Mercurial > repos > iuc > scanpy_remove_confounders
changeset 17:b70219da4a96 draft
planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/scanpy/ commit 91121b1e72696f17478dae383badaa71e9f96dbb
line wrap: on
line diff
--- a/README.md Tue Aug 20 09:51:42 2024 +0000 +++ b/README.md Sat Sep 14 12:43:38 2024 +0000 @@ -25,6 +25,7 @@ `pp.highly_variable_genes` | Extract highly variable genes `pp.subsample` | Subsample to a fraction of the number of observations `pp.downsample_counts` | Downsample counts so that each cell has no more than target_counts + `pp.scrublet` | Predict doublets 3. Normalize (`normalize.xml`) @@ -34,14 +35,18 @@ `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] + `external.pp.magic` | Denoising using Markov Affinity-based Graph Imputation of Cells (MAGIC) API 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.mnn_correct` | Correct batch effects by matching mutual nearest neighbors --> `pp.combat` | ComBat function for batch effect correction + `external.pp.bbknn` | Batch effect removal with Batch balanced KNN (BBKNN) + `external.pp.harmony_integrate` | Integrate multiple single-cell experiments with Harmony + `external.pp.scanorama_integrate` | Integrate multiple single-cell experiments with Scanorama 5. Clustering, embedding and trajectory inference (`cluster_reduce_dimension.xml`) @@ -49,14 +54,14 @@ --- | --- `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...) + `pp.pca` | Principal component analysis `tl.diffmap` | Diffusion Maps `tl.tsne` | t-SNE `tl.umap` | Embed the neighborhood graph using UMAP `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 + `tl.embedding_density` | Calculate the density of cells in an embedding (per condition) 6. Plot (`plot.xml`) @@ -66,18 +71,20 @@ --- | --- `pl.scatter` | Scatter plot along observations or variables axes `pl.heatmap` | Heatmap of the expression values of set of genes + `pl.tracksplot` | Tracks plot of the expression values per cell `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 - + 2. Preprocessing 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 + `pl.scrublet_score_distribution` | Histogram of doublet scores 3. PCA @@ -96,12 +103,13 @@ `pl.umap` | Scatter plot in UMAP basis `pl.diffmap` | Scatter plot in Diffusion Map basis `pl.draw_graph` | Scatter plot in graph-drawing basis + `pl.embedding_density` | Density of cells in an embedding (per condition) 5. Branching trajectories and pseudotime, clustering Methods | Description --- | --- - `pl.dpt_groups_pseudotime` | Plot groups and pseudotime + <!-- `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 @@ -113,3 +121,8 @@ --- | --- `pl.rank_genes_groups` | Plot ranking of genes using dotplot plot `pl.rank_genes_groups_violin` | Plot ranking of genes for all tested comparisons + `pl.rank_genes_groups_stacked_violin` | Plot ranking of genes as stacked violin plot + `pl.rank_genes_groups_heatmap` | Plot ranking of genes as heatmap plot + `pl.rank_genes_groups_dotplot` | Plot ranking of genes as dotplot plot + `pl.rank_genes_groups_matrixplot` | Plot ranking of genes as matrixplot plot + `pl.rank_genes_groups_tracksplot` | Plot ranking of genes as tracksplot plot
--- a/macros.xml Tue Aug 20 09:51:42 2024 +0000 +++ b/macros.xml Sat Sep 14 12:43:38 2024 +0000 @@ -1,17 +1,15 @@ <macros> - <token name="@TOOL_VERSION@">1.9.6</token> - <token name="@VERSION_SUFFIX@">4</token> - <token name="@profile@">21.09</token> + <token name="@TOOL_VERSION@">1.10.2</token> + <token name="@VERSION_SUFFIX@">0</token> + <token name="@PROFILE@">21.09</token> <xml name="requirements"> <requirements> <requirement type="package" version="@TOOL_VERSION@">scanpy</requirement> - <requirement type="package" version="3.0.6">loompy</requirement> - <requirement type="package" version="0.10.1">leidenalg</requirement> - <requirement type="package" version="0.8.1">louvain</requirement> - <requirement type="package" version="1.5.3">pandas</requirement> - <requirement type="package" version="3.7">matplotlib</requirement> - <requirement type="package" version="0.12.2">seaborn</requirement> - <requirement type="package" version="3.0.0">magic-impute</requirement> + <requirement type="package" version="0.10.3">anndata</requirement> + <requirement type="package" version="1.26.4">numpy</requirement> + <requirement type="package" version="2.2.2">pandas</requirement> + <requirement type="package" version="1.14.1">scipy</requirement> + <requirement type="package" version="0.14.2">statsmodels</requirement> <yield /> </requirements> </xml> @@ -22,7 +20,7 @@ </xml> <xml name="creators"> <creator> - <organization name="European Galaxy Team" url="https://galaxyproject.org/eu/" /> + <organization name="European Galaxy Team" url="https://galaxyproject.org/eu/"/> </creator> </xml> <xml name="citations"> @@ -31,28 +29,13 @@ <citation type="doi">10.1093/gigascience/giaa102</citation> </citations> </xml> - <xml name="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' > '$hidden_output' && -python '$script_file' >> '$hidden_output' && -ls . >> '$hidden_output' && -touch 'anndata_info.txt' && -cat 'anndata_info.txt' @CMD_prettify_stdout@ - ]]> - </token> - <token name="@CMD_imports@"><![CDATA[ -import scanpy as sc -import pandas as pd -import numpy as np - ]]> - </token> + + + <!-- param macros --> <xml name="sanitize_query" token_validinitial="string.printable"> <sanitizer> <valid initial="@VALIDINITIAL@"> - <remove value="'" /> + <remove value="'"/> </valid> </sanitizer> </xml> @@ -62,58 +45,55 @@ <add value=","/> </valid> </sanitizer> - </xml> + </xml> <xml name="inputs_anndata"> <param name="adata" type="data" format="h5ad" label="Annotated data matrix"/> </xml> - <token name="@CMD_read_inputs@"><![CDATA[ -adata = sc.read_h5ad('anndata.h5ad') -]]> - </token> <xml name="inputs_common_advanced"> <section name="advanced_common" title="Advanced Options" expanded="false"> - <param name="show_log" type="boolean" checked="false" label="Output Log?" /> + <param name="show_log" type="boolean" checked="false" label="Output Log?"/> </section> </xml> <xml name="anndata_outputs"> - <data name="anndata_out" format="h5ad" from_work_dir="anndata.h5ad" label="${tool.name} (${method.method}) on ${on_string}: Annotated data matrix"/> - <data name="hidden_output" format="txt" label="Log file" > + <data name="anndata_out" format="h5ad" from_work_dir="anndata.h5ad" label="${tool.name} (${method.method}) on ${on_string}: Annotated data matrix"> + <yield /> + </data> + <data name="hidden_output" format="txt" label="Log file" > <filter>advanced_common['show_log']</filter> </data> + </xml> + <xml name="param_use_rep"> + <param argument="use_rep" type="text" value="" optional="true" label="Use the indicated representation" help="If not set, the representation is chosen automatically: for n_vars below 50, X is used, otherwise X_pca (uns) is used. If X_pca is not present, it's computed with default parameter"> + <expand macro="sanitize_query"/> + </param> </xml> - <token name="@CMD_anndata_write_outputs@"><![CDATA[ -adata.write_h5ad('anndata.h5ad') -with open('anndata_info.txt','w', encoding='utf-8') as ainfo: - print(adata, file=ainfo) -]]> - </token> - <token name="@CMD_prettify_stdout@"><![CDATA[ | sed -r '1 s|AnnData object with (.+) = (.*)\s*|\1: \2|g' | sed "s|'||g" | sed -r 's|^\s*(.*):\s(.*)|[\1]\n- \2|g' | sed 's|, |\n- |g' - ]]></token> <xml name="svd_solver"> - <param name="svd_solver" type="select" label="SVD solver to use" help=""> + <param name="svd_solver" type="select" optional="true" label="SVD solver to use"> <option value="auto">Automatically chosen depending on the size of the problem</option> <option value="arpack">ARPACK wrapper in SciPy</option> <option value="randomized">Randomized algorithm due to Halko (2009)</option> + <option value="lobpcg">An alternative SciPy solver. Not available with dask arrays.</option> + <option value="tsqr">Only available with dask arrays. “tsqr” algorithm from Benson et. al. (2013).</option> </param> </xml> <xml name="pca_random_state"> - <param name="random_state" type="integer" value="0" label="Initial states for the optimization" help=""/> + <param name="random_state" type="integer" value="0" label="Initial states for the optimization"/> </xml> <xml name="param_plot_format"> <param name="format" type="select" label="Format for saving figures"> - <option value="png">png</option> + <option value="png" selected="true">png</option> <option value="pdf">pdf</option> <option value="svg">svg</option> </param> </xml> <xml name="numeric_distance_metric_options"> + <option value="euclidean" selected="true">euclidean</option> <option value="braycurtis">braycurtis</option> <option value="canberra">canberra</option> <option value="chebyshev">chebyshev</option> <option value="cityblock">cityblock</option> <option value="correlation">correlation</option> <option value="cosine">cosine</option> - <option value="euclidean" selected="true">euclidean</option> <option value="mahalanobis">mahalanobis</option> <option value="matching">matching</option> <option value="minkowski">minkowski</option> @@ -393,141 +373,6 @@ <option value="nipy_spectral">nipy_spectral (Miscellaneous)</option> <option value="gist_ncar">gist_ncar (Miscellaneous)</option> </xml> - <xml name="param_groupby"> - <param argument="groupby" type="text" value="" optional="true" label="The key of the observation grouping to consider" help="If it is given, the plot is ordered by the respective group. It is expected that to be a categorical. If it is not a categorical observation, it would be subdivided into 'num_categories'."> - <expand macro="sanitize_query" /> - </param> - </xml> - <xml name="param_use_raw"> - <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?"/> - </xml> - <xml name="pl_figsize"> - <conditional name="figsize"> - <param name="test" type="select" label="Custom figure size" > - <option value="yes">Yes</option> - <option value="no" selected="true">No: the figure width is set based on the number of variable names and the height is set to 10.</option> - </param> - <when value="yes"> - <param argument="width" type="integer" min="0" value="10" label="Figure width" help=""/> - <param argument="height" type="integer" min="0" value="10" label="Figure height" help=""/> - </when> - <when value="no"/> - </conditional> - </xml> - <token name="@CMD_params_figsize@"><![CDATA[ - - ]]></token> - <xml name="pl_var_names"> - <conditional name="var_names"> - <param name="type" type="select" label="Variables to plot (columns of the heatmaps)" > - <option value="all">All variables in 'adata.var_names'</option> - <option value="custom">Subset of variables in 'adata.var_names'</option> - <option value="customfile">Subset of variables as a tabular file</option> - </param> - <when value="all"/> - <when value="custom"> - <param argument="var_names" type="text" value="" label="List of variables to plot" help="They should be a valid subset of 'adata.var_names', and separated by comma"> - <expand macro="sanitize_query" /> - </param> - </when> - <when value="customfile"> - <param argument="var_names" type="data" format="tabular" label="List of variables to plot" help="This should be a tsv where row = group (e.g. celltypes) and columns = variables."></param> - <param name="header" type="select" label="Header in the list of markers?"> - <option value="included">Header incldued</option> - <option value="not_included">Header not included</option> - </param> - </when> - </conditional> - </xml> - <xml name="param_num_categories"> - <param argument="num_categories" type="integer" min="0" value="7" label="Number of categories" help="It is only used if groupby observation is not categorical. This value determines the number of groups into which the groupby observation should be subdivided."/> - </xml> - <xml name="param_dendrogram"> - <param argument="dendrogram" type="boolean" truevalue="True" falsevalue="False" checked="false" label="Compute and plot a dendrogram?" help="groupby categories are reordered accoring to the dendrogram order. If groups of var_names are set and those groups correspond to the groupby categories, those groups are also reordered. The ‘person’ method is used to compute the pairwise correlation between categories using all var_names in raw if use_raw is None, otherwise all adata.var_names are used. The linkage method used is complete."/> - </xml> - <xml name="pl_var_group_positions"> - <repeat name="var_group_positions" title="Group of variables to highlight" help="This will draw a 'bracket' on top of the plot between the given start and end positions. If a label is given, it will be added on top of the bracket. "> - <param name="start" type="integer" min="0" value="" label="Start" help=""/> - <param name="end" type="integer" min="0" value="" label="End" help=""/> - <param argument="label" type="text" value="" label="Label" help=""> - <expand macro="sanitize_query" /> - </param> - </repeat> - </xml> - <xml name="param_var_group_rotation"> - <param argument="var_group_rotation" type="float" value="" optional="true" label="Label rotation degrees" help="By default, labels larger than 4 characters are rotated 90 degrees"/> - </xml> - <xml name="param_layer"> - <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'."> - <expand macro="sanitize_query" /> - </param> - </xml> - <token name="@CMD_param_plot_inputs@"><![CDATA[ - adata, - save='.$format', - show=False, - ]]></token> - <xml name="params_inputs"> - <expand macro="pl_var_names"/> - <expand macro="param_groupby"/> - <expand macro="param_num_categories"/> - </xml> - <token name="@CMD_var_names_header_check@"><![CDATA[ -header='infer' -#if $method.var_names.type == 'customfile' and $method.var_names.header == 'not_included' : -header=None -#end if - ]]></token> - <token name="@CMD_params_inputs@"><![CDATA[ - #if $method.var_names.type == 'custom' - #set $var_names = ([x.strip() for x in str($method.var_names.var_names).split(',')]) - var_names=$var_names, - #else if $method.var_names.type == 'customfile' - var_names={key: [v for v in list(value.values()) if pd.notna(v)] for key, value in pd.read_csv('$var_names', sep='\t', index_col=0).to_dict(orient='index').items()}, - #else - var_names=adata.var_names, - #end if - #if $method.groupby - groupby='$method.groupby', - #end if - num_categories=$method.num_categories, - ]]></token> - <xml name="params_plots"> - <expand macro="param_log"/> - <expand macro="param_use_raw"/> - <expand macro="param_dendrogram"/> - <expand macro="pl_var_group_positions"/> - <expand macro="param_var_group_rotation"/> - <expand macro="pl_figsize"/> - <expand macro="param_layer"/> - </xml> - <token name="@CMD_params_plots@"><![CDATA[ - log=$method.log, - use_raw=$method.use_raw, - dendrogram=$method.dendrogram, - #if len($method.var_group_positions) > 0: - #set $var_group_positions=[] - #set $var_group_labels=[] - #for $i, $s in enumerate($method.var_group_positions) - #silent $var_group_positions.append((int($s.start), int($s.end))) - #silent $var_group_labels.append(str($s.label)) - #end for - var_group_positions=$var_group_positions, - var_group_labels=$var_group_labels, - #end if - #if str($method.var_group_rotation) != '' - var_group_rotation=$method.var_group_rotation, - #end if - #if $method.figsize.test == 'yes' - figsize=($method.figsize.width, $method.figsize.height), - #end if - #if $method.layer - layer='$method.layer', - #end if - ]]></token> <xml name="matplotlib_color"> <option value="AliceBlue">AliceBlue</option> <option value="AntiqueWhite">AntiqueWhite</option> @@ -679,500 +524,298 @@ <option value="YellowGreen">YellowGreen</option> </xml> <xml name="param_matplotlib_pyplot_edgecolors"> - <param argument="edgecolors" type="select" optional="true" label="Edge color of the marker" help=""> + <param argument="edgecolors" type="select" optional="true" label="Edge color of the marker"> <option value="face">The edge color will always be the same as the face color</option> <expand macro="matplotlib_color"/> </param> </xml> - <xml name="param_alpha"> - <param argument="alpha" type="float" value="" min="0" max="1" optional="true" label="Alpha blending value" help="Between 0 (transparent) and 1 (opaque)"/> - </xml> - <xml name="param_vmin"> - <param argument="vmin" type="float" value="" optional="true" label="Minimum value to normalize luminance data" help="If not set, it is inferred from the data and other keyword arguments"/> - </xml> - <xml name="param_vmax"> - <param argument="vmax" type="float" value="" optional="true" label="Maximum value to normalize luminance data" help="If not set, it is inferred from the data and other keyword arguments"/> - </xml> - <xml name="section_matplotlib_pyplot_scatter"> - <section name="matplotlib_pyplot_scatter" title="Parameters for matplotlib.pyplot.scatter"> - <!--<param argument="marker" type="select" label="Marker style" help=""> - <option value="o">o</option> - <option value="v">v</option> - <option value="^">^</option> - <option value="8">8</option> - <option value="s">s</option> - <option value="p">p</option> - <option value="*">*</option> - <option value="h">h</option> - <option value="H">H</option> - <option value="D">D</option> - <option value="d">d</option> - <option value="P">P</option> - <option value="X">X</option> - </param>--> - <expand macro="param_alpha"/> - <expand macro="param_vmin"/> - <expand macro="param_vmax"/> - <param argument="linewidths" type="float" value="0" label="Linewidth of the marker edges" help=""/> - <expand macro="param_matplotlib_pyplot_edgecolors"/> - </section> + <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> - <token name="@CMD_params_matplotlib_pyplot_scatter@"><![CDATA[ - #if str($method.matplotlib_pyplot_scatter.vmin) != '' - vmin=$method.matplotlib_pyplot_scatter.vmin, - #end if - #if str($method.matplotlib_pyplot_scatter.vmax) != '' - vmax=$method.matplotlib_pyplot_scatter.vmax, - #end if - #if str($method.matplotlib_pyplot_scatter.alpha) != '' - alpha=$method.matplotlib_pyplot_scatter.alpha, - #end if - lw=$method.matplotlib_pyplot_scatter.linewidths, - #if $method.matplotlib_pyplot_scatter.edgecolors - ec='$method.matplotlib_pyplot_scatter.edgecolors' - #end if - ]]></token> - <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> - <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="float" 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> + <xml name="param_cmap"> + <param argument="cmap" type="select" optional="true" label="Colors to use for plotting categorical annotation groups"> + <expand macro="matplotlib_pyplot_colormap"/> </param> </xml> - <token name="@CMD_params_violin_plots@"><![CDATA[ - @CMD_conditional_stripplot@ + <xml name="param_sort_order"> + <param argument="sort_order" type="boolean" truevalue="True" falsevalue="False" checked="true" label="Sort order?" help="For continuous annotations used as color parameter, plot data points with higher values on top of others."/> + </xml> + <xml name="param_arrows"> + <param argument="arrows" type="boolean" truevalue="True" falsevalue="False" checked="false" label="Show arrows?" help="It requires to run 'tl.rna_velocity' before."/> + </xml> + <!-- param macros --> + + + + <!-- command macros --> + <xml name="version_command"> + <version_command><![CDATA[python -c "import scanpy as sc;print('scanpy version: %s' % sc.__version__)"]]></version_command> + </xml> + <token name="@CMD_PRETTIFY_STDOUT@"><![CDATA[ +| sed -r '1 s|AnnData object with (.+) = (.*)\s*|\1: \2|g' | sed "s|'||g" | sed -r 's|^\s*(.*):\s(.*)|[\1]\n- \2|g' | sed 's|, |\n- |g' + ]]> + </token> + <token name="@CMD_READ_INPUTS@"><![CDATA[ +adata = sc.read_h5ad('anndata.h5ad') + ]]> + </token> + <!-- ln -s doesn't work here because the output is overwritten to the same file --> + <token name="@CMD@"><![CDATA[ +cp '$adata' 'anndata.h5ad' && +cat '$script_file' > '$hidden_output' && +python '$script_file' >> '$hidden_output' && +ls . >> '$hidden_output' && +touch 'anndata_info.txt' && +cat 'anndata_info.txt' @CMD_PRETTIFY_STDOUT@ + ]]> + </token> + <token name="@CMD_IMPORTS@"><![CDATA[ +import scanpy as sc +import pandas as pd +import numpy as np + ]]> + </token> + <token name="@CMD_ANNDATA_WRITE_OUTPUTS@"><![CDATA[ +adata.write_h5ad('anndata.h5ad', compression='gzip') +with open('anndata_info.txt','w', encoding='utf-8') as ainfo: + print(adata, file=ainfo) + ]]> + </token> + <token name="@CMD_PARAM_PLOT_INPUTS@"><![CDATA[ + adata, + save='.$format', + ]]> + </token> + <token name="@CMD_SHOW_NONE@"><![CDATA[ + show=None + ]]> + </token> + <token name="@CMD_VAR_NAMES_HEADER_CHECK@"><![CDATA[ +header='infer' +#if $method.var_names.type == 'customfile' and $method.var_names.header == 'not_included' : +header=None +#end if + ]]> + </token> + <token name="@CMD_PARAMS_VIOLIN_PLOTS@"><![CDATA[ + @CMD_CONDITIONAL_STRIPPLOT@ multi_panel=$method.violin_plot.multi_panel.multi_panel, #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', - ]]></token> - <xml name="seaborn_violinplot"> - <section name="seaborn_violinplot" title="Parameters for seaborn.violinplot"> - <param argument="bw" type="select" label="Name of a reference rule when computing the kernel bandwidth"> - <option value="scott">scott</option> - <option value="silverman">silverman</option> - </param> - <param argument="orient" type="select" optional="true" label="Orientation of the plot"> - <option value="v">vertical</option> - <option value="h">horizontal</option> - </param> - <param argument="linewidth" type="float" value="0" label="Width of the gray lines that frame the plot elements" help=""/> - <param argument="color" type="select" optional="true" label="Color for all of the elements" help=""> - <expand macro="matplotlib_color"/> - </param> - <param argument="saturation" type="float" value="0.75" min="0" max="1" label="Proportion of the original saturation to draw colors at" help=""/> - </section> - </xml> - <token name="@CMD_params_seaborn_violinplot@"><![CDATA[ - bw='$method.seaborn_violinplot.bw', -#if $method.seaborn_violinplot.orient - orient='$method.seaborn_violinplot.orient', -#end if - linewidth=$method.seaborn_violinplot.linewidth, - #if $method.seaborn_violinplot.color - color='$method.seaborn_violinplot.color', - #end if - 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'"> - <expand macro="sanitize_query" /> - </param> - </xml> - <token name="@CMD_param_color@"><![CDATA[ -#if $method.color - #set $color = ([x.strip() for x in str($method.color).split(',')]) - color=$color, -#end if - ]]></token> - <xml name="param_groups"> - <param argument="groups" type="text" value="" optional="true" label="Categorical observation annotations to plot" help="Comma-separated"> - <expand macro="sanitize_query" /> + density_norm='$method.violin_plot.density_norm', + ]]> + </token> + <!-- command macros --> + + + + <!-- param and cmd macros --> + <xml name="param_standard_scale"> + <param argument="standard_scale" type="select" label="Standardize a dimension between 0 and 1" help="Each variable or observation is subtracted by the minimum and divided each by its maximum."> + <option value="None" selected="true">No standardization</option> + <option value="var">Standardization on variable</option> + <option value="obs">Standardization on observation</option> </param> </xml> - <token name="@CMD_params_groups@"><![CDATA[ -#if $method.groups - #set $groups=([x.strip() for x in str($method.groups).split(',')]) - groups=$groups, -#end if - ]]></token> - <xml name="pl_components"> - <repeat name="components" title="Component"> - <param argument="axis1" type="text" value="1" label="X-Axis" help=""> - <expand macro="sanitize_query" /> - </param> - <param argument="axis2" type="text" value="2" label="Y-Axis" help=""> - <expand macro="sanitize_query" /> - </param> - </repeat> - </xml> - <token name="@CMD_params_pl_components@"><![CDATA[ -#if len($method.plot.components) > 0 - #set $components=[] - #for $i, $s in enumerate($method.plot.components) - #silent $components.append(str($s.axis1) + ',' + str($s.axis2)) - #end for - components=$components, -#end if - ]]> - </token> - <xml name="param_projection"> - <param argument="projection" type="select" label="Projection of plot" help=""> - <option value="2d">2d</option> - <option value="3d">3d</option> - </param> - </xml> - <xml name="param_legend_loc"> - <param argument="legend_loc" type="select" label="Location of legend" help=""> - <option value="none">none</option> - <option value="right margin" selected="true">right margin</option> - <option value="on data">on data</option> - <option value="on data export">on data export</option> - <option value="best">best</option> - <option value="upper right">upper right</option> - <option value="upper left">upper left</option> - <option value="lower left">lower left</option> - <option value="lower right">lower right</option> - <option value="center left">center left</option> - <option value="center right">center right</option> - <option value="lower center">lower center</option> - <option value="upper center">upper center</option> - <option value="center">center</option> - </param> - </xml> - <xml name="param_legend_fontsize"> - <param argument="legend_fontsize" type="integer" optional="true" value="" label="Legend font size" help=""/> - </xml> - <token name="@CMD_param_legend_fontsize@"><![CDATA[ - #if str($method.plot.legend_fontsize) != '' - legend_fontsize=$method.plot.legend_fontsize, + <token name="@CMD_STANDARD_SCALE@"><![CDATA[ + #if str($method.standard_scale) != 'None': + standard_scale='$method.standard_scale', #end if ]]> </token> - <xml name="param_legend_fontweight"> - <param argument="legend_fontweight" type="select" label="Legend font weight" help=""> - <option value="light">light</option> - <option value="normal" selected="true">normal</option> - <option value="medium">medium</option> - <option value="semibold">semibold</option> - <option value="bold">bold</option> - <option value="heavy">heavy</option> - <option value="black">black</option> - </param> - </xml> - <xml name="param_palette"> - <param argument="palette" type="select" optional="true" label="Colors to use for plotting categorical annotation groups" help=""> - <expand macro="matplotlib_pyplot_colormap"/> + + <xml name="param_layer" token_optional="true" token_label="If provided, use adata.layers[layer] for expression values instead of adata.X." token_help=""> + <param argument="layer" type="text" value="" optional="@OPTIONAL@" label="@LABEL@"> + <expand macro="sanitize_query"/> </param> </xml> - <xml name="param_color_map"> - <param argument="color_map" type="select" optional="true" label="Color map to use for continous variables" help=""> - <expand macro="matplotlib_pyplot_colormap"/> - </param> - </xml> - <xml name="param_frameon"> - <param argument="frameon" type="boolean" truevalue="True" falsevalue="False" checked="true" label="Draw a frame around the scatter plot?" help=""/> - </xml> - <xml name="param_right_margin"> - <param argument="right_margin" type="float" value="1" label="Width of the space right of each plotting panel" help=""/> - </xml> - <xml name="param_left_margin"> - <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" optional="true" value="" label="Point size" help=""/> - </xml> - <token name="@CMD_param_size@"><![CDATA[ - #if str($method.plot.size) != '' - size=$method.plot.size, + <token name="@CMD_PARAM_LAYER@"><![CDATA[ + #if str($method.layer) != '': + layer='$method.layer', #end if ]]> </token> - <xml name="param_title"> - <param argument="title" type="text" value="" optional="true" label="Title for panels" help="Titles must be separated by a comma"> - <expand macro="sanitize_query" /> + + <xml name="param_neighbors_key"> + <param argument="neighbors_key" type="text" value="" label="Key to look for neighbors settings and connectivities" help="If not specified, looks .uns[‘neighbors’] for neighbors settings and .obsp[‘connectivities’] for connectivities (default storage places for pp.neighbors)."> + <expand macro="sanitize_query"/> </param> </xml> - <token name="@CMD_param_title@"><![CDATA[ - #if $method.plot.title - title='$method.plot.title', + <token name="@CMD_PARAM_NEIGHBORS_KEY@"><![CDATA[ + #if $method.neighbors_key != '' + neighbors_key='$method.neighbors_key', #end if ]]> </token> - <xml name="param_sort_order"> - <param argument="sort_order" type="boolean" truevalue="True" falsevalue="False" checked="true" label="Sort order?" help="For continuous annotations used as color parameter, plot data points with higher values on top of others."/> - </xml> - <xml name="param_sort_order"> - <param argument="sort_order" type="boolean" truevalue="True" falsevalue="False" checked="true" label="Sort order?" help="For continuous annotations used as color parameter, plot data points with higher values on top of others."/> - </xml> - <xml name="param_ncols"> - <param argument="ncols" type="integer" min="0" value="4" label="Number of panels per row" help=""/> - </xml> - <xml name="param_wspace"> - <param argument="wspace" type="float" min="0" value="0.1" label="Width of the space between multiple panels" help=""/> - </xml> - <xml name="param_hspace"> - <param argument="hspace" type="float" min="0" value="0.25" label="Height of the space between multiple panels" help=""/> - </xml> - <xml name="pl_edges"> - <conditional name="edges"> - <param argument="edges" type="select" label="Show edges?"> - <option value="True">Yes</option> - <option value="False" selected="true">No</option> + + <xml name="pl_var_names"> + <conditional name="var_names"> + <param name="type" type="select" label="Variables to plot (columns of the heatmaps)" > + <option value="all" selected="true">All variables in 'adata.var_names'</option> + <option value="custom">Subset of variables in 'adata.var_names'</option> + <option value="customfile">Subset of variables as a tabular file</option> </param> - <when value="True"> - <param argument="edges_width" type="float" min="0" value="0.1" label="Width of edges"/> - <param argument="edges_color" type="select" optional="true" label="Color of edges"> - <expand macro="matplotlib_color"/> + <when value="all"/> + <when value="custom"> + <param argument="var_names" type="text" value="" label="List of variables to plot" help="They should be a valid subset of 'adata.var_names', and separated by comma"> + <expand macro="sanitize_query"/> </param> </when> - <when value="False"/> + <when value="customfile"> + <param argument="var_names" type="data" format="tabular" label="List of variables to plot" help="This should be a tsv where row = group (e.g. celltypes) and columns = variables."></param> + <param name="header" type="boolean" truevalue="included" falsevalue="not_included" checked="true" label="Header is included in the list of markers?"/> + </when> </conditional> </xml> - <token name="@CMD_pl_edges@"><![CDATA[ -#if str($method.edges.edges) == 'True' - edges=True, - edges_width=$method.edges.edges_width, - #if $method.edges.edges_color - edges_color='$method.edges.edges_color', - #end if -#else - edges=False, -#end if - ]]> - </token> - <xml name="param_arrows"> - <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" optional="true" label="Colors to use for plotting categorical annotation groups" help=""> - <expand macro="matplotlib_pyplot_colormap"/> - </param> - </xml> - <xml name="pl_attribute_section"> - <section name="plot" title="Plot attributes"> - <expand macro="pl_components"/> - <expand macro="param_projection"/> - <expand macro="param_legend_loc"/> - <expand macro="param_legend_fontsize"/> - <expand macro="param_legend_fontweight"/> - <expand macro="param_size"/> - <expand macro="param_color_map"/> - <expand macro="param_palette"/> - <expand macro="param_frameon"/> - <expand macro="param_ncols"/> - <expand macro="param_wspace"/> - <expand macro="param_hspace"/> - <expand macro="param_title"/> - </section> - </xml> - <token name="@CMD_pl_attribute_section@"><![CDATA[ - projection='$method.plot.projection', - legend_loc='$method.plot.legend_loc', - @CMD_param_legend_fontsize@ - legend_fontweight='$method.plot.legend_fontweight', - @CMD_param_size@ - #if $method.plot.color_map - color_map='$method.plot.color_map', - #end if - #if $method.plot.palette - palette='$method.plot.palette', - #end if - frameon=$method.plot.frameon, - ncols=$method.plot.ncols, - wspace=$method.plot.wspace, - hspace=$method.plot.hspace, - @CMD_param_title@ - ]]> - </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" optional="false" 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."> - <expand macro="sanitize_query" /> + <xml name="param_groupby"> + <param argument="groupby" type="text" value="" optional="true" label="The key of the observation grouping to consider" help="If it is given, the plot is ordered by the respective group. It is expected that to be a categorical. If it is not a categorical observation, it would be subdivided into 'num_categories'."> + <expand macro="sanitize_query"/> </param> </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 name="param_num_categories"> + <param argument="num_categories" type="integer" min="0" value="7" label="Number of categories" help="It is only used if groupby observation is not categorical. This value determines the number of groups into which the groupby observation should be subdivided."/> </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="param_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'."> - <expand macro="sanitize_query" /> - </param> - <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."> - <expand macro="sanitize_query" /> - </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=""/> - <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'"> - <expand macro="sanitize_query" /> - </param> - <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"> - <expand macro="sanitize_query" /> - </param> - <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."> - <expand macro="sanitize_query" /> - </param> - <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=""/> - <param argument="node_size_power" type="float" min="0" value="0.5" label="Power with which groups sizes influence the radius of the nodes" help=""/> - <param argument="edge_width_scale" type="float" min="0" value="5" label="Scale for edge width" help=""/> - <param argument="min_edge_width" type="float" min="0" value="" optional="true" label="Min width of solid edges" help=""/> - <param argument="max_edge_width" type="float" min="0" value="" optional="true" label="Max width of solid and dashed edges" help=""/> - <param argument="arrowsize" type="integer" min="0" value="30" label="Arrow size" help="For directed graphs, choose the size of the arrow head head's length and width."/> - <param argument="normalize_to_color" type="boolean" truevalue="True" falsevalue="False" checked="false" label="Normalize categorical plots to color or the underlying grouping?" help=""/> - <expand macro="param_cmap"/> - <expand macro="param_title"/> - <expand macro="param_frameon"/> + + <xml name="params_inputs"> + <expand macro="pl_var_names"/> + <expand macro="param_groupby"/> + <expand macro="param_num_categories"/> </xml> - <token name="@CMD_params_pl_paga@"><![CDATA[ - threshold=$method.threshold, -#if $method.groups - #set $groups=([x.strip() for x in str($method.groups).split(',')]) - groups=$groups, -#end if -#if $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 -#if $method.labels - #set $labels=([x.strip() for x in str($method.labels).split(',')]) - labels=$labels, -#end if - layout='$method.layout', -#if $method.init_pos - init_pos=np.fromfile($method.init_pos, dtype=dt), -#end if - random_state=$method.random_state, -#if $method.root - #set $root=([int(x.strip()) for x in str($method.root).split(',')]) - root=$root, -#end if -#if $method.transitions - transitions='$method.transitions', -#end if - solid_edges='$method.solid_edges', -#if $method.dashed_edges - dashed_edges='$method.dashed_edges', -#end if - single_component=$method.single_component, - fontsize=$method.fontsize, - node_size_scale=$method.node_size_scale, - node_size_power=$method.node_size_power, - edge_width_scale=$method.edge_width_scale, -#if str($method.min_edge_width) != '' - min_edge_width=$method.min_edge_width, -#end if -#if str($method.max_edge_width) != '' - max_edge_width=$method.max_edge_width, -#end if - arrowsize=$method.arrowsize, - normalize_to_color=$method.normalize_to_color, - #if $method.cmap - cmap='$method.cmap', + <token name="@CMD_PARAMS_INPUTS@"><![CDATA[ + #if str($method.var_names.type) == 'custom': + #set $var_names = ([x.strip() for x in str($method.var_names.var_names).split(',')]) + var_names=$var_names, + #else if str($method.var_names.type) == 'customfile': + var_names={key: [v for v in list(value.values()) if pd.notna(v)] for key, value in pd.read_csv('$var_names', sep='\t', index_col=0, header=header).to_dict(orient='index').items()}, + #else + var_names=adata.var_names, + #end if + #if str($method.groupby) != '': + groupby='$method.groupby', #end if -#if $method.title - title='$method.title', -#end if - frameon=$method.frameon, + num_categories=$method.num_categories, + ]]> + </token> + + <xml name="pl_figsize"> + <conditional name="figsize"> + <param name="custom" type="select" label="Custom figure size" > + <option value="no" selected="true">No: the figure width is set based on the number of variable names and the height is set to 10.</option> + <option value="yes">Yes</option> + </param> + <when value="yes"> + <param argument="width" type="integer" min="0" value="10" label="Figure width"/> + <param argument="height" type="integer" min="0" value="10" label="Figure height"/> + </when> + <when value="no"/> + </conditional> + </xml> + <token name="@CMD_PARAMS_FIGSIZE@"><![CDATA[ + #if $method.figsize.custom == 'yes': + figsize=($method.figsize.width, $method.figsize.height), + #end if ]]> </token> - <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 name="param_log" token_checked="false"> + <param argument="log" type="boolean" truevalue="True" falsevalue="False" checked="@CHECKED@" label="Use the log of the values?"/> + </xml> + <xml name="param_use_raw" token_falsevalue="False"> + <param argument="use_raw" type="boolean" truevalue="True" falsevalue="@FALSEVALUE@" checked="false" label="Use 'raw' attribute of input if present"/> + </xml> + <xml name="param_dendrogram"> + <param argument="dendrogram" type="boolean" truevalue="True" falsevalue="False" checked="false" label="Compute and plot a dendrogram?" help="groupby categories are reordered accoring to the dendrogram order. If groups of var_names are set and those groups correspond to the groupby categories, those groups are also reordered. The ‘person’ method is used to compute the pairwise correlation between categories using all var_names in raw if use_raw is None, otherwise all adata.var_names are used. The linkage method used is complete."/> </xml> - <xml name="gene_symbols"> - <param argument="gene_symbols" type="text" value="" optional="true" label="Key for field in '.var' that stores gene symbols"> - <expand macro="sanitize_query" /> - </param> + <xml name="pl_var_group_positions"> + <repeat name="var_group_positions" title="Group of variables to highlight" help="This will draw a 'bracket' on top of the plot between the given start and end positions. If a label is given, it will be added on top of the bracket. "> + <param name="start" type="integer" min="0" value="" label="Start"/> + <param name="end" type="integer" min="0" value="" label="End"/> + <param argument="label" type="text" value="" label="Label"> + <expand macro="sanitize_query"/> + </param> + </repeat> </xml> - <xml name="param_n_genes"> - <param argument="n_genes" type="integer" min="0" value="10" label="Number of genes to show" help="It is only used if you are not specifying certain variable names"/> + <xml name="param_var_group_rotation"> + <param argument="var_group_rotation" type="float" value="" optional="true" label="Label rotation degrees" help="By default, labels larger than 4 characters are rotated 90 degrees"/> </xml> - <xml name="pl_dotplot"> - <param argument="color_map" type="select" optional="true" label="Color palette"> - <expand macro="matplotlib_pyplot_colormap"/> - </param> - <param argument="dot_max" type="float" value="" min="0" max="1" optional="true" label="Maximum dot size" help="If none, the maximum dot size is set to the maximum fraction value found (e.g. 0.6). If given, the value should be a number between 0 and 1. All fractions larger than dot_max are clipped to this value."/> - <param argument="dot_min" type="float" value="" min="0" max="1" optional="true" label="Minimum dot size" help="If none, the minimum dot size is set to 0. If given, the value should be a number between 0 and 1. All fractions smaller than dot_min are clipped to this value."/> - <expand macro="section_matplotlib_pyplot_scatter"/> + <xml name="params_plots"> + <expand macro="param_log"/> + <expand macro="param_use_raw" falsevalue="None"/> + <expand macro="param_dendrogram"/> + <expand macro="pl_var_group_positions"/> + <expand macro="param_var_group_rotation"/> + <expand macro="pl_figsize"/> + <expand macro="param_layer" optional="true" 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_pl_dotplot@"><![CDATA[ - #if $method.color_map - color_map='$method.color_map', + <token name="@CMD_PARAMS_PLOTS@"><![CDATA[ + log=$method.log, + use_raw=$method.use_raw, + dendrogram=$method.dendrogram, + #if len($method.var_group_positions) > 0: + #set $var_group_positions=[] + #set $var_group_labels=[] + #for $i, $s in enumerate($method.var_group_positions) + #silent $var_group_positions.append((int($s.start), int($s.end))) + #silent $var_group_labels.append(str($s.label)) + #end for + var_group_positions=$var_group_positions, + var_group_labels=$var_group_labels, #end if - #if str($method.dot_max) != '' - dot_max=$method.dot_max, + #if str($method.var_group_rotation) != '': + var_group_rotation=$method.var_group_rotation, #end if - #if str($method.dot_min) != '' - dot_min=$method.dot_min, - #end if - @CMD_params_matplotlib_pyplot_scatter@ + @CMD_PARAMS_FIGSIZE@ + @CMD_PARAM_LAYER@ ]]> </token> - <xml name="param_key"> - <param argument="key" type="text" value="" label="Key used to store the ranking results in 'uns'"> - <expand macro="sanitize_query" /> - </param> + + <xml name="param_alpha"> + <param argument="alpha" type="float" value="" min="0" max="1" optional="true" label="Alpha blending value" help="Between 0 (transparent) and 1 (opaque)"/> + </xml> + <xml name="param_vmin" token_label="Minimum value to normalize luminance data" token_help="If not set, it is inferred from the data and other keyword arguments"> + <param argument="vmin" type="float" value="" optional="true" label="@LABEL@" help="@HELP@"/> + </xml> + <xml name="param_vmax" token_label="Maximum value to normalize luminance data" token_help="If not set, it is inferred from the data and other keyword arguments"> + <param argument="vmax" type="float" value="" optional="true" label="@LABEL@" help="@HELP@"/> + </xml> + <xml name="param_vcenter"> + <param argument="vcenter" type="float" value="" optional="true" label="The value representing the center of the color scale" help="Useful for diverging colormaps."/> </xml> - <xml name="pl_heatmap"> + <xml name="section_matplotlib_pyplot_scatter"> + <section name="matplotlib_pyplot_scatter" title="Parameters for matplotlib.pyplot.scatter"> + <expand macro="param_alpha"/> + <expand macro="param_vmin"/> + <expand macro="param_vmax"/> + <param argument="linewidths" type="float" value="0" label="Linewidth of the marker edges"/> + <expand macro="param_matplotlib_pyplot_edgecolors"/> + </section> + </xml> + <token name="@CMD_SECTION_MATPLOTLIB_PYPLOT_SCATTER@"><![CDATA[ + #if str($method.matplotlib_pyplot_scatter.vmin) != '': + vmin=$method.matplotlib_pyplot_scatter.vmin, + #end if + #if str($method.matplotlib_pyplot_scatter.vmax) != '': + vmax=$method.matplotlib_pyplot_scatter.vmax, + #end if + #if str($method.matplotlib_pyplot_scatter.alpha) != '': + alpha=$method.matplotlib_pyplot_scatter.alpha, + #end if + linewidth=$method.matplotlib_pyplot_scatter.linewidths, + #if $method.matplotlib_pyplot_scatter.edgecolors: + edgecolor='$method.matplotlib_pyplot_scatter.edgecolors', + #end if + ]]> + </token> + + <xml name="params_pl_heatmap"> <expand macro="param_swap_axes"/> <param argument="show_gene_labels" type="boolean" truevalue="True" falsevalue="False" checked="false" label="Show gene labels?" help="By default gene labels are shown when there are 50 or less genes. Otherwise the labels are removed."/> + <expand macro="param_standard_scale"/> <section name="matplotlib_pyplot_imshow" title="Parameters for matplotlib.pyplot.imshow"> <expand macro="param_cmap"/> - <param name="interpolation" type="select" label="Interpolation method" help=""> - <option value="None">none</option> + <param name="interpolation" type="select" label="Interpolation method"> + <option value="None" selected="true">none</option> <option value="nearest">nearest</option> <option value="bilinear">bilinear</option> <option value="bicubic">bicubic</option> @@ -1194,106 +837,627 @@ <expand macro="param_vmin"/> <expand macro="param_vmax"/> <param name="origin" type="select" label="Place the [0,0] index of the array in the upper left or lower left corner of the axes" help=" The convention 'upper' is typically used for matrices and images."> - <option value="upper">Upper</option> + <option value="upper" selected="true">Upper</option> <option value="lower">Lower</option> </param> </section> </xml> - <token name="@CMD_pl_heatmap@"><![CDATA[ + <token name="@CMD_PARAMS_PL_HEATMAP@"><![CDATA[ swap_axes=$method.swap_axes, show_gene_labels=$method.show_gene_labels, - #if $method.matplotlib_pyplot_imshow.cmap + @CMD_STANDARD_SCALE@ + #if $method.matplotlib_pyplot_imshow.cmap: cmap='$method.matplotlib_pyplot_imshow.cmap', #end if - #if str($method.matplotlib_pyplot_imshow.interpolation) != 'None' + #if str($method.matplotlib_pyplot_imshow.interpolation) != 'None': interpolation='$method.matplotlib_pyplot_imshow.interpolation', #end if - #if str($method.matplotlib_pyplot_imshow.alpha) != '' + #if str($method.matplotlib_pyplot_imshow.alpha) != '': alpha=$method.matplotlib_pyplot_imshow.alpha, #end if - #if str($method.matplotlib_pyplot_imshow.vmin) != '' + #if str($method.matplotlib_pyplot_imshow.vmin) != '': vmin=$method.matplotlib_pyplot_imshow.vmin, #end if - #if str($method.matplotlib_pyplot_imshow.vmax) != '' + #if str($method.matplotlib_pyplot_imshow.vmax) != '': vmax=$method.matplotlib_pyplot_imshow.vmax, #end if - origin='$method.matplotlib_pyplot_imshow.origin' + origin='$method.matplotlib_pyplot_imshow.origin', ]]> </token> - <xml name="pl_rank_genes_groups_ext"> - <expand macro="param_groups"/> - <expand macro="param_n_genes"/> - <expand macro="param_key"/> - </xml> - <token name="@CMD_pl_rank_genes_groups_ext@"><![CDATA[ - @CMD_params_groups@ - n_genes=$method.n_genes, - #if $method.key - key='$method.key', - #end if - ]]> - </token> - <xml name="pl_matrixplot"> + + <xml name="params_pl_matrixplot"> <expand macro="param_swap_axes"/> <section name="matplotlib_pyplot_pcolor" title="Parameters for matplotlib.pyplot.pcolor"> <param argument="cmap" type="select" optional="true" label="Color palette"> <expand macro="seaborn_color_palette_options"/> </param> - <param argument="vmin" type="float" value="" optional="true" label="Minimum value to anchor the colormap" help=""/> - <param argument="vmax" type="float" value="" optional="true" label="Maximum value to anchor the colormap" help=""/> <expand macro="param_matplotlib_pyplot_edgecolors"/> <expand macro="param_alpha"/> - <param argument="snap" type="boolean" truevalue="True" falsevalue="False" checked="false" label="Snap the mesh to pixel boundaries?" help=""/> + <param argument="snap" type="boolean" truevalue="True" falsevalue="False" checked="false" label="Snap the mesh to pixel boundaries?"/> </section> + <expand macro="param_standard_scale"/> + <expand macro="param_vmin" label="The value representing the lower limit of the color scale" help="Values smaller than vmin are plotted with the same color as vmin."/> + <expand macro="param_vmax" label="The value representing the upper limit of the color scale" help="Values larger than vmax are plotted with the same color as vmax."/> + <expand macro="param_vcenter"/> </xml> - <token name="@CMD_pl_matrixplot@"><![CDATA[ + <token name="@CMD_PARAMS_PL_MATRIXPLOT@"><![CDATA[ swap_axes=$method.swap_axes, - #if $method.matplotlib_pyplot_pcolor.cmap + #if $method.matplotlib_pyplot_pcolor.cmap: cmap='$method.matplotlib_pyplot_pcolor.cmap', #end if - #if str($method.matplotlib_pyplot_pcolor.vmin) != '' - vmin=$method.matplotlib_pyplot_pcolor.vmin, + #if $method.matplotlib_pyplot_pcolor.edgecolors: + edgecolor='$method.matplotlib_pyplot_pcolor.edgecolors', #end if - #if str($method.matplotlib_pyplot_pcolor.vmax) != '' - vmax=$method.matplotlib_pyplot_pcolor.vmax, - #end if - #if $method.matplotlib_pyplot_pcolor.edgecolors - ec='$method.matplotlib_pyplot_pcolor.edgecolors', - #end if - #if str($method.matplotlib_pyplot_pcolor.alpha) != '' + #if str($method.matplotlib_pyplot_pcolor.alpha) != '': alpha=$method.matplotlib_pyplot_pcolor.alpha, #end if - snap=$method.matplotlib_pyplot_pcolor.snap + snap=$method.matplotlib_pyplot_pcolor.snap, + #if str($method.vmin) != '': + vmin=$method.vmin, + #end if + #if str($method.vmax) != '': + vmax=$method.vmax, + #end if + #if str($method.vcenter) != '': + vcenter=$method.vcenter, + #end if + @CMD_STANDARD_SCALE@ + ]]> + </token> + + <xml name="conditional_stripplot"> + <conditional name="stripplot"> + <param argument="stripplot" type="select" label="Add a stripplot on top of the violin plot"> + <option value="True" selected="true">Yes</option> + <option value="False">No</option> + </param> + <when value="True"> + <conditional name="jitter"> + <param argument="jitter" type="select" label="Add a jitter to the stripplot"> + <option value="True" selected="true">Yes</option> + <option value="False">No</option> + </param> + <when value="True"> + <param argument="size" type="float" min="0" value="1" label="Size of the jitter points"/> + </when> + <when value="False"/> + </conditional> + </when> + <when value="False"/> + </conditional> + </xml> + <token name="@CMD_CONDITIONAL_STRIPPLOT@"><![CDATA[ + stripplot=$method.violin_plot.stripplot.stripplot, +#if str($method.violin_plot.stripplot.stripplot) == 'True': + jitter=$method.violin_plot.stripplot.jitter.jitter, + #if str($method.violin_plot.stripplot.jitter.jitter) == 'True': + size=$method.violin_plot.stripplot.jitter.size, + #end if +#end if + ]]> + </token> + + <xml name="params_seaborn_violinplot"> + <section name="seaborn_violinplot" title="Parameters for seaborn.violinplot"> + <param argument="bw_method" type="select" label="Name of a reference rule when computing the kernel bandwidth"> + <option value="scott" selected="true">scott</option> + <option value="silverman">silverman</option> + </param> + <param argument="bw_adjust" type="float" value="1" label="Factor that scales the bandwidth to use more or less smoothing."/> + <param argument="orient" type="select" optional="true" label="Orientation of the plot"> + <option value="v">vertical</option> + <option value="h">horizontal</option> + </param> + <param argument="linewidth" type="float" value="" optional="true" label="Width of the gray lines that frame the plot elements"/> + <param argument="color" type="select" optional="true" label="Color for all of the elements"> + <expand macro="matplotlib_color"/> + </param> + <param argument="saturation" type="float" value="0.75" min="0" max="1" label="Proportion of the original saturation to draw colors at"/> + </section> + </xml> + <token name="@CMD_PARAMS_SEABORN_VIOLINPLOT@"><![CDATA[ + bw_method='$method.seaborn_violinplot.bw_method', + bw_adjust=$method.seaborn_violinplot.bw_adjust, + #if $method.seaborn_violinplot.orient: + orient='$method.seaborn_violinplot.orient', + #end if + #if str($method.seaborn_violinplot.linewidth) != '': + linewidth=$method.seaborn_violinplot.linewidth, + #end if + #if $method.seaborn_violinplot.color: + color='$method.seaborn_violinplot.color', + #end if + saturation=$method.seaborn_violinplot.saturation, + ]]></token> + + <xml name="param_color"> + <param argument="color" type="text" value="" optional="true" label="Keys for annotations of observations/cells or variables/genes" help="One or a list of comma-separated index or key from either '.obs' or '.var'"> + <expand macro="sanitize_query"/> + </param> + </xml> + <token name="@CMD_PARAM_COLOR@"><![CDATA[ +#if str($method.color) != '': + #set $color = ([x.strip() for x in str($method.color).split(',')]) + color=$color, +#end if + ]]> + </token> + + <xml name="param_groups"> + <param argument="groups" type="text" value="" optional="true" label="Categorical observation annotations to plot" help="Comma-separated"> + <expand macro="sanitize_query"/> + </param> + </xml> + <token name="@CMD_PARAM_GROUPS@"><![CDATA[ +#if str($method.groups) != '': + #set $groups=([x.strip() for x in str($method.groups).split(',')]) + groups=$groups, +#end if + ]]> + </token> + + + <xml name="param_pl_components"> + <repeat name="components" title="Component"> + <param argument="axis1" type="text" value="1" label="X-Axis"> + <expand macro="sanitize_query"/> + </param> + <param argument="axis2" type="text" value="2" label="Y-Axis"> + <expand macro="sanitize_query"/> + </param> + </repeat> + </xml> + <token name="@CMD_PARAM_PL_COMPONENTS@"><![CDATA[ +#if len($method.plot.components) > 0: + #set $components=[] + #for $i, $s in enumerate($method.plot.components) + #silent $components.append(str($s.axis1) + ',' + str($s.axis2)) + #end for + components=$components, +#end if + ]]> + </token> + + <xml name="param_legend_fontsize"> + <param argument="legend_fontsize" type="integer" optional="true" value="" label="Legend font size"/> + </xml> + <token name="@CMD_PARAM_LEGEND_FONTSIZE@"><![CDATA[ + #if str($method.plot.legend_fontsize) != '': + legend_fontsize=$method.plot.legend_fontsize, + #end if + ]]> + </token> + + <xml name="param_size"> + <param argument="size" type="float" optional="true" value="" label="Point size"/> + </xml> + <token name="@CMD_PARAM_SIZE@"><![CDATA[ + #if str($method.plot.size) != '': + size=$method.plot.size, + #end if + ]]> + </token> + + <xml name="param_title"> + <param argument="title" type="text" value="" optional="true" label="Title for panels" help="Titles must be separated by a comma"> + <expand macro="sanitize_query"/> + </param> + </xml> + <token name="@CMD_PARAM_TITLE@"><![CDATA[ + #if str($method.plot.title) != '': + title='$method.plot.title', + #end if ]]> </token> - <xml name="pl_stacked_violin"> + + <xml name="param_projection"> + <param argument="projection" type="select" label="Projection of plot"> + <option value="2d" selected="true">2d</option> + <option value="3d">3d</option> + </param> + </xml> + <xml name="param_legend_loc"> + <param argument="legend_loc" type="select" label="Location of legend"> + <yield /> + <option value="none">none</option> + <option value="on data export">on data export</option> + <option value="best">best</option> + <option value="upper right">upper right</option> + <option value="upper left">upper left</option> + <option value="lower left">lower left</option> + <option value="lower right">lower right</option> + <option value="right">right</option> + <option value="center left">center left</option> + <option value="center right">center right</option> + <option value="lower center">lower center</option> + <option value="upper center">upper center</option> + <option value="center">center</option> + </param> + </xml> + <xml name="param_legend_fontweight"> + <param argument="legend_fontweight" type="select" label="Legend font weight"> + <option value="bold" selected="true">bold</option> + <option value="normal">normal</option> + <option value="light">light</option> + <option value="medium">medium</option> + <option value="semibold">semibold</option> + <option value="heavy">heavy</option> + <option value="black">black</option> + </param> + </xml> + <xml name="param_color_map"> + <param argument="color_map" type="select" optional="true" label="Color map to use for continous variables"> + <expand macro="matplotlib_pyplot_colormap"/> + </param> + </xml> + <xml name="param_palette"> + <param argument="palette" type="select" optional="true" label="Colors to use for plotting categorical annotation groups"> + <expand macro="matplotlib_pyplot_colormap"/> + </param> + </xml> + <xml name="param_frameon"> + <param argument="frameon" type="boolean" truevalue="True" falsevalue="False" checked="true" label="Draw a frame around the scatter plot?"/> + </xml> + <xml name="param_ncols"> + <param argument="ncols" type="integer" min="0" value="4" label="Number of panels per row"/> + </xml> + <xml name="param_wspace"> + <param argument="wspace" type="float" min="0" value="0.1" label="Width of the space between multiple panels"/> + </xml> + <xml name="param_hspace"> + <param argument="hspace" type="float" min="0" value="0.25" label="Height of the space between multiple panels"/> + </xml> + + <xml name="params_pl_attribute_section"> + <section name="plot" title="Plot attributes"> + <expand macro="param_pl_components"/> + <expand macro="param_projection"/> + <expand macro="param_legend_loc"> + <option value="right margin">right margin</option> + <option value="on data">on data</option> + </expand> + <expand macro="param_legend_fontsize"/> + <expand macro="param_legend_fontweight"/> + <expand macro="param_size"/> + <expand macro="param_color_map"/> + <expand macro="param_palette"/> + <expand macro="param_frameon"/> + <expand macro="param_ncols"/> + <expand macro="param_wspace"/> + <expand macro="param_hspace"/> + <expand macro="param_title"/> + </section> + </xml> + <token name="@CMD_PARAMS_PL_ATTRIBUTE_SECTION@"><![CDATA[ + @CMD_PARAM_PL_COMPONENTS@ + projection='$method.plot.projection', + #if str($method.plot.legend_loc) != '': + legend_loc='$method.plot.legend_loc', + #end if + @CMD_PARAM_LEGEND_FONTSIZE@ + legend_fontweight='$method.plot.legend_fontweight', + @CMD_PARAM_SIZE@ + #if $method.plot.color_map: + color_map='$method.plot.color_map', + #end if + #if $method.plot.palette: + palette='$method.plot.palette', + #end if + frameon=$method.plot.frameon, + ncols=$method.plot.ncols, + wspace=$method.plot.wspace, + hspace=$method.plot.hspace, + @CMD_PARAM_TITLE@ + ]]> + </token> + + <xml name="pl_edges"> + <conditional name="edges"> + <param argument="edges" type="select" label="Show edges?"> + <option value="False" selected="true">No</option> + <option value="True">Yes</option> + </param> + <when value="True"> + <param argument="edges_width" type="float" min="0" value="0.1" label="Width of edges"/> + <param argument="edges_color" type="select" optional="true" label="Color of edges"> + <expand macro="matplotlib_color"/> + </param> + </when> + <when value="False"/> + </conditional> + </xml> + <token name="@CMD_PL_EDGES@"><![CDATA[ +#if str($method.edges.edges) == 'True': + edges=True, + edges_width=$method.edges.edges_width, + #if $method.edges.edges_color: + edges_color='$method.edges.edges_color', + #end if +#else + edges=False, +#end if + ]]> + </token> + + + <xml name="options_layout"> + <option value="fa" selected="true">fa: ForceAtlas2</option> + <option value="drl">drl: Distributed Recursive Layout, pretty fast</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="lgl">Large Graph, very fast</option> + <option value="rt">rt: Reingold Tilford tree layout</option> + <option value="rt_circular">rt_circular: Reingold Tilford tree circular</option> + </xml> + <xml name="param_layout"> + <param argument="layout" type="select" label="Plotting layout" optional="false"> + <expand macro="options_layout"/> + </param> + </xml> + <xml name="params_pl_paga"> + <param argument="threshold" type="float" min="0" value="" optional="true" 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="param_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'."> + <expand macro="sanitize_query"/> + </param> + <param argument="pos" type="data" format="tabular,csv,tsv" optional="true" label="Two-column tabular file storing the x and y coordinates for drawing"/> + <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."> + <expand macro="sanitize_query"/> + </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"/> + <param argument="random_state" type="integer" value="0" label="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="0" 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="sanitize_query"/> + </param> + <param argument="transitions" type="text" value="" label="Key corresponding to the matrix storing the arrows" help="Key for '.uns['paga']', e.g. 'transistions_confidence'"> + <expand macro="sanitize_query"/> + </param> + <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"> + <expand macro="sanitize_query"/> + </param> + <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."> + <expand macro="sanitize_query"/> + </param> + <param argument="single_component" type="boolean" truevalue="True" falsevalue="False" checked="false" label="Restrict to largest connected component?"/> + <param argument="fontsize" type="integer" min="0" value="" optional="true" label="Font size for node labels"/> + <param argument="node_size_scale" type="float" min="0" value="1.0" label="Size of the nodes"/> + <param argument="node_size_power" type="float" min="0" value="0.5" label="Power with which groups sizes influence the radius of the nodes"/> + <param argument="edge_width_scale" type="float" min="0" value="1.0" label="Scale for edge width"/> + <param argument="min_edge_width" type="float" min="0" value="" optional="true" label="Min width of solid edges"/> + <param argument="max_edge_width" type="float" min="0" value="" optional="true" label="Max width of solid and dashed edges"/> + <param argument="arrowsize" type="integer" min="0" value="30" label="Arrow size" help="For directed graphs, choose the size of the arrow head head's length and width."/> + <param argument="normalize_to_color" type="boolean" truevalue="True" falsevalue="False" checked="false" label="Normalize categorical plots to color or the underlying grouping?"/> + <expand macro="param_cmap"/> + <expand macro="param_title"/> + <expand macro="param_frameon"/> + </xml> + <token name="@CMD_PARAMS_PL_PAGA@"><![CDATA[ + #if str($method.threshold) != '': + threshold=$method.threshold, + #end if + #if str($method.groups) != '': + #set $groups=([x.strip() for x in str($method.groups).split(',')]) + groups=$groups, + #end if + #if str($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 + #if str($method.labels) != '': + #set $labels=([x.strip() for x in str($method.labels).split(',')]) + labels=$labels, + #end if + layout='$method.layout', + #if $method.init_pos: + init_pos=np.fromfile($method.init_pos, dtype=dt), + #end if + random_state=$method.random_state, + #if str($method.root) != '': + #set $root=([int(x.strip()) for x in str($method.root).split(',')]) + root=$root, + #end if + #if str($method.transitions) != '': + transitions='$method.transitions', + #end if + solid_edges='$method.solid_edges', + #if str($method.dashed_edges) != '': + dashed_edges='$method.dashed_edges', + #end if + single_component=$method.single_component, + fontsize=$method.fontsize, + node_size_scale=$method.node_size_scale, + node_size_power=$method.node_size_power, + edge_width_scale=$method.edge_width_scale, + #if str($method.min_edge_width) != '': + min_edge_width=$method.min_edge_width, + #end if + #if str($method.max_edge_width) != '': + max_edge_width=$method.max_edge_width, + #end if + arrowsize=$method.arrowsize, + normalize_to_color=$method.normalize_to_color, + #if $method.cmap: + cmap='$method.cmap', + #end if + #if str($method.title) != '': + title='$method.title', + #end if + frameon=$method.frameon, + ]]> + </token> + + <xml name="param_gene_symbols"> + <param argument="gene_symbols" type="text" value="" optional="true" label="Key for field in '.var' that stores gene symbols" help="By default 'var_names' refer to the index column of the '.var' DataFrame"> + <expand macro="sanitize_query"/> + </param> + </xml> + <token name="@CMD_PARAM_GENE_SYMBOLS@"><![CDATA[ + #if str($method.gene_symbols) != '': + gene_symbols='$method.gene_symbols', + #end if + ]]> + </token> + + <xml name="params_pl_dotplot"> + <param argument="color_map" type="select" optional="true" label="Color palette"> + <expand macro="matplotlib_pyplot_colormap"/> + </param> + <param argument="dot_max" type="float" value="" min="0" max="1" optional="true" label="Maximum dot size" help="If none, the maximum dot size is set to the maximum fraction value found (e.g. 0.6). If given, the value should be a number between 0 and 1. All fractions larger than dot_max are clipped to this value."/> + <param argument="dot_min" type="float" value="" min="0" max="1" optional="true" label="Minimum dot size" help="If none, the minimum dot size is set to 0. If given, the value should be a number between 0 and 1. All fractions smaller than dot_min are clipped to this value."/> + <expand macro="param_standard_scale"/> + <param argument="expression_cutoff" type="float" min="0.0" value="0.0" label="Expression cutoff that is used for binarizing the gene expression and determining the fraction of cells expressing given genes" help="A gene is expressed only if the expression value is greater than this threshold."/> + <param argument="mean_only_expressed" type="boolean" truevalue="True" falsevalue="False" checked="false" label="average the gene expression only over the cells expressing the given genes"/> + <expand macro="section_matplotlib_pyplot_scatter"/> + </xml> + <token name="@CMD_PL_DOTPLOT@"><![CDATA[ + #if $method.color_map: + color_map='$method.color_map', + #end if + #if str($method.dot_max) != '': + dot_max=$method.dot_max, + #end if + #if str($method.dot_min) != '': + dot_min=$method.dot_min, + #end if + @CMD_STANDARD_SCALE@ + expression_cutoff=$method.expression_cutoff, + mean_only_expressed=$method.mean_only_expressed, + @CMD_SECTION_MATPLOTLIB_PYPLOT_SCATTER@ + ]]> + </token> + + <xml name="values_to_plot"> + <param argument="values_to_plot" type="select" optional="true" label="Values to plot" help="Defualt: plots mean expression. When plotting logfoldchanges a divergent colormap is recommended."> + <option value="scores">Scores</option> + <option value="logfoldchanges">Log foldchanges</option> + <option value="pvals">P-values</option> + <option value="pvals_adj">Adjusted p-values</option> + <option value="log10_pvals">log10 of p-values</option> + <option value="log10_pvals_adj">log10 of adjusted p-values</option> + </param> + </xml> + <token name="@CMD_VALUES_TO_PLOT@"><![CDATA[ + #if $method.values_to_plot: + values_to_plot='$method.values_to_plot', + colorbar_title='$method.values_to_plot', + #end if + ]]> + </token> + + + <xml name="param_n_genes" token_value=""> + <param argument="n_genes" type="integer" min="0" value="@VALUE@" optional="true" label="Number of genes to show" help="It is only used if you are not specifying certain variable names"/> + </xml> + <xml name="param_key"> + <param argument="key" type="text" value="" label="Key used to store the ranking results in 'uns'"> + <expand macro="sanitize_query"/> + </param> + </xml> + + <xml name="pl_rank_genes_groups_ext"> + <expand macro="pl_var_names"/> + <expand macro="param_groups"/> + <expand macro="param_n_genes" value=""/> + <expand macro="param_key"/> + <param argument="min_logfoldchange" type="integer" optional="true" value="" label="Value to filter genes in groups if their logfoldchange is less than this value"/> + </xml> + <token name="@CMD_PL_RANK_GENES_GROUPS_EXT@"><![CDATA[ + #if str($method.var_names.type) == 'custom': + #set $var_names = ([x.strip() for x in str($method.var_names.var_names).split(',')]) + var_names=$var_names, + #else if str($method.var_names.type) == 'customfile': + var_names={key: [v for v in list(value.values()) if pd.notna(v)] for key, value in pd.read_csv('$var_names', sep='\t', index_col=0, header=header).to_dict(orient='index').items()}, + #end if + @CMD_PARAM_GROUPS@ + #if str($method.n_genes) != '': + n_genes=$method.n_genes, + #end if + #if str($method.key) != '': + key='$method.key', + #end if + #if str($method.min_logfoldchange) != '': + min_logfoldchange=$method.min_logfoldchange, + #end if + ]]> + </token> + + <xml name="param_density_norm"> + <param argument="density_norm" type="select" label="Method used to scale the width of each violin"> + <option value="area" selected="true">area: each violin will have the same area</option> + <option value="width">width: each violin will have the same width</option> + <option value="count">count: the width of the violins will be scaled by the number of observations in that bin</option> + </param> + </xml> + <xml name="params_pl_stacked_violin"> <expand macro="param_swap_axes"/> <section name="violin_plot" title="Violin plot attributes"> <expand macro="conditional_stripplot"/> - <expand macro="param_scale"/> + <expand macro="param_density_norm"/> </section> <param argument="row_palette" type="select" optional="true" label="Colors to use in each of the stacked violin plots"> <option value="muted">muted</option> <expand macro="seaborn_color_palette_options"/> </param> - <param argument="standard_scale" type="select" label="Standardize a dimension between 0 and 1" help="Each variable or observation is subtracted by the minimum and divided each by its maximum."> - <option value="None">No standardization</option> - <option value="var">Standardization on variable</option> - <option value="obs">Standardization on observation</option> - </param> - <expand macro="seaborn_violinplot"/> + <expand macro="param_standard_scale"/> + <expand macro="params_seaborn_violinplot"/> + <param argument="yticklabels" type="boolean" truevalue="True" falsevalue="False" checked="false" label="Set to view the y tick labels"/> + <expand macro="param_vmin" label="The value representing the lower limit of the color scale" help="Values smaller than vmin are plotted with the same color as vmin."/> + <expand macro="param_vmax" label="The value representing the upper limit of the color scale" help="Values larger than vmax are plotted with the same color as vmax."/> + <expand macro="param_vcenter"/> </xml> - <token name="@CMD_pl_stacked_violin@"><![CDATA[ + <token name="@CMD_PARAMS_PL_STACKED_VIOLIN@"><![CDATA[ swap_axes=$method.swap_axes, - @CMD_conditional_stripplot@ - scale='$method.violin_plot.scale', - #if $method.row_palette + @CMD_CONDITIONAL_STRIPPLOT@ + density_norm='$method.violin_plot.density_norm', + #if $method.row_palette: row_palette='$method.row_palette', #end if - #if str($method.standard_scale) != 'None' - standard_scale='$method.standard_scale', + @CMD_STANDARD_SCALE@ + @CMD_PARAMS_SEABORN_VIOLINPLOT@ + yticklabels=$method.yticklabels, + #if str($method.vmin) != '': + vmin=$method.vmin, #end if - @CMD_params_seaborn_violinplot@ + #if str($method.vmax) != '': + vmax=$method.vmax, + #end if + #if str($method.vcenter) != '': + vcenter=$method.vcenter, + #end if ]]> </token> + + <xml name="params_scatter_outine"> + <param argument="add_outline" type="boolean" truevalue="True" falsevalue="False" checked="false" label="Add a thin border around groups of dots" help="In some situations this can enhance the aesthetics of the resulting image"/> + <param name="outline_color_border" type="select" optional="true" label="Border color around the scatter dot" help="Default: black"> + <expand macro="matplotlib_color"/> + </param> + <param name="outline_color_gap" type="select" optional="true" label="Gap color between the border color and the scatter dot" help="Default: white"> + <expand macro="matplotlib_color"/> + </param> + <param argument="outline_width_border" type="float" value="0.3" optional="true" label=" width of the border color as a fraction of the scatter dot size "/> + <param argument="outline_width_gap" type="float" value="0.05" optional="true" label="The width of the gap color"/> + </xml> + <token name="@CMD_SCATTER_OUTINE@"><![CDATA[ + add_outline=$method.add_outline, + #if $method.outline_color_border and $method.outline_color_gap: + outline_color=($method.outline_color_border, $method.outline_color_gap), + #end if + outline_width=($method.outline_width_border, $method.outline_width_gap), + ]]> + </token> + + + <!-- unused macros --> + <!-- <xml name="param_right_margin"> + <param argument="right_margin" type="float" value="1" label="Width of the space right of each plotting panel"/> + </xml> + <xml name="param_left_margin"> + <param argument="left_margin" type="float" value="1" label="Width of the space left of each plotting panel"/> + </xml> --> </macros>
--- a/remove_confounders.xml Tue Aug 20 09:51:42 2024 +0000 +++ b/remove_confounders.xml Sat Sep 14 12:43:38 2024 +0000 @@ -1,67 +1,164 @@ -<tool id="scanpy_remove_confounders" name="Remove confounders" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="@profile@"> +<tool id="scanpy_remove_confounders" name="Scanpy remove confounders" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="@PROFILE@"> <description>with scanpy</description> <macros> <import>macros.xml</import> </macros> <expand macro="bio_tools"/> - <expand macro="requirements"/> + <expand macro="requirements"> + <requirement type="package" version="1.6.0">bbknn</requirement> + <requirement type="package" version="0.0.10">harmonypy</requirement> + <requirement type="package" version="1.7.4">scanorama</requirement> + <requirement type="package" version="0.5.13">pynndescent</requirement> + </expand> <command detect_errors="exit_code"><![CDATA[ @CMD@ ]]></command> <configfiles> <configfile name="script_file"><![CDATA[ -@CMD_imports@ -@CMD_read_inputs@ +@CMD_IMPORTS@ +@CMD_READ_INPUTS@ -#if $method.method == "pp.regress_out" +#if str($method.method) == 'pp.regress_out': +print("stats before regress_out:", "min=", adata.X.min(), "max=", adata.X.max(), "mean=", adata.X.mean()) + +import os sc.pp.regress_out( adata=adata, + #if str($method.layer) != '': + layer='$method.layer', + #end if #set $keys = [str(x.strip()) for x in str($method.keys).split(',')] keys=$keys, + n_jobs = int(os.getenv("GALAXY_SLOTS", 4)), copy=False) -#else if $method.method == "pp.mnn_correct" - #for i, filepath in enumerate($methods.extra_adata) -adata_$i = ad.read('$filepath') - #end for +print("stats after regress_out:", "min=", adata.X.min(), "max=", adata.X.max(), "mean=", adata.X.mean()) -sc.pp.mnn_correct( - adata, - #for i, filepath in enumerate($methods.extra_adata) - adata_$i, - #end for - #if $methods.var_subset - #set $var_subset=([x.strip() for x in str($method.var_subset).split(',')]) - var_subset=$var_subset, - #end if - batch_key='$method.batch_key', - index_unique='$method.index_unique' - #if $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}) +## This function is commented out because the conda package is not working. Please add this if there is user demand and the conda package is fixed. If not please remove in the next update. +## #else if str($method.method) == 'external.pp.mnn_correct': +## #if $method.extra_adata: +## #for i, filepath in enumerate($method.extra_adata) +## adata_$i = sc.read_h5ad('$filepath') +## #end for +## #end if +## import os +## corrected = sc.external.pp.mnn_correct( +## adata, +## #if $method.extra_adata: +## #for i, filepath in enumerate($method.extra_adata) +## adata_$i, +## #end for +## #end if +## #if str($method.var_subset) != '': +## #set $var_subset=([x.strip() for x in str($method.var_subset).split(',')]) +## var_subset=$var_subset, +## #end if +## batch_key='$method.batch_key', +## index_unique='$method.index_unique', +## #if str($method.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=$method.cos_norm_out, +## #if str($method.svd_dim) != '': +## svd_dim=$method.svd_dim, +## #end if +## var_adj=$method.var_adj, +## compute_angle=$method.compute_angle, +## #if str($method.mnn_order) != '': +## mnn_order='$method.mnn_order', +## #end if +## #if str($method.svd_mode) != '': +## svd_mode='$method.svd_mode', +## #end if +## do_concatenate=True, +## save_raw=True, +## n_jobs = int(os.getenv("GALAXY_SLOTS", 4))) -#else if $method.method == "pp.combat" +## adata = corrected[0] + + +#else if str($method.method) == 'pp.combat': +print("stats before combat:", "min=", adata.X.min(), "max=", adata.X.max(), "mean=", adata.X.mean()) + sc.pp.combat( adata, key='$method.key', + #if str($method.covariates) != '': + #set $covariates = [str(x.strip()) for x in str($method.covariates).split(',')] + covariates=$covariates, + #end if inplace=True) +print("stats after combat:", "min=", adata.X.min(), "max=", adata.X.max(), "mean=", adata.X.mean()) + +#else if str($method.method) == 'external.pp.bbknn': +sc.external.pp.bbknn( + adata, + batch_key='$method.batch_key', + use_rep='$method.use_rep', + #if str($method.approx.approx_method) == 'no': + approx=False, + #else if str($method.approx.approx_method) == 'annoy': + approx=True, + use_annoy=True, + annoy_n_trees=$method.approx.annoy_n_trees, + #else if str($method.approx.approx_method) == 'pyNNDescent': + approx=True, + use_annoy=False, + pynndescent_n_neighbors=$method.approx.pynndescent_n_neighbors, + pynndescent_random_state=$method.approx.pynndescent_random_state, + #end if + metric='$method.metric', + neighbors_within_batch=$method.neighbors_within_batch, + n_pcs=$method.n_pcs, + #if str($method.trim) != '': + trim=$method.trim, + #end if + set_op_mix_ratio=$method.set_op_mix_ratio, + local_connectivity=$method.local_connectivity, + copy=False) + +#else if str($method.method) == 'external.pp.harmony_integrate': +sc.external.pp.harmony_integrate( + adata, + key='$method.key', + basis='$method.basis', + adjusted_basis='$method.adjusted_basis', + #if str($method.theta) != '': + theta=$method.theta, + #end if + #if str($method.lamb) != '': + lamb=$method.lamb, + #end if + sigma=$method.sigma, + #if str($method.nclust) != '': + nclust=$method.nclust, + #end if + tau=$method.tau, + block_size=$method.block_size, + max_iter_harmony=$method.max_iter_harmony, + max_iter_kmeans=$method.max_iter_kmeans, + epsilon_cluster=$method.epsilon_cluster, + epsilon_harmony=$method.epsilon_harmony) + +#else if str($method.method) == 'external.pp.scanorama_integrate': +sc.external.pp.scanorama_integrate( + adata, + key='$method.key', + basis='$method.basis', + adjusted_basis='$method.adjusted_basis', + knn=$method.knn, + sigma=$method.sigma, + approx=$method.approx, + alpha=$method.alpha, + batch_size=$method.batch_size) #end if -@CMD_anndata_write_outputs@ +@CMD_ANNDATA_WRITE_OUTPUTS@ ]]></configfile> </configfiles> <inputs> @@ -69,21 +166,29 @@ <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">Correct batch effects by matching mutual nearest neighbors, using 'pp.mnn_correct'</option> + <!-- This function is commented out because the conda package is not working. Please add this if there is user demand and the conda package is fixed. If not please remove in the next update. --> + <!-- <option value="external.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> + <option value="external.pp.bbknn">Batch effect removal with Batch balanced KNN (BBKNN), using 'external.pp.bbknn'</option> + <option value="external.pp.harmony_integrate">Integrate multiple single-cell experiments with Harmony, using 'external.pp.harmony_integrate'</option> + <option value="external.pp.scanorama_integrate">Integrate multiple single-cell experiments with Scanorama, using 'external.pp.scanorama_integrate'</option> </param> <when value="pp.regress_out"> + <param argument="layer" type="text" value="" label="Which element of layers to regress on"> + <expand macro="sanitize_query"/> + </param> <param argument="keys" type="text" value="" label="Keys for observation annotation on which to regress on" help="Keys separated by a comma"> - <expand macro="sanitize_query" /> + <expand macro="sanitize_query"/> </param> </when> - <when value="pp.mnn_correct"> + <!-- This function is commented out because the conda package is not working. Please add this if there is user demand and the conda package is fixed. If not please remove in the next update. --> + <!-- <when value="external.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"> - <expand macro="sanitize_query" /> + <expand macro="sanitize_query"/> </param> <param argument="batch_key" type="text" value="batch" label="Batch key for the concatenate"> - <expand macro="sanitize_query" /> + <expand macro="sanitize_query"/> </param> <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> @@ -92,7 +197,7 @@ <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"> - <expand macro="sanitize_query" /> + <expand macro="sanitize_query"/> </param> <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"/> @@ -102,18 +207,89 @@ <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"> - <expand macro="sanitize_query" /> + <expand macro="sanitize_query"/> </param> <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> --> <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"> - <expand macro="sanitize_query" /> + <expand macro="sanitize_query"/> + </param> + <param argument="covariates" type="text" value="" optional="true" label="Additional covariates besides the batch variable such as adjustment variables or biological condition."> + <expand macro="sanitize_query"/> + </param> + </when> + <when value="external.pp.bbknn"> + <param argument="batch_key" type="text" value="batch" label="Batch key for the concatenate"> + <expand macro="sanitize_query"/> + </param> + <param argument="use_rep" type="text" value="X_pca" label="The dimensionality reduction in .obsm to use for neighbour detection"> + <expand macro="sanitize_query"/> + </param> + <conditional name="approx"> + <param name="approx_method" type="select" label="Approximate neighbour finding"> + <option value="annoy" selected="true">Yes, using ANNOY algorithm</option> + <option value="pyNNDescent">Yes, using pyNNDescent</option> + <option value="no">Do not use approximate neighbor finding</option> + </param> + <when value="annoy"> + <param argument="annoy_n_trees" type="integer" value="10" label="The number of trees to construct in the annoy forest" help="More trees give higher precision when querying, at the cost of increased run time and resource intensity"/> + </when> + <when value="pyNNDescent"> + <param argument="pynndescent_n_neighbors" type="integer" value="30" label="The number of neighbours to include in the approximate neighbour graph" help="More neighbours give higher precision when querying, at the cost of increased run time and resource intensity"/> + <param argument="pynndescent_random_state" type="integer" value="0" label="The RNG seed to use when creating the graph"/> + </when> + <when value="no"/> + </conditional> + <param name="metric" type="select" label="Distance metric to use for the data"> + <expand macro="distance_metric_options"/> </param> + <param argument="neighbors_within_batch" type="integer" value="3" label="Number of top neighbours to report for each batch" help="total number of neighbours in the initial k-nearest-neighbours computation will be this number times the number of batches. This then serves as the basis for the construction of a symmetrical matrix of connectivities"/> + <param argument="n_pcs" type="integer" value="50" label="Number of dimensions to use in the analysis" help="in case of PCA, principal components"/> + <param argument="trim" type="integer" value="" optional="true" label="Trim the neighbours of each cell to these many top connectivities" help=" The lower the value the more independent the individual populations, at the cost of more conserved batch effect. If not set, sets the parameter value automatically to 10 times neighbors_within_batch times the number of batches. Set to 0 to skip."/> + <param argument="set_op_mix_ratio" type="float" value="1.0" min="0" max="1" label="UMAP connectivity computation parameter" help="controlling the blend between a connectivity matrix formed exclusively from mutual nearest neighbour pairs (0) and a union of all observed neighbour relationships with the mutual pairs emphasised (1)"/> + <param argument="local_connectivity" type="integer" value="1" label="Number of nearest neighbors of each cell are assumed to be fully connected"/> + </when> + <when value="external.pp.harmony_integrate"> + <param argument="key" type="text" value="batch" label="The name of the column in adata.obs that differentiates among experiments/batches"> + <expand macro="sanitize_query"/> + </param> + <param argument="basis" type="text" value="X_pca" label="The name of the field in adata.obsm where the PCA table is stored"> + <expand macro="sanitize_query"/> + </param> + <param argument="adjusted_basis" type="text" value="X_pca_harmony" label="The name of the field in adata.obsm where the adjusted PCA table will be stored after running this function"> + <expand macro="sanitize_query"/> + </param> + <param argument="theta" type="integer" value="" optional="true" label="Diversity clustering penalty parameter" help="Default theta=2. theta=0 does not encourage any diversity. Larger values of theta result in more diverse clusters."/> + <param argument="lamb" type="integer" value="" optional="true" min="1" label="Ridge regression penalty parameter" help="Default lamb=1. Lambda must be strictly positive. Smaller values result in more aggressive correction."/> + <param argument="sigma" type="float" value="0.1" label="Width of soft kmeans clusters" help="Sigma scales the distance from a cell to cluster centroids. Larger values of sigma result in cells assigned to more clusters. Smaller values of sigma make soft kmeans cluster approach hard clustering."/> + <param argument="nclust" type="integer" value="" optional="true" label="Number of clusters in model" help="nclust=1 equivalent to simple linear regression."/> + <param argument="tau" type="integer" value="0" label="Expected number of cells per cluster" help="Protection against overclustering small datasets with large ones"/> + <param argument="block_size" type="float" value="0.05" min="0" max="1" label="Proportion of cells to update during clustering" help="Larger values may be faster but less accurate"/> + <param argument="max_iter_harmony" type="integer" value="10" label="Maximum number of rounds to run Harmony" help="One round of Harmony involves one clustering and one correction step"/> + <param argument="max_iter_kmeans" type="integer" value="20" label="Maximum number of rounds to run clustering at each round of Harmony"/> + <param argument="epsilon_cluster" type="float" value="1e-5" label="Convergence tolerance for clustering round of Harmony"/> + <param argument="epsilon_harmony" type="float" value="1e-4" label="Convergence tolerance for Harmony"/> + </when> + <when value="external.pp.scanorama_integrate"> + <param argument="key" type="text" value="batch" label="The name of the column in adata.obs that differentiates among experiments/batches"> + <expand macro="sanitize_query"/> + </param> + <param argument="basis" type="text" value="X_pca" label="The name of the field in adata.obsm where the PCA table is stored"> + <expand macro="sanitize_query"/> + </param> + <param argument="adjusted_basis" type="text" value="X_scanorama" label="The name of the field in adata.obsm where the adjusted PCA table will be stored after running this function"> + <expand macro="sanitize_query"/> + </param> + <param argument="knn" type="integer" value="20" label="Number of nearest neighbors to use for matching"/> + <param argument="sigma" type="integer" value="15" label="Correction smoothing parameter on Gaussian kernel"/> + <param argument="approx" type="boolean" truevalue="True" falsevalue="False" checked="true" label="Use approximate nearest neighbors with Python annoy" help="greatly speeds up matching runtime"/> + <param argument="alpha" type="float" value="0.1" label="Alignment score minimum cutoff"/> + <param argument="batch_size" type="integer" value="5000" label="The batch size used in the alignment vector computation" help="Useful when integrating very large (>100k samples) datasets. Set to large value that runs within available memory."/> </when> </conditional> <expand macro="inputs_common_advanced"/> @@ -122,76 +298,228 @@ <expand macro="anndata_outputs"/> </outputs> <tests> + + <!-- test 1 --> <test expect_num_outputs="2"> - <!-- test 0 --> - <param name="adata" value="krumsiek11.h5ad" /> + <param name="adata" value="pp.pca.krumsiek11.batch.h5ad"/> <conditional name="method"> <param name="method" value="pp.regress_out"/> - <param name="keys" value="cell_type"/> + <param name="keys" value="batch"/> </conditional> <section name="advanced_common"> - <param name="show_log" value="true" /> + <param name="show_log" value="true"/> </section> <output name="hidden_output"> <assert_contents> <has_text_matching expression="sc.pp.regress_out"/> - <has_text_matching expression="keys=\['cell_type'\]"/> + <has_text_matching expression="keys=\['batch'\]"/> + <has_text_matching expression="stats before regress_out: min= -0.0163 max= 1.0106 mean= 0.2864376"/> + <has_text_matching expression="stats after regress_out: min= -0.7017021868145134 max= 0.7091581022301392 mean= -1.730938624756494e-16"/> + </assert_contents> + </output> + <output name="anndata_out" ftype="h5ad"> + <assert_contents> + <has_h5_keys keys="varm/PCs"/> </assert_contents> </output> - <output name="anndata_out" file="pp.regress_out.krumsiek11.h5ad" ftype="h5ad" compare="sim_size"/> </test> - <!--<test expect_num_outputs="2"> - < test 2 > - <param name="adata" value="krumsiek11.h5ad" /> + + <!-- This function is commented out because the conda package is not working. Please add this if there is user demand and the conda package is fixed. If not please remove in the next update. --> + <!-- test 2 --> + <!-- <test expect_num_outputs="2"> + <param name="adata" value="pp.pca.krumsiek11.batch.h5ad"/> + <param name="extra_adata" value="pp.pca.krumsiek11.batch.h5ad"/> <conditional name="method"> - <param name="method" value="pp.mnn_correct"/> - <param name="reg_keys" value="cell_type"/> + <param name="method" value="external.pp.mnn_correct"/> + <param name="batch_key" value="batch"/> </conditional> + <section name="advanced_common"> + <param name="show_log" value="true"/> + </section> <assert_stdout> - <has_text_matching expression="sc.pp.mnn_correct"/> - <has_text_matching expression="keys='cell_type'"/> + <has_text_matching expression="I_have_to_check"/> </assert_stdout> - <output name="anndata_out" file="pp.mnn_correct.krumsiek11.h5ad" ftype="h5ad" compare="sim_size"/> - </test>--> + <output name="hidden_output"> + <assert_contents> + <has_text_matching expression="sc.external.pp.mnn_correct"/> + <has_text_matching expression="batch_key='batch'"/> + </assert_contents> + </output> + <output name="anndata_out" file="external.pp.mnn_correct.krumsiek11.h5ad" ftype="h5ad" compare="sim_size"/> + </test> --> + + <!-- test 3 --> <test expect_num_outputs="2"> - <!-- test 1 --> - <param name="adata" value="blobs.h5ad" /> + <param name="adata" value="pp.pca.krumsiek11.batch.h5ad"/> <conditional name="method"> <param name="method" value="pp.combat"/> - <param name="key" value="blobs"/> </conditional> <section name="advanced_common"> - <param name="show_log" value="true" /> + <param name="show_log" value="true"/> </section> <output name="hidden_output"> <assert_contents> <has_text_matching expression="sc.pp.combat"/> - <has_text_matching expression="key='blobs'"/> + <has_text_matching expression="key='batch'"/> + <has_text_matching expression="stats before combat: min= -0.0163 max= 1.0106 mean= 0.2864376"/> + <has_text_matching expression="stats after combat: min= -0.07474318799213325 max= 1.2280063438242503 mean= 0.2870530757430964"/> + </assert_contents> + </output> + <output name="anndata_out" ftype="h5ad"> + <assert_contents> + <has_h5_keys keys="obsm/X_pca"/> + </assert_contents> + </output> + </test> + + <!-- test 4 --> + <test expect_num_outputs="2"> + <param name="adata" value="pp.pca.krumsiek11.batch.h5ad"/> + <conditional name="method"> + <param name="method" value="external.pp.bbknn"/> + <param name="n_pcs" value="10"/> + <param name="set_op_mix_ratio" value="0.5"/> + </conditional> + <section name="advanced_common"> + <param name="show_log" value="true"/> + </section> + <output name="hidden_output"> + <assert_contents> + <has_text_matching expression="external.pp.bbknn"/> + <has_text_matching expression="batch_key='batch'"/> + <has_text_matching expression="use_rep='X_pca'"/> + <has_text_matching expression="use_annoy=True"/> + <has_text_matching expression="annoy_n_trees=10"/> + <has_text_matching expression="neighbors_within_batch=3"/> + <has_text_matching expression="n_pcs=10"/> + <has_text_matching expression="set_op_mix_ratio=0.5"/> + </assert_contents> + </output> + <output name="anndata_out" ftype="h5ad"> + <assert_contents> + <has_h5_keys keys="uns/neighbors"/> + <has_h5_keys keys="obsp/distances,obsp/connectivities"/> </assert_contents> </output> - <output name="anndata_out" file="pp.combat.blobs.h5ad" ftype="h5ad" compare="sim_size"/> + </test> + + <!-- test 5 --> + <test expect_num_outputs="2"> + <param name="adata" value="pp.pca.krumsiek11.batch.h5ad"/> + <conditional name="method"> + <param name="method" value="external.pp.bbknn"/> + <conditional name="approx"> + <param name="approx_method" value="pyNNDescent"/> + <param name="pynndescent_n_neighbors" value="10"/> + </conditional> + <param name="n_pcs" value="10"/> + <param name="set_op_mix_ratio" value="0.5"/> + </conditional> + <section name="advanced_common"> + <param name="show_log" value="true"/> + </section> + <output name="hidden_output"> + <assert_contents> + <has_text_matching expression="external.pp.bbknn"/> + <has_text_matching expression="batch_key='batch'"/> + <has_text_matching expression="use_rep='X_pca'"/> + <has_text_matching expression="use_annoy=False"/> + <has_text_matching expression="pynndescent_n_neighbors=10"/> + <has_text_matching expression="pynndescent_random_state=0"/> + <has_text_matching expression="neighbors_within_batch=3"/> + <has_text_matching expression="n_pcs=10"/> + <has_text_matching expression="set_op_mix_ratio=0.5"/> + </assert_contents> + </output> + <output name="anndata_out" ftype="h5ad"> + <assert_contents> + <has_h5_keys keys="uns/neighbors"/> + <has_h5_keys keys="obsp/distances,obsp/connectivities"/> + </assert_contents> + </output> + </test> + + <!-- test 6 --> + <test expect_num_outputs="2"> + <param name="adata" value="pp.pca.krumsiek11.batch.h5ad"/> + <conditional name="method"> + <param name="method" value="external.pp.harmony_integrate"/> + <param name="theta" value="2"/> + <param name="lamb" value="1"/> + <param name="block_size" value="0.1"/> + </conditional> + <section name="advanced_common"> + <param name="show_log" value="true"/> + </section> + <output name="hidden_output"> + <assert_contents> + <has_text_matching expression="external.pp.harmony_integrate"/> + <has_text_matching expression="key='batch'"/> + <has_text_matching expression="basis='X_pca'"/> + <has_text_matching expression="adjusted_basis='X_pca_harmony'"/> + <has_text_matching expression="theta=2"/> + <has_text_matching expression="lamb=1"/> + <has_text_matching expression="block_size=0.1"/> + </assert_contents> + </output> + <output name="anndata_out" ftype="h5ad"> + <assert_contents> + <has_h5_keys keys="obsm/X_pca_harmony"/> + </assert_contents> + </output> + </test> + + <!-- test 7 --> + <test expect_num_outputs="2"> + <param name="adata" value="pp.pca.krumsiek11.batch.h5ad"/> + <conditional name="method"> + <param name="method" value="external.pp.scanorama_integrate"/> + <param name="knn" value="2"/> + <param name="sigma" value="10"/> + <param name="batch_size" value="100"/> + </conditional> + <section name="advanced_common"> + <param name="show_log" value="true"/> + </section> + <output name="hidden_output"> + <assert_contents> + <has_text_matching expression="external.pp.scanorama_integrate"/> + <has_text_matching expression="key='batch'"/> + <has_text_matching expression="basis='X_pca'"/> + <has_text_matching expression="adjusted_basis='X_scanorama'"/> + <has_text_matching expression="knn=2"/> + <has_text_matching expression="sigma=1"/> + <has_text_matching expression="batch_size=100"/> + </assert_contents> + </output> + <output name="anndata_out" ftype="h5ad"> + <assert_contents> + <has_h5_keys keys="obsm/X_scanorama"/> + </assert_contents> + </output> </test> </tests> <help><![CDATA[ Regress out unwanted sources of variation, using `pp.regress_out` ================================================================= -Regress out unwanted sources of variation, using simple linear regression. This is +Regress out unwanted sources of variation, using simple linear regression. This is inspired by Seurat's `regressOut` function in R. More details on the `scanpy documentation <https://scanpy.readthedocs.io/en/stable/api/scanpy.pp.regress_out.html>`__ -Correct batch effects by matching mutual nearest neighbors, using `pp.mnn_correct` -================================================================================== +.. This function is commented out because the conda package is not working. Please add this if there is user demand and the conda package is fixed. If not please remove in the next update. +.. Correct batch effects by matching mutual nearest neighbors, using `external.pp.mnn_correct` +.. =========================================================================================== -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 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. -Be reminded that it is not advised to use the corrected data matrices for differential expression testing. +.. 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/stable/generated/scanpy.external.pp.mnn_correct.html>`__ +.. More details on the `scanpy documentation +.. <https://scanpy.readthedocs.io/en/stable/generated/scanpy.external.pp.mnn_correct.html>`__ Correct batch effects with ComBat function (`pp.combat`) @@ -203,6 +531,33 @@ <https://scanpy.readthedocs.io/en/stable/api/generated/scanpy.pp.combat.html>`__ +Correct batch effects with bbknn function (`external.pp.bbknn`) +=============================================================== + +Batch balanced kNN alters the kNN procedure to identify each cell’s top neighbours in each batch separately instead of the entire cell pool with no accounting for batch. The nearest neighbours for each batch are then merged to create a final list of neighbours for the cell. Aligns batches in a quick and lightweight manner. + +More details on the `scanpy documentation +<https://scanpy.readthedocs.io/en/stable/generated/scanpy.external.pp.bbknn.html>`__ + + +Correct batch effects with harmony function (`external.pp.harmony_integrate`) +============================================================================= + +Harmony is an algorithm for integrating single-cell data from multiple experiments. +As Harmony works by adjusting the principal components, this function should be run after performing PCA but before computing the neighbor graph. + +More details on the `scanpy documentation +<https://scanpy.readthedocs.io/en/stable/generated/scanpy.external.pp.harmony_integrate.html>`__ + + +Correct batch effects with scanprama function (`external.pp.scanorama_integrate`) +================================================================================= + +Scanprama is an algorithm for integrating single-cell data from multiple experiments stored in an AnnData object. This function should be run after performing PCA but before computing the neighbor graph. + +More details on the `scanpy documentation +<https://scanpy.readthedocs.io/en/stable/generated/scanpy.external.pp.scanorama_integrate.html>`__ + ]]></help> <expand macro="citations"/> </tool>
Binary file test-data/pl.diffmap.neighbors_gauss_braycurtis.recipe_weinreb17.paul15_subsample.png has changed
Binary file test-data/pl.dpt_timeseries.dpt.diffmap.neighbors_gauss_braycurtis.recipe_weinreb17.paul15_subsample.png has changed
Binary file test-data/pl.highest_expr_genes.filter_genes_dispersion.krumsiek11-seurat.png has changed
Binary file test-data/pl.rank_genes_groups.newton-cg.pbmc68k_highly_reduced_marker_1.png has changed
Binary file test-data/pl.rank_genes_groups.newton-cg.pbmc68k_highly_reduced_marker_filtered_1.png has changed
Binary file test-data/pl.rank_genes_groups_stacked_violin.rank_genes_groups.krumsiek11.png has changed
Binary file test-data/pl.rank_genes_groups_tracksplot.newton-cg.pbmc68k_highly_reduced_marker_filtered_1.png has changed
Binary file test-data/pl.stacked_violin_pp.filter_genes_dispersion.krumsiek11-seurat.png has changed
Binary file test-data/pl.umap.neighbors_umap_euclidean.recipe_weinreb17.paul15_subsample.png has changed
Binary file test-data/tl.embedding_density.umap.neighbors_umap_euclidean.recipe_weinreb17.paul15_subsample.h5ad has changed
Binary file test-data/tl.leiden.neighbors_gauss_braycurtis.recipe_weinreb17.paul15_subsample.h5ad has changed
Binary file test-data/tl.louvain.neighbors_gauss_braycurtis.recipe_weinreb17.paul15_subsample.h5ad has changed