progenitor
-66	progenitor
-67	progenitor
-68	progenitor
-69	progenitor
-70	progenitor
-71	progenitor
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-74	progenitor
-75	progenitor
-76	progenitor
-77	progenitor
-78	progenitor
-79	progenitor
-80	Mk
-81	Mk
-82	Mk
-83	Mk
-84	Mk
-85	Mk
-86	Mk
-87	Mk
-88	Mk
-89	Mk
-90	Mk
-91	Mk
-92	Mk
-93	Mk
-94	Mk
-95	Mk
-96	Mk
-97	Mk
-98	Mk
-99	Mk
-100	Mk
-101	Mk
-102	Mk
-103	Mk
-104	Mk
-105	Mk
-106	Mk
-107	Mk
-108	Mk
-109	Mk
-110	Mk
-111	Mk
-112	Mk
-113	Mk
-114	Mk
-115	Mk
-116	Mk
-117	Mk
-118	Mk
-119	Mk
-120	Mk
-121	Mk
-122	Mk
-123	Mk
-124	Mk
-125	Mk
-126	Mk
-127	Mk
-128	Mk
-129	Mk
-130	Mk
-131	Mk
-132	Mk
-133	Mk
-134	Mk
-135	Mk
-136	Mk
-137	Mk
-138	Mk
-139	Mk
-140	Mk
-141	Mk
-142	Mk
-143	Mk
-144	Mk
-145	Mk
-146	Mk
-147	Mk
-148	Mk
-149	Mk
-150	Mk
-151	Mk
-152	Mk
-153	Mk
-154	Mk
-155	Mk
-156	Mk
-157	Mk
-158	Mk
-159	Mk
-0	progenitor
-1	progenitor
-2	progenitor
-3	progenitor
-4	progenitor
-5	progenitor
-6	progenitor
-7	progenitor
-8	progenitor
-9	progenitor
-10	progenitor
-11	progenitor
-12	progenitor
-13	progenitor
-14	progenitor
-15	progenitor
-16	progenitor
-17	progenitor
-18	progenitor
-19	progenitor
-20	progenitor
-21	progenitor
-22	progenitor
-23	progenitor
-24	progenitor
-25	progenitor
-26	progenitor
-27	progenitor
-28	progenitor
-29	progenitor
-30	progenitor
-31	progenitor
-32	progenitor
-33	progenitor
-34	progenitor
-35	progenitor
-36	progenitor
-37	progenitor
-38	progenitor
-39	progenitor
-40	progenitor
-41	progenitor
-42	progenitor
-43	progenitor
-44	progenitor
-45	progenitor
-46	progenitor
-47	progenitor
-48	progenitor
-49	progenitor
-50	progenitor
-51	progenitor
-52	progenitor
-53	progenitor
-54	progenitor
-55	progenitor
-56	progenitor
-57	progenitor
-58	progenitor
-59	progenitor
-60	progenitor
-61	progenitor
-62	progenitor
-63	progenitor
-64	progenitor
-65	progenitor
-66	progenitor
-67	progenitor
-68	progenitor
-69	progenitor
-70	progenitor
-71	progenitor
-72	progenitor
-73	progenitor
-74	progenitor
-75	progenitor
-76	progenitor
-77	progenitor
-78	progenitor
-79	progenitor
-80	Neu
-81	Neu
-82	Neu
-83	Neu
-84	Neu
-85	Neu
-86	Neu
-87	Neu
-88	Neu
-89	Neu
-90	Neu
-91	Neu
-92	Neu
-93	Neu
-94	Neu
-95	Neu
-96	Neu
-97	Neu
-98	Neu
-99	Neu
-100	Neu
-101	Neu
-102	Neu
-103	Neu
-104	Neu
-105	Neu
-106	Neu
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diff -r 9ca360dde8e3 -r a89ee42625ad test-data/sparce_csr_matrix.h5ad
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diff -r 9ca360dde8e3 -r a89ee42625ad test-data/tl.diffmap.neighbors_gauss_braycurtis.recipe_weinreb17.paul15_subsample.X_diffmap.tabular
--- a/test-data/tl.diffmap.neighbors_gauss_braycurtis.recipe_weinreb17.paul15_subsample.X_diffmap.tabular	Mon Mar 04 10:16:47 2019 -0500
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
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diff -r 9ca360dde8e3 -r a89ee42625ad test-data/tl.diffmap.neighbors_gauss_braycurtis.recipe_weinreb17.paul15_subsample.h5ad
Binary file test-data/tl.diffmap.neighbors_gauss_braycurtis.recipe_weinreb17.paul15_subsample.h5ad has changed
diff -r 9ca360dde8e3 -r a89ee42625ad test-data/tl.dpt.diffmap.neighbors_gauss_braycurtis.recipe_weinreb17.paul15_subsample.h5ad
Binary file test-data/tl.dpt.diffmap.neighbors_gauss_braycurtis.recipe_weinreb17.paul15_subsample.h5ad has changed
diff -r 9ca360dde8e3 -r a89ee42625ad test-data/tl.dpt.diffmap.neighbors_gauss_braycurtis.recipe_weinreb17.paul15_subsample.obs.tabular
--- a/test-data/tl.dpt.diffmap.neighbors_gauss_braycurtis.recipe_weinreb17.paul15_subsample.obs.tabular	Mon Mar 04 10:16:47 2019 -0500
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,101 +0,0 @@
-index	paul15_clusters	dpt_groups	dpt_order	dpt_order_indices
-578	13Baso	2	53	27
-2242	3Ery	1	30	46
-2690	10GMP	2	66	45
-70	5Ery	1	32	65
-758	15Mo	2	67	8
-465	16Neu	2	68	80
-245	16Neu	2	69	87
-2172	10GMP	2	70	90
-2680	10GMP	0	4	36
-1790	7MEP	2	71	59
-855	11DC	2	72	82
-2721	10GMP	2	73	30
-104	2Ery	1	38	62
-1106	2Ery	1	40	32
-2367	15Mo	3	93	35
-124	2Ery	1	41	37
-2477	8Mk	2	74	31
-1968	2Ery	1	42	78
-563	1Ery	1	43	28
-276	2Ery	1	44	56
-192	16Neu	2	75	42
-2409	2Ery	1	45	44
-2054	15Mo	3	95	75
-720	8Mk	2	76	48
-2225	14Mo	3	97	98
-878	6Ery	1	29	54
-156	7MEP	2	77	79
-1244	8Mk	0	0	40
-10	2Ery	1	18	83
-1108	6Ery	2	65	25
-353	5Ery	1	11	1
-182	5Ery	1	16	97
-2053	3Ery	1	13	3
-2291	16Neu	3	92	96
-2056	10GMP	2	79	95
-1047	2Ery	1	14	94
-1947	14Mo	0	8	92
-1390	3Ery	1	15	60
-2317	14Mo	2	90	12
-2348	11DC	2	82	69
-953	5Ery	1	27	13
-628	9GMP	2	83	15
-2691	5Ery	1	20	17
-1499	16Neu	3	96	18
-1083	2Ery	1	21	19
-831	14Mo	0	2	21
-15	7MEP	0	1	86
-2005	7MEP	2	87	66
-1662	3Ery	1	23	84
-2457	7MEP	2	64	89
-757	7MEP	2	81	70
-1642	14Mo	2	91	68
-2520	10GMP	2	89	67
-1393	7MEP	2	88	0
-2170	6Ery	1	25	73
-988	14Mo	2	86	76
-1338	2Ery	1	19	77
-2189	16Neu	2	85	81
-446	13Baso	2	84	85
-2276	14Mo	0	9	88
-317	2Ery	1	37	91
-1540	16Neu	3	99	93
-2164	4Ery	1	12	72
-227	15Mo	2	78	64
-906	12Baso	2	63	49
-716	15Mo	0	3	29
-912	14Mo	1	47	2
-2688	11DC	2	52	4
-1678	7MEP	2	51	5
-1063	6Ery	1	39	6
-1041	5Ery	1	50	7
-2279	15Mo	3	98	9
-558	13Baso	2	62	10
-2196	14Mo	2	54	11
-1270	13Baso	3	94	16
-2259	3Ery	1	22	20
-2410	13Baso	2	55	23
-886	7MEP	2	56	26
-2072	13Baso	1	17	63
-443	5Ery	1	26	34
-910	13Baso	0	5	99
-2608	15Mo	2	57	50
-2645	1Ery	1	10	39
-616	6Ery	1	28	41
-1866	2Ery	1	48	58
-923	7MEP	2	58	57
-1716	4Ery	1	46	55
-2476	11DC	0	6	47
-1872	10GMP	2	59	53
-1009	4Ery	1	49	52
-1680	6Ery	0	7	38
-1490	14Mo	2	60	51
-1454	2Ery	1	36	33
-2580	9GMP	2	61	14
-958	1Ery	1	35	74
-2626	2Ery	1	34	22
-1677	3Ery	1	33	43
-982	4Ery	1	31	24
-202	2Ery	1	24	71
-891	10GMP	2	80	61
diff -r 9ca360dde8e3 -r a89ee42625ad test-data/tl.draw_graph.pp.neighbors_umap_euclidean.recipe_weinreb17.paul15_subsample.h5ad
Binary file test-data/tl.draw_graph.pp.neighbors_umap_euclidean.recipe_weinreb17.paul15_subsample.h5ad has changed
diff -r 9ca360dde8e3 -r a89ee42625ad test-data/tl.leiden.neighbors_gauss_braycurtis.recipe_weinreb17.paul15_subsample.h5ad
Binary file test-data/tl.leiden.neighbors_gauss_braycurtis.recipe_weinreb17.paul15_subsample.h5ad has changed
diff -r 9ca360dde8e3 -r a89ee42625ad test-data/tl.louvain.neighbors_gauss_braycurtis.recipe_weinreb17.paul15_subsample.h5ad
Binary file test-data/tl.louvain.neighbors_gauss_braycurtis.recipe_weinreb17.paul15_subsample.h5ad has changed
diff -r 9ca360dde8e3 -r a89ee42625ad test-data/tl.paga.neighbors_gauss_braycurtis.recipe_weinreb17.paul15_subsample.h5ad
Binary file test-data/tl.paga.neighbors_gauss_braycurtis.recipe_weinreb17.paul15_subsample.h5ad has changed
diff -r 9ca360dde8e3 -r a89ee42625ad test-data/tl.pca.krumsiek11.h5ad
Binary file test-data/tl.pca.krumsiek11.h5ad has changed
diff -r 9ca360dde8e3 -r a89ee42625ad test-data/tl.rank_genes_groups.krumsiek11.h5ad
Binary file test-data/tl.rank_genes_groups.krumsiek11.h5ad has changed
diff -r 9ca360dde8e3 -r a89ee42625ad test-data/tl.rank_genes_groups.liblinear.krumsiek11.h5ad
Binary file test-data/tl.rank_genes_groups.liblinear.krumsiek11.h5ad has changed
diff -r 9ca360dde8e3 -r a89ee42625ad test-data/tl.rank_genes_groups.newton-cg.pbmc68k_reduced.h5ad
Binary file test-data/tl.rank_genes_groups.newton-cg.pbmc68k_reduced.h5ad has changed
diff -r 9ca360dde8e3 -r a89ee42625ad test-data/tl.score_genes.krumsiek11.h5ad
Binary file test-data/tl.score_genes.krumsiek11.h5ad has changed
diff -r 9ca360dde8e3 -r a89ee42625ad test-data/tl.score_genes.krumsiek11.obs.tabular
--- a/test-data/tl.score_genes.krumsiek11.obs.tabular	Mon Mar 04 10:16:47 2019 -0500
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,641 +0,0 @@
-index	cell_type	score
-0	progenitor	
-1	progenitor	
-2	progenitor	
-3	progenitor	
-4	progenitor	
-5	progenitor	
-6	progenitor	
-7	progenitor	
-8	progenitor	
-9	progenitor	
-10	progenitor	
-11	progenitor	
-12	progenitor	
-13	progenitor	
-14	progenitor	
-15	progenitor	
-16	progenitor	
-17	progenitor	
-18	progenitor	
-19	progenitor	
-20	progenitor	
-21	progenitor	
-22	progenitor	
-23	progenitor	
-24	progenitor	
-25	progenitor	
-26	progenitor	
-27	progenitor	
-28	progenitor	
-29	progenitor	
-30	progenitor	
-31	progenitor	
-32	progenitor	
-33	progenitor	
-34	progenitor	
-35	progenitor	
-36	progenitor	
-37	progenitor	
-38	progenitor	
-39	progenitor	
-40	progenitor	
-41	progenitor	
-42	progenitor	
-43	progenitor	
-44	progenitor	
-45	progenitor	
-46	progenitor	
-47	progenitor	
-48	progenitor	
-49	progenitor	
-50	progenitor	
-51	progenitor	
-52	progenitor	
-53	progenitor	
-54	progenitor	
-55	progenitor	
-56	progenitor	
-57	progenitor	
-58	progenitor	
-59	progenitor	
-60	progenitor	
-61	progenitor	
-62	progenitor	
-63	progenitor	
-64	progenitor	
-65	progenitor	
-66	progenitor	
-67	progenitor	
-68	progenitor	
-69	progenitor	
-70	progenitor	
-71	progenitor	
-72	progenitor	
-73	progenitor	
-74	progenitor	
-75	progenitor	
-76	progenitor	
-77	progenitor	
-78	progenitor	
-79	progenitor	
-80	Mo	
-81	Mo	
-82	Mo	
-83	Mo	
-84	Mo	
-85	Mo	
-86	Mo	
-87	Mo	
-88	Mo	
-89	Mo	
-90	Mo	
-91	Mo	
-92	Mo	
-93	Mo	
-94	Mo	
-95	Mo	
-96	Mo	
-97	Mo	
-98	Mo	
-99	Mo	
-100	Mo	
-101	Mo	
-102	Mo	
-103	Mo	
-104	Mo	
-105	Mo	
-106	Mo	
-107	Mo	
-108	Mo	
-109	Mo	
-110	Mo	
-111	Mo	
-112	Mo	
-113	Mo	
-114	Mo	
-115	Mo	
-116	Mo	
-117	Mo	
-118	Mo	
-119	Mo	
-120	Mo	
-121	Mo	
-122	Mo	
-123	Mo	
-124	Mo	
-125	Mo	
-126	Mo	
-127	Mo	
-128	Mo	
-129	Mo	
-130	Mo	
-131	Mo	
-132	Mo	
-133	Mo	
-134	Mo	
-135	Mo	
-136	Mo	
-137	Mo	
-138	Mo	
-139	Mo	
-140	Mo	
-141	Mo	
-142	Mo	
-143	Mo	
-144	Mo	
-145	Mo	
-146	Mo	
-147	Mo	
-148	Mo	
-149	Mo	
-150	Mo	
-151	Mo	
-152	Mo	
-153	Mo	
-154	Mo	
-155	Mo	
-156	Mo	
-157	Mo	
-158	Mo	
-159	Mo	
-0	progenitor	
-1	progenitor	
-2	progenitor	
-3	progenitor	
-4	progenitor	
-5	progenitor	
-6	progenitor	
-7	progenitor	
-8	progenitor	
-9	progenitor	
-10	progenitor	
-11	progenitor	
-12	progenitor	
-13	progenitor	
-14	progenitor	
-15	progenitor	
-16	progenitor	
-17	progenitor	
-18	progenitor	
-19	progenitor	
-20	progenitor	
-21	progenitor	
-22	progenitor	
-23	progenitor	
-24	progenitor	
-25	progenitor	
-26	progenitor	
-27	progenitor	
-28	progenitor	
-29	progenitor	
-30	progenitor	
-31	progenitor	
-32	progenitor	
-33	progenitor	
-34	progenitor	
-35	progenitor	
-36	progenitor	
-37	progenitor	
-38	progenitor	
-39	progenitor	
-40	progenitor	
-41	progenitor	
-42	progenitor	
-43	progenitor	
-44	progenitor	
-45	progenitor	
-46	progenitor	
-47	progenitor	
-48	progenitor	
-49	progenitor	
-50	progenitor	
-51	progenitor	
-52	progenitor	
-53	progenitor	
-54	progenitor	
-55	progenitor	
-56	progenitor	
-57	progenitor	
-58	progenitor	
-59	progenitor	
-60	progenitor	
-61	progenitor	
-62	progenitor	
-63	progenitor	
-64	progenitor	
-65	progenitor	
-66	progenitor	
-67	progenitor	
-68	progenitor	
-69	progenitor	
-70	progenitor	
-71	progenitor	
-72	progenitor	
-73	progenitor	
-74	progenitor	
-75	progenitor	
-76	progenitor	
-77	progenitor	
-78	progenitor	
-79	progenitor	
-80	Ery	
-81	Ery	
-82	Ery	
-83	Ery	
-84	Ery	
-85	Ery	
-86	Ery	
-87	Ery	
-88	Ery	
-89	Ery	
-90	Ery	
-91	Ery	
-92	Ery	
-93	Ery	
-94	Ery	
-95	Ery	
-96	Ery	
-97	Ery	
-98	Ery	
-99	Ery	
-100	Ery	
-101	Ery	
-102	Ery	
-103	Ery	
-104	Ery	
-105	Ery	
-106	Ery	
-107	Ery	
-108	Ery	
-109	Ery	
-110	Ery	
-111	Ery	
-112	Ery	
-113	Ery	
-114	Ery	
-115	Ery	
-116	Ery	
-117	Ery	
-118	Ery	
-119	Ery	
-120	Ery	
-121	Ery	
-122	Ery	
-123	Ery	
-124	Ery	
-125	Ery	
-126	Ery	
-127	Ery	
-128	Ery	
-129	Ery	
-130	Ery	
-131	Ery	
-132	Ery	
-133	Ery	
-134	Ery	
-135	Ery	
-136	Ery	
-137	Ery	
-138	Ery	
-139	Ery	
-140	Ery	
-141	Ery	
-142	Ery	
-143	Ery	
-144	Ery	
-145	Ery	
-146	Ery	
-147	Ery	
-148	Ery	
-149	Ery	
-150	Ery	
-151	Ery	
-152	Ery	
-153	Ery	
-154	Ery	
-155	Ery	
-156	Ery	
-157	Ery	
-158	Ery	
-159	Ery	
-0	progenitor	
-1	progenitor	
-2	progenitor	
-3	progenitor	
-4	progenitor	
-5	progenitor	
-6	progenitor	
-7	progenitor	
-8	progenitor	
-9	progenitor	
-10	progenitor	
-11	progenitor	
-12	progenitor	
-13	progenitor	
-14	progenitor	
-15	progenitor	
-16	progenitor	
-17	progenitor	
-18	progenitor	
-19	progenitor	
-20	progenitor	
-21	progenitor	
-22	progenitor	
-23	progenitor	
-24	progenitor	
-25	progenitor	
-26	progenitor	
-27	progenitor	
-28	progenitor	
-29	progenitor	
-30	progenitor	
-31	progenitor	
-32	progenitor	
-33	progenitor	
-34	progenitor	
-35	progenitor	
-36	progenitor	
-37	progenitor	
-38	progenitor	
-39	progenitor	
-40	progenitor	
-41	progenitor	
-42	progenitor	
-43	progenitor	
-44	progenitor	
-45	progenitor	
-46	progenitor	
-47	progenitor	
-48	progenitor	
-49	progenitor	
-50	progenitor	
-51	progenitor	
-52	progenitor	
-53	progenitor	
-54	progenitor	
-55	progenitor	
-56	progenitor	
-57	progenitor	
-58	progenitor	
-59	progenitor	
-60	progenitor	
-61	progenitor	
-62	progenitor	
-63	progenitor	
-64	progenitor	
-65	progenitor	
-66	progenitor	
-67	progenitor	
-68	progenitor	
-69	progenitor	
-70	progenitor	
-71	progenitor	
-72	progenitor	
-73	progenitor	
-74	progenitor	
-75	progenitor	
-76	progenitor	
-77	progenitor	
-78	progenitor	
-79	progenitor	
-80	Mk	
-81	Mk	
-82	Mk	
-83	Mk	
-84	Mk	
-85	Mk	
-86	Mk	
-87	Mk	
-88	Mk	
-89	Mk	
-90	Mk	
-91	Mk	
-92	Mk	
-93	Mk	
-94	Mk	
-95	Mk	
-96	Mk	
-97	Mk	
-98	Mk	
-99	Mk	
-100	Mk	
-101	Mk	
-102	Mk	
-103	Mk	
-104	Mk	
-105	Mk	
-106	Mk	
-107	Mk	
-108	Mk	
-109	Mk	
-110	Mk	
-111	Mk	
-112	Mk	
-113	Mk	
-114	Mk	
-115	Mk	
-116	Mk	
-117	Mk	
-118	Mk	
-119	Mk	
-120	Mk	
-121	Mk	
-122	Mk	
-123	Mk	
-124	Mk	
-125	Mk	
-126	Mk	
-127	Mk	
-128	Mk	
-129	Mk	
-130	Mk	
-131	Mk	
-132	Mk	
-133	Mk	
-134	Mk	
-135	Mk	
-136	Mk	
-137	Mk	
-138	Mk	
-139	Mk	
-140	Mk	
-141	Mk	
-142	Mk	
-143	Mk	
-144	Mk	
-145	Mk	
-146	Mk	
-147	Mk	
-148	Mk	
-149	Mk	
-150	Mk	
-151	Mk	
-152	Mk	
-153	Mk	
-154	Mk	
-155	Mk	
-156	Mk	
-157	Mk	
-158	Mk	
-159	Mk	
-0	progenitor	
-1	progenitor	
-2	progenitor	
-3	progenitor	
-4	progenitor	
-5	progenitor	
-6	progenitor	
-7	progenitor	
-8	progenitor	
-9	progenitor	
-10	progenitor	
-11	progenitor	
-12	progenitor	
-13	progenitor	
-14	progenitor	
-15	progenitor	
-16	progenitor	
-17	progenitor	
-18	progenitor	
-19	progenitor	
-20	progenitor	
-21	progenitor	
-22	progenitor	
-23	progenitor	
-24	progenitor	
-25	progenitor	
-26	progenitor	
-27	progenitor	
-28	progenitor	
-29	progenitor	
-30	progenitor	
-31	progenitor	
-32	progenitor	
-33	progenitor	
-34	progenitor	
-35	progenitor	
-36	progenitor	
-37	progenitor	
-38	progenitor	
-39	progenitor	
-40	progenitor	
-41	progenitor	
-42	progenitor	
-43	progenitor	
-44	progenitor	
-45	progenitor	
-46	progenitor	
-47	progenitor	
-48	progenitor	
-49	progenitor	
-50	progenitor	
-51	progenitor	
-52	progenitor	
-53	progenitor	
-54	progenitor	
-55	progenitor	
-56	progenitor	
-57	progenitor	
-58	progenitor	
-59	progenitor	
-60	progenitor	
-61	progenitor	
-62	progenitor	
-63	progenitor	
-64	progenitor	
-65	progenitor	
-66	progenitor	
-67	progenitor	
-68	progenitor	
-69	progenitor	
-70	progenitor	
-71	progenitor	
-72	progenitor	
-73	progenitor	
-74	progenitor	
-75	progenitor	
-76	progenitor	
-77	progenitor	
-78	progenitor	
-79	progenitor	
-80	Neu	
-81	Neu	
-82	Neu	
-83	Neu	
-84	Neu	
-85	Neu	
-86	Neu	
-87	Neu	
-88	Neu	
-89	Neu	
-90	Neu	
-91	Neu	
-92	Neu	
-93	Neu	
-94	Neu	
-95	Neu	
-96	Neu	
-97	Neu	
-98	Neu	
-99	Neu	
-100	Neu	
-101	Neu	
-102	Neu	
-103	Neu	
-104	Neu	
-105	Neu	
-106	Neu	
-107	Neu	
-108	Neu	
-109	Neu	
-110	Neu	
-111	Neu	
-112	Neu	
-113	Neu	
-114	Neu	
-115	Neu	
-116	Neu	
-117	Neu	
-118	Neu	
-119	Neu	
-120	Neu	
-121	Neu	
-122	Neu	
-123	Neu	
-124	Neu	
-125	Neu	
-126	Neu	
-127	Neu	
-128	Neu	
-129	Neu	
-130	Neu	
-131	Neu	
-132	Neu	
-133	Neu	
-134	Neu	
-135	Neu	
-136	Neu	
-137	Neu	
-138	Neu	
-139	Neu	
-140	Neu	
-141	Neu	
-142	Neu	
-143	Neu	
-144	Neu	
-145	Neu	
-146	Neu	
-147	Neu	
-148	Neu	
-149	Neu	
-150	Neu	
-151	Neu	
-152	Neu	
-153	Neu	
-154	Neu	
-155	Neu	
-156	Neu	
-157	Neu	
-158	Neu	
-159	Neu	
diff -r 9ca360dde8e3 -r a89ee42625ad test-data/tl.score_genes_cell_cycle.krumsiek11.h5ad
Binary file test-data/tl.score_genes_cell_cycle.krumsiek11.h5ad has changed
diff -r 9ca360dde8e3 -r a89ee42625ad test-data/tl.score_genes_cell_cycle.krumsiek11.obs.tabular
--- a/test-data/tl.score_genes_cell_cycle.krumsiek11.obs.tabular	Mon Mar 04 10:16:47 2019 -0500
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,641 +0,0 @@
-index	cell_type	S_score	G2M_score	phase
-0	progenitor	0.2681	0.20055	S
-1	progenitor	0.24346666	0.15855001	S
-2	progenitor	0.2276	0.13482499	S
-3	progenitor	0.21043333	0.12637499	S
-4	progenitor	0.19113334	0.1272	S
-5	progenitor	0.17531666	0.13072497	S
-6	progenitor	0.16073334	0.13242501	S
-7	progenitor	0.15353334	0.13672501	S
-8	progenitor	0.14314999	0.1399	S
-9	progenitor	0.1337	0.14515	G2M
-10	progenitor	0.12695001	0.15165001	G2M
-11	progenitor	0.11726667	0.16077498	G2M
-12	progenitor	0.11081667	0.16735	G2M
-13	progenitor	0.104849994	0.17429999	G2M
-14	progenitor	0.09816667	0.18152499	G2M
-15	progenitor	0.095350005	0.186625	G2M
-16	progenitor	0.09528333	0.19447501	G2M
-17	progenitor	0.09463333	0.199675	G2M
-18	progenitor	0.0947	0.205275	G2M
-19	progenitor	0.0947	0.20802501	G2M
-20	progenitor	0.097733326	0.21100001	G2M
-21	progenitor	0.09881667	0.21964999	G2M
-22	progenitor	0.10131666	0.22662501	G2M
-23	progenitor	0.104849994	0.23022501	G2M
-24	progenitor	0.112266675	0.23387499	G2M
-25	progenitor	0.120283335	0.2393	G2M
-26	progenitor	0.12826668	0.24174997	G2M
-27	progenitor	0.13323334	0.24710001	G2M
-28	progenitor	0.13971666	0.25280002	G2M
-29	progenitor	0.14393334	0.256775	G2M
-30	progenitor	0.15066667	0.259775	G2M
-31	progenitor	0.15316668	0.26244998	G2M
-32	progenitor	0.15993333	0.26487502	G2M
-33	progenitor	0.16430001	0.266275	G2M
-34	progenitor	0.16598332	0.270625	G2M
-35	progenitor	0.17068332	0.2715	G2M
-36	progenitor	0.17713334	0.276475	G2M
-37	progenitor	0.17893334	0.27514997	G2M
-38	progenitor	0.18013333	0.278025	G2M
-39	progenitor	0.18251666	0.279675	G2M
-40	progenitor	0.18876666	0.27925	G2M
-41	progenitor	0.19041668	0.281775	G2M
-42	progenitor	0.19083333	0.2824	G2M
-43	progenitor	0.19411668	0.281725	G2M
-44	progenitor	0.19639999	0.2844	G2M
-45	progenitor	0.19843334	0.285375	G2M
-46	progenitor	0.20406666	0.284075	G2M
-47	progenitor	0.20673332	0.28625	G2M
-48	progenitor	0.20769998	0.2885	G2M
-49	progenitor	0.21186668	0.28935	G2M
-50	progenitor	0.21285	0.28867498	G2M
-51	progenitor	0.21443334	0.28855002	G2M
-52	progenitor	0.21568334	0.28705	G2M
-53	progenitor	0.21788335	0.29035	G2M
-54	progenitor	0.22551665	0.28815	G2M
-55	progenitor	0.22586668	0.28689998	G2M
-56	progenitor	0.23069999	0.2816	G2M
-57	progenitor	0.23118332	0.282375	G2M
-58	progenitor	0.23160002	0.28230003	G2M
-59	progenitor	0.23546667	0.28329998	G2M
-60	progenitor	0.23661667	0.28195	G2M
-61	progenitor	0.24134998	0.27899998	G2M
-62	progenitor	0.24546666	0.27855	G2M
-63	progenitor	0.24836665	0.27609998	G2M
-64	progenitor	0.25375	0.27562502	G2M
-65	progenitor	0.25834998	0.273525	G2M
-66	progenitor	0.26393333	0.27015	G2M
-67	progenitor	0.26746666	0.26622498	S
-68	progenitor	0.2706333	0.267025	S
-69	progenitor	0.27618334	0.2651	S
-70	progenitor	0.28033334	0.263975	S
-71	progenitor	0.2868167	0.2622	S
-72	progenitor	0.29141667	0.26174998	S
-73	progenitor	0.29198334	0.26385	S
-74	progenitor	0.29348332	0.26275003	S
-75	progenitor	0.29788333	0.263575	S
-76	progenitor	0.30125	0.26232502	S
-77	progenitor	0.29955	0.261825	S
-78	progenitor	0.30065	0.2623	S
-79	progenitor	0.30573332	0.2588	S
-80	Mo	0.30818334	0.25555003	S
-81	Mo	0.31073332	0.25422502	S
-82	Mo	0.31378332	0.25410002	S
-83	Mo	0.31268334	0.25304997	S
-84	Mo	0.31355	0.25059998	S
-85	Mo	0.3157	0.251275	S
-86	Mo	0.3139333	0.25072497	S
-87	Mo	0.3151833	0.25165	S
-88	Mo	0.3149333	0.25079998	S
-89	Mo	0.31440002	0.25172502	S
-90	Mo	0.31251666	0.254725	S
-91	Mo	0.31613332	0.25347498	S
-92	Mo	0.31813332	0.25372502	S
-93	Mo	0.31543335	0.25340003	S
-94	Mo	0.31663334	0.257025	S
-95	Mo	0.31793332	0.25435	S
-96	Mo	0.3184333	0.2527	S
-97	Mo	0.31743336	0.25052497	S
-98	Mo	0.3164667	0.24747501	S
-99	Mo	0.31841668	0.2466	S
-100	Mo	0.31648335	0.24679999	S
-101	Mo	0.31504998	0.2501	S
-102	Mo	0.31489998	0.250375	S
-103	Mo	0.31256667	0.25195	S
-104	Mo	0.31425	0.250675	S
-105	Mo	0.31441668	0.248675	S
-106	Mo	0.31828332	0.24724999	S
-107	Mo	0.32236665	0.25105	S
-108	Mo	0.32341668	0.2527	S
-109	Mo	0.32334998	0.25145	S
-110	Mo	0.32061666	0.2516	S
-111	Mo	0.3239333	0.24855	S
-112	Mo	0.3217833	0.248275	S
-113	Mo	0.3194833	0.25055	S
-114	Mo	0.32711667	0.24814999	S
-115	Mo	0.32861665	0.244375	S
-116	Mo	0.33048332	0.244225	S
-117	Mo	0.33173332	0.24415	S
-118	Mo	0.32801664	0.24665	S
-119	Mo	0.3321833	0.245675	S
-120	Mo	0.32905	0.24717501	S
-121	Mo	0.33133334	0.245975	S
-122	Mo	0.33201668	0.24515	S
-123	Mo	0.33265	0.24475	S
-124	Mo	0.32968336	0.24344999	S
-125	Mo	0.32461664	0.245175	S
-126	Mo	0.32303333	0.24647498	S
-127	Mo	0.32363334	0.24472499	S
-128	Mo	0.3234	0.24480002	S
-129	Mo	0.32494998	0.24702501	S
-130	Mo	0.32526666	0.24975002	S
-131	Mo	0.32278332	0.24785002	S
-132	Mo	0.3201	0.24885	S
-133	Mo	0.32130003	0.25125	S
-134	Mo	0.32468334	0.2521	S
-135	Mo	0.32040003	0.25545	S
-136	Mo	0.31931666	0.25560004	S
-137	Mo	0.31963333	0.25262502	S
-138	Mo	0.31644997	0.253575	S
-139	Mo	0.31913334	0.251575	S
-140	Mo	0.32393336	0.24987501	S
-141	Mo	0.32683334	0.2504	S
-142	Mo	0.32791668	0.24740002	S
-143	Mo	0.329	0.247075	S
-144	Mo	0.32784998	0.24852501	S
-145	Mo	0.32766664	0.24740002	S
-146	Mo	0.32676667	0.2485	S
-147	Mo	0.3254	0.24985	S
-148	Mo	0.32301664	0.24805	S
-149	Mo	0.32369998	0.25047502	S
-150	Mo	0.3267	0.250475	S
-151	Mo	0.3280667	0.252875	S
-152	Mo	0.32885	0.25315002	S
-153	Mo	0.32688335	0.2515	S
-154	Mo	0.32666668	0.25325	S
-155	Mo	0.3258167	0.25137502	S
-156	Mo	0.32818332	0.2465	S
-157	Mo	0.32963336	0.24692501	S
-158	Mo	0.3318167	0.24837498	S
-159	Mo	0.33176666	0.247625	S
-0	progenitor	0.26751667	0.2007	S
-1	progenitor	0.24345	0.157325	S
-2	progenitor	0.22616667	0.139575	S
-3	progenitor	0.20503333	0.13499999	S
-4	progenitor	0.18988334	0.1349	S
-5	progenitor	0.17425	0.134875	S
-6	progenitor	0.16213334	0.13455	S
-7	progenitor	0.14678332	0.14125	S
-8	progenitor	0.1336	0.146375	G2M
-9	progenitor	0.1237	0.15342501	G2M
-10	progenitor	0.11621666	0.16017501	G2M
-11	progenitor	0.10858333	0.1669	G2M
-12	progenitor	0.09945001	0.17515	G2M
-13	progenitor	0.09445	0.182875	G2M
-14	progenitor	0.091649994	0.18862501	G2M
-15	progenitor	0.08881667	0.196275	G2M
-16	progenitor	0.08878334	0.20034999	G2M
-17	progenitor	0.09183334	0.208125	G2M
-18	progenitor	0.094516665	0.21419999	G2M
-19	progenitor	0.094349995	0.223	G2M
-20	progenitor	0.09643334	0.228775	G2M
-21	progenitor	0.09933333	0.232925	G2M
-22	progenitor	0.10111666	0.2406	G2M
-23	progenitor	0.10683333	0.24365	G2M
-24	progenitor	0.11198333	0.24744998	G2M
-25	progenitor	0.1187	0.24800001	G2M
-26	progenitor	0.12223333	0.253475	G2M
-27	progenitor	0.12516668	0.25777498	G2M
-28	progenitor	0.13296667	0.261875	G2M
-29	progenitor	0.13638332	0.2664	G2M
-30	progenitor	0.14060001	0.27075002	G2M
-31	progenitor	0.14363334	0.27295002	G2M
-32	progenitor	0.14310001	0.277825	G2M
-33	progenitor	0.14686668	0.2806	G2M
-34	progenitor	0.14746666	0.28705	G2M
-35	progenitor	0.1488	0.291375	G2M
-36	progenitor	0.14686665	0.295125	G2M
-37	progenitor	0.14803334	0.29590002	G2M
-38	progenitor	0.14774999	0.30242503	G2M
-39	progenitor	0.14461668	0.30615002	G2M
-40	progenitor	0.14245	0.3091	G2M
-41	progenitor	0.14150001	0.313175	G2M
-42	progenitor	0.13565	0.316325	G2M
-43	progenitor	0.12808332	0.3198	G2M
-44	progenitor	0.12049997	0.3262	G2M
-45	progenitor	0.11080001	0.33355	G2M
-46	progenitor	0.09916668	0.33852503	G2M
-47	progenitor	0.08836666	0.34457502	G2M
-48	progenitor	0.0756	0.35015002	G2M
-49	progenitor	0.061966658	0.354175	G2M
-50	progenitor	0.04515001	0.361325	G2M
-51	progenitor	0.026250005	0.365675	G2M
-52	progenitor	0.008533329	0.371575	G2M
-53	progenitor	-0.0058666766	0.36895004	G2M
-54	progenitor	-0.01971668	0.36967498	G2M
-55	progenitor	-0.035949945	0.36804998	G2M
-56	progenitor	-0.04824999	0.36305	G2M
-57	progenitor	-0.06161666	0.35704997	G2M
-58	progenitor	-0.07620004	0.34805	G2M
-59	progenitor	-0.09081668	0.341575	G2M
-60	progenitor	-0.103000015	0.32840002	G2M
-61	progenitor	-0.11609998	0.317375	G2M
-62	progenitor	-0.12736666	0.30952498	G2M
-63	progenitor	-0.13890001	0.30077502	G2M
-64	progenitor	-0.15153334	0.28985	G2M
-65	progenitor	-0.16445002	0.28004998	G2M
-66	progenitor	-0.17231664	0.26997498	G2M
-67	progenitor	-0.18360004	0.2623	G2M
-68	progenitor	-0.19526666	0.250675	G2M
-69	progenitor	-0.20973334	0.24382502	G2M
-70	progenitor	-0.22153333	0.23462497	G2M
-71	progenitor	-0.23176664	0.22642499	G2M
-72	progenitor	-0.23878333	0.21525	G2M
-73	progenitor	-0.24899998	0.20759997	G2M
-74	progenitor	-0.25769997	0.196425	G2M
-75	progenitor	-0.266	0.190525	G2M
-76	progenitor	-0.27291664	0.185325	G2M
-77	progenitor	-0.27909997	0.17939998	G2M
-78	progenitor	-0.28546664	0.16992497	G2M
-79	progenitor	-0.2924833	0.16142498	G2M
-80	Ery	-0.30063334	0.158275	G2M
-81	Ery	-0.3081833	0.14844999	G2M
-82	Ery	-0.31410003	0.13829997	G2M
-83	Ery	-0.32265	0.12857503	G2M
-84	Ery	-0.33280006	0.12172499	G2M
-85	Ery	-0.34323335	0.11087498	G2M
-86	Ery	-0.3550667	0.09400001	G2M
-87	Ery	-0.36045003	0.074499995	G2M
-88	Ery	-0.36565	0.056499988	G2M
-89	Ery	-0.37118334	0.03820002	G2M
-90	Ery	-0.3749	0.026174992	G2M
-91	Ery	-0.37931666	0.019950002	G2M
-92	Ery	-0.38785002	0.012800008	G2M
-93	Ery	-0.3930334	0.0039000213	G2M
-94	Ery	-0.39623332	-0.0038750172	G1
-95	Ery	-0.40098336	-0.008474976	G1
-96	Ery	-0.41044998	-0.008125007	G1
-97	Ery	-0.41723332	-0.0113250315	G1
-98	Ery	-0.42673334	-0.008574992	G1
-99	Ery	-0.43113336	-0.009875029	G1
-100	Ery	-0.4387667	-0.009699941	G1
-101	Ery	-0.44501665	-0.006850004	G1
-102	Ery	-0.44808337	-0.0041999817	G1
-103	Ery	-0.45334998	-0.0044499934	G1
-104	Ery	-0.4579167	-0.0024499893	G1
-105	Ery	-0.4625	0.0014250278	G2M
-106	Ery	-0.46655002	0.003275007	G2M
-107	Ery	-0.4705	0.0074749887	G2M
-108	Ery	-0.47354996	0.011525005	G2M
-109	Ery	-0.47571668	0.012849987	G2M
-110	Ery	-0.47741672	0.014274985	G2M
-111	Ery	-0.47899997	0.015850008	G2M
-112	Ery	-0.48184994	0.017825007	G2M
-113	Ery	-0.48310003	0.021875024	G2M
-114	Ery	-0.48716664	0.023850024	G2M
-115	Ery	-0.48626667	0.024949968	G2M
-116	Ery	-0.4891	0.03274998	G2M
-117	Ery	-0.4909666	0.035274982	G2M
-118	Ery	-0.4974334	0.037799954	G2M
-119	Ery	-0.5008334	0.040574998	G2M
-120	Ery	-0.50525	0.044800013	G2M
-121	Ery	-0.50745004	0.045899987	G2M
-122	Ery	-0.51255	0.048699975	G2M
-123	Ery	-0.5148666	0.051825017	G2M
-124	Ery	-0.51621664	0.054074973	G2M
-125	Ery	-0.52003336	0.058725	G2M
-126	Ery	-0.5201167	0.06525004	G2M
-127	Ery	-0.5232334	0.06755	G2M
-128	Ery	-0.5255166	0.06912503	G2M
-129	Ery	-0.52691674	0.071750015	G2M
-130	Ery	-0.5294833	0.07469997	G2M
-131	Ery	-0.5308	0.07885	G2M
-132	Ery	-0.53328335	0.08200002	G2M
-133	Ery	-0.53339994	0.082275	G2M
-134	Ery	-0.5356667	0.08287498	G2M
-135	Ery	-0.53651667	0.083850026	G2M
-136	Ery	-0.53586674	0.08415002	G2M
-137	Ery	-0.5371834	0.08655003	G2M
-138	Ery	-0.53768337	0.08915001	G2M
-139	Ery	-0.5387167	0.086775005	G2M
-140	Ery	-0.5398166	0.08837497	G2M
-141	Ery	-0.5402333	0.09094998	G2M
-142	Ery	-0.5395833	0.09077501	G2M
-143	Ery	-0.5413166	0.094074994	G2M
-144	Ery	-0.5375334	0.094500035	G2M
-145	Ery	-0.5376667	0.09659997	G2M
-146	Ery	-0.5442666	0.09917498	G2M
-147	Ery	-0.5433	0.10099995	G2M
-148	Ery	-0.54293334	0.09899998	G2M
-149	Ery	-0.5396333	0.09729999	G2M
-150	Ery	-0.53550005	0.09580001	G2M
-151	Ery	-0.5340333	0.094500005	G2M
-152	Ery	-0.53835	0.094024986	G2M
-153	Ery	-0.5339166	0.09344998	G2M
-154	Ery	-0.5354667	0.095400006	G2M
-155	Ery	-0.5398333	0.09622499	G2M
-156	Ery	-0.54073334	0.09739998	G2M
-157	Ery	-0.54269993	0.09609997	G2M
-158	Ery	-0.54613334	0.09427503	G2M
-159	Ery	-0.5469167	0.09325001	G2M
-0	progenitor	0.26924998	0.20047499	S
-1	progenitor	0.24753334	0.15694998	S
-2	progenitor	0.2261	0.129575	S
-3	progenitor	0.20549999	0.12205	S
-4	progenitor	0.18906666	0.118075006	S
-5	progenitor	0.17461666	0.1156	S
-6	progenitor	0.1549	0.112900004	S
-7	progenitor	0.14206666	0.11277501	S
-8	progenitor	0.12825	0.11547499	S
-9	progenitor	0.11403333	0.116174996	G2M
-10	progenitor	0.10465	0.11955001	G2M
-11	progenitor	0.09291667	0.123825	G2M
-12	progenitor	0.08646667	0.12455	G2M
-13	progenitor	0.07824999	0.13115	G2M
-14	progenitor	0.07111666	0.13497499	G2M
-15	progenitor	0.06305	0.138225	G2M
-16	progenitor	0.059816666	0.14175001	G2M
-17	progenitor	0.055983335	0.1487	G2M
-18	progenitor	0.05093333	0.15525001	G2M
-19	progenitor	0.048833337	0.161075	G2M
-20	progenitor	0.047583334	0.16835001	G2M
-21	progenitor	0.040233333	0.1783	G2M
-22	progenitor	0.038650002	0.18339998	G2M
-23	progenitor	0.034033336	0.19080001	G2M
-24	progenitor	0.0334	0.19689998	G2M
-25	progenitor	0.036050003	0.19765002	G2M
-26	progenitor	0.037483335	0.20150003	G2M
-27	progenitor	0.0379	0.205475	G2M
-28	progenitor	0.03891667	0.21019998	G2M
-29	progenitor	0.041166663	0.21605001	G2M
-30	progenitor	0.041533336	0.22262499	G2M
-31	progenitor	0.0463	0.226375	G2M
-32	progenitor	0.048683327	0.22929999	G2M
-33	progenitor	0.057249997	0.233375	G2M
-34	progenitor	0.06268333	0.236	G2M
-35	progenitor	0.06565	0.23992498	G2M
-36	progenitor	0.06738335	0.24414998	G2M
-37	progenitor	0.07278331	0.24974999	G2M
-38	progenitor	0.07835	0.25365	G2M
-39	progenitor	0.08574999	0.25655	G2M
-40	progenitor	0.089816675	0.25997502	G2M
-41	progenitor	0.094816685	0.268325	G2M
-42	progenitor	0.10088334	0.27127498	G2M
-43	progenitor	0.10618336	0.27574998	G2M
-44	progenitor	0.11181665	0.27997503	G2M
-45	progenitor	0.12016666	0.28125003	G2M
-46	progenitor	0.120766655	0.2857	G2M
-47	progenitor	0.12061668	0.289625	G2M
-48	progenitor	0.12701666	0.292675	G2M
-49	progenitor	0.13323334	0.294025	G2M
-50	progenitor	0.13686669	0.29399997	G2M
-51	progenitor	0.14141665	0.296375	G2M
-52	progenitor	0.14054999	0.29835	G2M
-53	progenitor	0.13769999	0.30177498	G2M
-54	progenitor	0.13920003	0.306425	G2M
-55	progenitor	0.13541666	0.30935	G2M
-56	progenitor	0.13395001	0.31435	G2M
-57	progenitor	0.12931666	0.319175	G2M
-58	progenitor	0.12291667	0.32285002	G2M
-59	progenitor	0.11760001	0.32947502	G2M
-60	progenitor	0.1109	0.33325002	G2M
-61	progenitor	0.098733336	0.33807498	G2M
-62	progenitor	0.08863334	0.345725	G2M
-63	progenitor	0.074066654	0.347775	G2M
-64	progenitor	0.062050015	0.3543	G2M
-65	progenitor	0.050833344	0.359575	G2M
-66	progenitor	0.038566664	0.36534998	G2M
-67	progenitor	0.022033334	0.37015	G2M
-68	progenitor	0.009916633	0.37007502	G2M
-69	progenitor	-0.002099961	0.37010002	G2M
-70	progenitor	-0.013416678	0.36807504	G2M
-71	progenitor	-0.026216656	0.36464998	G2M
-72	progenitor	-0.04154995	0.357625	G2M
-73	progenitor	-0.054400027	0.35250002	G2M
-74	progenitor	-0.06606665	0.3451	G2M
-75	progenitor	-0.07311666	0.33777502	G2M
-76	progenitor	-0.077833325	0.32635	G2M
-77	progenitor	-0.08776665	0.3159	G2M
-78	progenitor	-0.09445	0.30395	G2M
-79	progenitor	-0.102666676	0.2935	G2M
-80	Mk	-0.10896668	0.282375	G2M
-81	Mk	-0.12169999	0.27165002	G2M
-82	Mk	-0.12861666	0.26255003	G2M
-83	Mk	-0.13356665	0.2516	G2M
-84	Mk	-0.1381667	0.2421	G2M
-85	Mk	-0.14588335	0.23299998	G2M
-86	Mk	-0.14643335	0.220175	G2M
-87	Mk	-0.15011665	0.216025	G2M
-88	Mk	-0.15608332	0.20797502	G2M
-89	Mk	-0.1635333	0.20320001	G2M
-90	Mk	-0.1667167	0.19779998	G2M
-91	Mk	-0.16811666	0.18747498	G2M
-92	Mk	-0.16958332	0.17795	G2M
-93	Mk	-0.17056668	0.16855001	G2M
-94	Mk	-0.17408332	0.16107498	G2M
-95	Mk	-0.17345	0.1532	G2M
-96	Mk	-0.17251664	0.147325	G2M
-97	Mk	-0.17686662	0.141125	G2M
-98	Mk	-0.17819998	0.1339	G2M
-99	Mk	-0.18205002	0.12702498	G2M
-100	Mk	-0.18008336	0.12057501	G2M
-101	Mk	-0.17778334	0.10987502	G2M
-102	Mk	-0.17706665	0.10052502	G2M
-103	Mk	-0.17208335	0.09229997	G2M
-104	Mk	-0.17455	0.09097502	G2M
-105	Mk	-0.17273334	0.087374985	G2M
-106	Mk	-0.17373335	0.08560002	G2M
-107	Mk	-0.17395002	0.07944998	G2M
-108	Mk	-0.17468333	0.07655001	G2M
-109	Mk	-0.1739833	0.07757497	G2M
-110	Mk	-0.17766666	0.08107501	G2M
-111	Mk	-0.17615	0.07807499	G2M
-112	Mk	-0.17605004	0.077325016	G2M
-113	Mk	-0.17686665	0.07712501	G2M
-114	Mk	-0.17955002	0.07734999	G2M
-115	Mk	-0.17851666	0.07519999	G2M
-116	Mk	-0.17718336	0.076775014	G2M
-117	Mk	-0.17596671	0.07339999	G2M
-118	Mk	-0.1750167	0.07412499	G2M
-119	Mk	-0.17744997	0.076675	G2M
-120	Mk	-0.1789	0.074625015	G2M
-121	Mk	-0.17714998	0.071624994	G2M
-122	Mk	-0.1736333	0.068425	G2M
-123	Mk	-0.17461663	0.06832498	G2M
-124	Mk	-0.17366666	0.069875	G2M
-125	Mk	-0.17350003	0.07087502	G2M
-126	Mk	-0.17423335	0.073125005	G2M
-127	Mk	-0.17289999	0.07657498	G2M
-128	Mk	-0.17336664	0.07489997	G2M
-129	Mk	-0.16989997	0.07117501	G2M
-130	Mk	-0.16938332	0.06972501	G2M
-131	Mk	-0.17073336	0.07189995	G2M
-132	Mk	-0.16995004	0.07332501	G2M
-133	Mk	-0.16946661	0.07052502	G2M
-134	Mk	-0.16478333	0.070250005	G2M
-135	Mk	-0.16570002	0.072375	G2M
-136	Mk	-0.16755003	0.073075026	G2M
-137	Mk	-0.16876668	0.076124996	G2M
-138	Mk	-0.16663334	0.07460004	G2M
-139	Mk	-0.1660833	0.07682499	G2M
-140	Mk	-0.16843331	0.0783	G2M
-141	Mk	-0.17143327	0.07712501	G2M
-142	Mk	-0.17213336	0.07727498	G2M
-143	Mk	-0.16951668	0.07885	G2M
-144	Mk	-0.16820005	0.078149974	G2M
-145	Mk	-0.16826665	0.07882503	G2M
-146	Mk	-0.17055002	0.08182496	G2M
-147	Mk	-0.17345	0.082975	G2M
-148	Mk	-0.17216668	0.086125016	G2M
-149	Mk	-0.17273334	0.09057501	G2M
-150	Mk	-0.17401668	0.092824996	G2M
-151	Mk	-0.17518333	0.091575	G2M
-152	Mk	-0.17483333	0.09237501	G2M
-153	Mk	-0.17593333	0.092875004	G2M
-154	Mk	-0.1739333	0.094374955	G2M
-155	Mk	-0.1740667	0.09417495	G2M
-156	Mk	-0.17770004	0.09324998	G2M
-157	Mk	-0.17335	0.09350002	G2M
-158	Mk	-0.1704	0.09047499	G2M
-159	Mk	-0.17143336	0.089825004	G2M
-0	progenitor	0.2660833	0.20005001	S
-1	progenitor	0.24146667	0.1564	S
-2	progenitor	0.22096668	0.12695	S
-3	progenitor	0.19886668	0.112325005	S
-4	progenitor	0.18153334	0.102675	S
-5	progenitor	0.16055	0.10249999	S
-6	progenitor	0.14478332	0.098000005	S
-7	progenitor	0.13021666	0.092875004	S
-8	progenitor	0.11686668	0.091899976	S
-9	progenitor	0.10476667	0.091975	S
-10	progenitor	0.09625	0.094950005	S
-11	progenitor	0.09105	0.09615001	G2M
-12	progenitor	0.0822	0.102025	G2M
-13	progenitor	0.074	0.10612498	G2M
-14	progenitor	0.062583335	0.10890001	G2M
-15	progenitor	0.052600004	0.11175001	G2M
-16	progenitor	0.045050006	0.112574995	G2M
-17	progenitor	0.038033333	0.11227499	G2M
-18	progenitor	0.03231667	0.11082502	G2M
-19	progenitor	0.028383333	0.11277501	G2M
-20	progenitor	0.021966662	0.11262502	G2M
-21	progenitor	0.02043334	0.110575005	G2M
-22	progenitor	0.017400004	0.110875025	G2M
-23	progenitor	0.017300002	0.111875	G2M
-24	progenitor	0.015683334	0.112075	G2M
-25	progenitor	0.014233332	0.11295	G2M
-26	progenitor	0.012683332	0.11170004	G2M
-27	progenitor	0.011016667	0.112225026	G2M
-28	progenitor	0.010216668	0.116024986	G2M
-29	progenitor	0.0077833347	0.11819999	G2M
-30	progenitor	0.004733335	0.119224995	G2M
-31	progenitor	0.002683334	0.12180002	G2M
-32	progenitor	0.006133329	0.11839999	G2M
-33	progenitor	0.0052000023	0.116349995	G2M
-34	progenitor	0.006116666	0.115775004	G2M
-35	progenitor	0.0019833297	0.115449995	G2M
-36	progenitor	0.0007166676	0.114999995	G2M
-37	progenitor	0.00016666204	0.113325	G2M
-38	progenitor	-0.0018666722	0.116224974	G2M
-39	progenitor	-0.0030833334	0.11517501	G2M
-40	progenitor	-0.0030166656	0.11082499	G2M
-41	progenitor	-0.0019833334	0.10034999	G2M
-42	progenitor	0.0010500029	0.094025	G2M
-43	progenitor	-0.0039666668	0.086150005	G2M
-44	progenitor	-0.0024000034	0.077549994	G2M
-45	progenitor	-0.0036166683	0.07370001	G2M
-46	progenitor	-0.00485	0.0651	G2M
-47	progenitor	-0.002550004	0.05520001	G2M
-48	progenitor	0.0003666673	0.041975006	G2M
-49	progenitor	-0.0010499991	0.030874997	G2M
-50	progenitor	0.0007333346	0.014625013	G2M
-51	progenitor	9.999983e-05	-0.0017999709	S
-52	progenitor	0.0018333336	-0.01987499	S
-53	progenitor	0.00090000033	-0.032900006	S
-54	progenitor	0.0029999996	-0.05064997	S
-55	progenitor	0.003983334	-0.068574995	S
-56	progenitor	-0.0008500004	-0.08140004	G1
-57	progenitor	-0.0029833335	-0.09470001	G1
-58	progenitor	-0.0021333336	-0.106824994	G1
-59	progenitor	-0.0015000002	-0.11555001	G1
-60	progenitor	-0.0022999998	-0.12255001	G1
-61	progenitor	-0.0017666668	-0.13125	G1
-62	progenitor	0.0033999998	-0.14297503	S
-63	progenitor	0.006316666	-0.15117502	S
-64	progenitor	0.005033333	-0.15187496	S
-65	progenitor	0.0031333338	-0.15367502	S
-66	progenitor	0.0035666667	-0.15197498	S
-67	progenitor	0.005016666	-0.14580002	S
-68	progenitor	0.0061	-0.142575	S
-69	progenitor	0.00515	-0.13665	S
-70	progenitor	0.0028499998	-0.12865001	S
-71	progenitor	0.0030833331	-0.12112501	S
-72	progenitor	0.0032833333	-0.11669999	S
-73	progenitor	0.0006166666	-0.11475003	S
-74	progenitor	-0.0006833335	-0.11412498	G1
-75	progenitor	-2.3283064e-10	-0.11702502	G1
-76	progenitor	0.0007333332	-0.121425	S
-77	progenitor	0.0005833333	-0.12972501	S
-78	progenitor	-0.0015333334	-0.13869998	G1
-79	progenitor	-0.0023	-0.14877501	G1
-80	Neu	-0.0046166666	-0.157125	G1
-81	Neu	-0.0035666665	-0.16639996	G1
-82	Neu	-0.0011666667	-0.17409998	G1
-83	Neu	-0.0026166667	-0.180325	G1
-84	Neu	-0.0001833333	-0.18502498	G1
-85	Neu	0.0035666665	-0.18762502	S
-86	Neu	0.0024333335	-0.19062501	S
-87	Neu	0.0023	-0.19277498	S
-88	Neu	0.0014833333	-0.19762498	S
-89	Neu	0.0024333335	-0.201725	S
-90	Neu	0.003866667	-0.20430002	S
-91	Neu	0.0067999996	-0.20865002	S
-92	Neu	0.0079333335	-0.21332502	S
-93	Neu	0.0068	-0.21907501	S
-94	Neu	0.0058	-0.22292498	S
-95	Neu	0.0069666663	-0.22795	S
-96	Neu	0.0023833334	-0.22915001	S
-97	Neu	0.0056166667	-0.230375	S
-98	Neu	0.0051666666	-0.23027502	S
-99	Neu	0.001966667	-0.23169999	S
-100	Neu	0.0033666668	-0.23169999	S
-101	Neu	0.0047333334	-0.233675	S
-102	Neu	0.0045666667	-0.23272496	S
-103	Neu	0.00060000026	-0.23024999	S
-104	Neu	0.0036833333	-0.22662503	S
-105	Neu	0.0025166667	-0.22107498	S
-106	Neu	0.0038833334	-0.22109997	S
-107	Neu	0.0033666666	-0.21907501	S
-108	Neu	0.0042666667	-0.218675	S
-109	Neu	0.0038	-0.2165	S
-110	Neu	0.004633333	-0.21385	S
-111	Neu	0.003266667	-0.21305001	S
-112	Neu	0.0034166668	-0.21077499	S
-113	Neu	0.0017166669	-0.21184999	S
-114	Neu	0.0012666667	-0.21437502	S
-115	Neu	-0.0016333334	-0.2153	G1
-116	Neu	-0.00043333336	-0.215675	G1
-117	Neu	0.0018833333	-0.21865001	S
-118	Neu	0.0014666667	-0.22187501	S
-119	Neu	-0.0020833332	-0.21787499	G1
-120	Neu	-0.0039000001	-0.21329997	G1
-121	Neu	-0.0023	-0.20820004	G1
-122	Neu	-0.00195	-0.21035	G1
-123	Neu	-0.0058833333	-0.20732501	G1
-124	Neu	-0.0070166667	-0.20714998	G1
-125	Neu	-0.008633333	-0.20389998	G1
-126	Neu	-0.006616667	-0.20832503	G1
-127	Neu	-0.003116667	-0.21047503	G1
-128	Neu	-0.0055833333	-0.21289998	G1
-129	Neu	-0.0042333333	-0.216575	G1
-130	Neu	-0.005016667	-0.21945003	G1
-131	Neu	-0.0020833334	-0.21799998	G1
-132	Neu	-0.0032	-0.21150002	G1
-133	Neu	-0.0033333339	-0.20989999	G1
-134	Neu	-0.0011666667	-0.21257499	G1
-135	Neu	-0.0023	-0.21222499	G1
-136	Neu	-0.0034666667	-0.2146	G1
-137	Neu	-0.0011833335	-0.21350002	G1
-138	Neu	-0.00325	-0.21377501	G1
-139	Neu	-0.0040166667	-0.213925	G1
-140	Neu	-0.0024666665	-0.21455	G1
-141	Neu	0.0028333336	-0.21975	S
-142	Neu	0.0032833333	-0.220325	S
-143	Neu	0.004766667	-0.22119999	S
-144	Neu	0.00705	-0.22362499	S
-145	Neu	0.0036	-0.22555003	S
-146	Neu	0.006733333	-0.22377498	S
-147	Neu	0.0025000002	-0.22509998	S
-148	Neu	0.0018	-0.221075	S
-149	Neu	6.666663e-05	-0.22125	S
-150	Neu	-0.0014499999	-0.219875	G1
-151	Neu	-0.0012833332	-0.21900001	G1
-152	Neu	-0.0001999999	-0.21767499	G1
-153	Neu	-0.0032666668	-0.21407498	G1
-154	Neu	-0.0017	-0.2116	G1
-155	Neu	-0.0028166666	-0.2077	G1
-156	Neu	-0.00245	-0.2053	G1
-157	Neu	-0.0011166666	-0.203825	G1
-158	Neu	-0.001966667	-0.20535001	G1
-159	Neu	-0.0027	-0.20725003	G1
diff -r 9ca360dde8e3 -r a89ee42625ad test-data/tl.tsne.krumsiek11.h5ad
Binary file test-data/tl.tsne.krumsiek11.h5ad has changed
diff -r 9ca360dde8e3 -r a89ee42625ad test-data/tl.umap.neighbors_umap_euclidean.recipe_weinreb17.paul15_subsample.h5ad
Binary file test-data/tl.umap.neighbors_umap_euclidean.recipe_weinreb17.paul15_subsample.h5ad has changed