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planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/ampvis2 commit 9fe04d29ea604a152144908dbd20c0754695a025
author | iuc |
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date | Sat, 16 Nov 2024 19:58:32 +0000 |
parents | 14695ae019be |
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<tool id="ampvis2_heatmap" name="ampvis2 heatmap" version="@TOOL_VERSION@+galaxy1" profile="@PROFILE@" license="MIT"> <description></description> <macros> <import>macros.xml</import> </macros> <expand macro="header"/> <command detect_errors="exit_code"><![CDATA[ Rscript '$rscript' ]]></command> <configfiles> <configfile name="rscript"><![CDATA[ #if $tax_add #set ta='c("' + '", "'.join(str($tax_add).split(",")) + '")' #else #set ta='NULL' #end if library(ampvis2, quietly = TRUE) d <- readRDS("$data") #if $output_options.out_format == "tabular" raw <- #else plot <- #end if amp_heatmap( d , #if $group_by group_by = "$group_by", #end if #if $facet_by facet_by = "$facet_by", #end if normalise = $normalise, tax_aggregate = "$tax_aggregate", tax_add = $ta, @TAX_SHOW@ showRemainingTaxa = $showRemainingTaxa, ## tax_class = NULL, tax_empty = "$tax_empty", ## TODO giving the order of the columns is difficult but "cluster" would be nice I guess ## order_x_by = NULL, ## order_y_by = NULL, plot_values = $plot_values_cond.plot_values, #if $plot_values_cond.plot_values == "TRUE" plot_values_size = $plot_values_cond.plot_values_size, #end if ## plot_legendbreaks = NULL, plot_colorscale = "$plot_colorscale", plot_na = $plot_na, measure = "$measure", #if str($min_abundance) != '' min_abundance = $min_abundance, #end if #if str($max_abundance) != '' max_abundance = $max_abundance, #end if #if $sort_by_cond.sort_by_sel != 'no' sort_by = "$sort_by_cond.sort_by", #end if #if $normalise_by normalise_by = "$normalise_by", #end if #if $scale_by scale_by = "$scale_by", #end if color_vector = c("$color_palette_start", "$color_palette_end"), ## round = 1, #if $output_options.out_format == "tabular" textmap = TRUE, #else textmap = FALSE, #end if #if $plot_functions_cond.plot_functions_sel != "no" plot_functions = TRUE, #if $plot_functions_cond.plot_functions_sel == "file" function_data = read.table("$plot_functions_cond.function_data", header = TRUE, sep = "\t"), #end if #set foo='c("' + '", "'.join(str($plot_functions_cond.functions).split(",")) + '")' functions = $foo, #end if rel_widths = c(0.75, 0.25) ) #if $output_options.out_format != "tabular" @OUTPUT_TOKEN@ #else write.table(raw, file = "$plot_raw", sep = "\t") #end if ]]></configfile> </configfiles> <inputs> <expand macro="rds_metadata_input_macro"/> <expand macro="metadata_select_discrete" argument="group_by" label="Group samples" help="By a categorical variable in the metadata"/> <expand macro="metadata_select_discrete" argument="facet_by" label="Facet the samples" help="By a categorical variable in the metadata."/> <expand macro="normalise_macro" checked="true"/> <expand macro="taxlevel_macro" argument="tax_aggregate" label="The taxonomic level to aggregate the OTUs"> <option value="Phylum" selected="true">Phylum</option> </expand> <expand macro="taxlevel_macro" argument="tax_add" multiple="true" optional="true" label="Additional taxonomic level(s) to display"/> <expand macro="tax_show_macro" value="10"/> <param argument="showRemainingTaxa" type="boolean" truevalue="TRUE" falsevalue="FALSE" label="Display sum of remaining taxa" help="Add an additional row at the bottom displaying the sum of all remaining taxa that are not part of the top tax_show most abundant taxa."/> <expand macro="tax_empty_macro"/> <conditional name="plot_values_cond"> <param argument="plot_values" type="select" label="Plot the values on the heatmap"> <option value="TRUE">Yes</option> <option value="FALSE">No</option> </param> <when value="TRUE"> <param name="plot_values_size" type="integer" value="4" label="Size of the plotted values"/> </when> <when value="FALSE"/> </conditional> <param argument="plot_colorscale" type="select" label="Type of scale used for coloring abundances"> <option value="sqrt">Square root (sqrt)</option> <option value="log10" selected="true">Log (log10)</option> </param> <param argument="plot_na" type="boolean" truevalue="TRUE" falsevalue="FALSE" label="Color missing values with the lowest color in the scale"/> <param argument="measure" type="select" label="Value to show across the groups"> <option value="mean">Mean</option> <option value="max">Maximum</option> <option value="median">Median</option> </param> <param argument="min_abundance" type="float" value="0.1" min="0" optional="true" label="Maximum abundance" help="All values below this value are given the same color."/> <param argument="max_abundance" type="float" value="" min="0" optional="true" label="Maximum abundance" help="All values above this value are given the same color." /> <conditional name="sort_by_cond"> <param name="sort_by_sel" type="select" label="Sort heatmap by most abundant taxa"> <option value="no">No</option> <option value="group">in a group of samples</option> <option value="sample">in a specific sample</option> </param> <when value="no"/> <when value="group"> <param argument="sort_by" type="select" optional="true" label="Group to sort by"> <options from_dataset="metadata_list"> <column name="name" index="1"/> <column name="value" index="1"/> <filter type="param_value" column="0" ref="group_by"/> <filter type="unique_value" column="1"/> </options> </param> </when> <when value="sample"> <param argument="sort_by" type="select" optional="true" label="Sample to sort by"> <options from_dataset="metadata_list"> <column name="name" index="1"/> <column name="value" index="1"/> <filter type="static_value" value="TRUE" column="2"/> <!-- filter samples --> <filter type="unique_value" column="1"/> </options> </param> </when> </conditional> <param argument="color_palette_start" type="color" label="Start color for the heatmap" help="Choose the start color for the heatmap."/> <param argument="color_palette_end" type="color" label="End color for the heatmap" help="Choose the end color for the heatmap."/> <!-- https://github.com/KasperSkytte/ampvis2/issues/168 if this is possible again reuse: metadata_sample_or_variable_select ? --> <expand macro="metadata_sample_select" argument="normalise_by" label="Normalize counts by a variable or a specific sample"/> <expand macro="metadata_select_discrete" argument="scale_by" label="Scale the abundances by a variable in the metadata"/> <conditional name="plot_functions_cond"> <param name="plot_functions_sel" type="select" label="Show functional information about the Genus-level OTUs" help="Produces a 2-column grid plot, showing known functional information about the Genus-level OTUs next to the heatmap. When using this feature, make sure that either tax_aggregate or tax_add is set to Genus and that Genus is the lowest level in either."> <option value="no">No</option> <option value="midasfieldguide">Use data from midasfieldguide.org</option> <option value="file">Use data from a dataset in the history</option> </param> <when value="no"/> <when value="file"> <!-- neeed tsv here since tabular does not fill the column_names metadata and therefore the data_meta filter in the functions select would not work--> <param argument="function_data" type="data" format="tsv" label="Tabular dataset with functional information at Genus level" help="See help"/> <param argument="functions" type="select" multiple="true" label="Function(s) to include"> <options> <filter type="data_meta" ref="function_data" key="column_names"/> <filter type="remove_value" value="Genus"/> </options> </param> </when> <when value="midasfieldguide"> <param name="functions" type="select" multiple="true" label="Function(s) to include"> <option value="MiDAS" selected="true">MiDAS</option> <option value="Filamentous" selected="true">Filamentous</option> <option value="AOB" selected="true">AOB</option> <option value="NOB" selected="true">PAO</option> <option value="GAO" selected="true">GAO</option> </param> </when> </conditional> <expand macro="out_format_macro"> <option value="tabular">Table</option> </expand> </inputs> <outputs> <expand macro="out_macro"> <filter>output_options["out_format"] != "tabular"</filter> </expand> <data name="plot_raw" format="tabular" label="${tool.name} on ${on_string}: Table"> <filter>output_options["out_format"] == "tabular"</filter> </data> </outputs> <tests> <!-- defaults --> <test expect_num_outputs="1"> <param name="data" value="AalborgWWTPs.rds" ftype="ampvis2"/> <output name="plot" value="AalborgWWTPs-heatmap.pdf" ftype="pdf" compare="sim_size"/> </test> <!-- group and facet--> <test expect_num_outputs="1"> <param name="data" value="AalborgWWTPs.rds" ftype="ampvis2"/> <param name="metadata_list" value="AalborgWWTPs-metadata.list"/> <param name="group_by" value="Plant"/> <param name="facet_by" value="Year"/> <output name="plot_raw" value="AalborgWWTPs-heatmap-group-facet.pdf" ftype="pdf" compare="sim_size"/> </test> <!-- group and facet and test raw output --> <test expect_num_outputs="1"> <param name="data" value="AalborgWWTPs.rds" ftype="ampvis2"/> <param name="metadata_list" value="AalborgWWTPs-metadata.list"/> <param name="group_by" value="Plant"/> <param name="facet_by" value="Year"/> <param name="out_format" value="tabular"/> <output name="plot_raw" value="AalborgWWTPs-heatmap-group-facet.tsv" ftype="tabular"/> </test> <!-- normalise --> <test expect_num_outputs="1"> <param name="data" value="AalborgWWTPs.rds" ftype="ampvis2"/> <param name="normalise" value="true"/> <output name="plot" value="AalborgWWTPs-heatmap-normalise.pdf" ftype="pdf" compare="sim_size"/> </test> <!-- normalise by a specific sample --> <test expect_num_outputs="1"> <param name="data" value="AalborgWWTPs.rds" ftype="ampvis2"/> <param name="metadata_list" value="AalborgWWTPs-metadata.list"/> <param name="normalise" value="true"/> <param name="normalise_by" value="16SAMP-747"/> <output name="plot" value="AalborgWWTPs-heatmap-normalise_by_sample.pdf" ftype="pdf" compare="sim_size"/> </test> <!-- normalise by a metadata variable https://github.com/KasperSkytte/ampvis2/issues/168 --> <!-- <test expect_num_outputs="1"> <param name="data" value="AalborgWWTPs.rds" ftype="ampvis2"/> <param name="metadata_list" value="AalborgWWTPs-metadata.list"/> <param name="group_by" value="Plant"/> <conditional name="normalise_by_cond"> <param name="normalise_by_sel" value="variable"/> <param name="normalise_by" value="Plant"/> </conditional> <output name="plot" value="AalborgWWTPs-heatmap-normalise_by_variable.pdf" ftype="pdf"/> </test> --> <!-- tax options --> <test expect_num_outputs="1"> <param name="data" value="AalborgWWTPs.rds" ftype="ampvis2"/> <param name="tax_aggregate" value="Order"/> <param name="tax_add" value="Class"/> <param name="tax_show" value="5"/> <param name="showRemainingTaxa" value="true"/> <output name="plot" value="AalborgWWTPs-heatmap-tax.pdf" ftype="pdf" compare="sim_size"/> </test> <!-- sort by a specific sample --> <test expect_num_outputs="1"> <param name="data" value="AalborgWWTPs.rds" ftype="ampvis2"/> <param name="metadata_list" value="AalborgWWTPs-metadata.list"/> <conditional name="sort_by_cond"> <param name="sort_by_sel" value="sample"/> <param name="sort_by" value="16SAMP-747"/> </conditional> <output name="plot" value="AalborgWWTPs-heatmap-sort_by_sample.pdf" ftype="pdf" compare="sim_size"/> </test> <!-- sort by a group of samples --> <test expect_num_outputs="1"> <param name="data" value="AalborgWWTPs.rds" ftype="ampvis2"/> <param name="metadata_list" value="AalborgWWTPs-metadata.list"/> <param name="group_by" value="Period"/> <conditional name="sort_by_cond"> <param name="sort_by_sel" value="group"/> <param name="sort_by" value="Winter"/> </conditional> <output name="plot" value="AalborgWWTPs-heatmap-sort_by_group.pdf" ftype="pdf" compare="sim_size"/> </test> <test expect_num_outputs="1"> <param name="data" value="AalborgWWTPs.rds" ftype="ampvis2"/> <param name="tax_aggregate" value="Genus"/> <conditional name="plot_functions_cond"> <param name="plot_functions_sel" value="midasfieldguide"/> <param name="functions" value="MiDAS,Filamentous,AOB,NOB,GAO"/> </conditional> <output name="plot" value="AalborgWWTPs-heatmap-plot_foo_midas.pdf" ftype="pdf" compare="sim_size"/> </test> <test expect_num_outputs="1"> <param name="data" value="AalborgWWTPs.rds" ftype="ampvis2"/> <param name="tax_aggregate" value="Genus"/> <conditional name="plot_functions_cond"> <param name="plot_functions_sel" value="file"/> <param name="function_data" value="AalborgWWTPs-functions.tsv" ftype="tsv"/> <param name="functions" value="Foo,Bar"/> </conditional> <output name="plot" value="AalborgWWTPs-heatmap-plot_foo_file.pdf" ftype="pdf" compare="sim_size"/> </test> <!-- test with different color palettes --> <test expect_num_outputs="1"> <param name="data" value="AalborgWWTPs.rds" ftype="ampvis2"/> <param name="color_palette_start" value="red"/> <param name="color_palette_end" value="yellow"/> <output name="plot" value="AalborgWWTPs-heatmap-red-yellow.pdf" ftype="pdf" compare="sim_size"/> </test> <test expect_num_outputs="1"> <param name="data" value="AalborgWWTPs.rds" ftype="ampvis2"/> <param name="color_palette_start" value="blue"/> <param name="color_palette_end" value="green"/> <output name="plot" value="AalborgWWTPs-heatmap-blue-green.pdf" ftype="pdf" compare="sim_size"/> </test> </tests> <help><![CDATA[ What it does ============ Generates a heatmap of amplicon data by using sample metadata to aggregate samples and taxonomy to aggregate OTUs. The Galaxy tool calls the `amp_heatmap <https://kasperskytte.github.io/ampvis2/reference/amp_heatmap.html>`_ function of the ampvis2 package. @HELP_RELATIVE_ABUNDANCES@ Input ===== @HELP_RDS_INPUT@ @HELP_METADATA_LIST_INPUT@ Funtional data at genus level can be added to the plot. By default the information is taken from `midasfieldguide <https://midasfieldguide.org/>`_ but it can also be given by a dataset (parameter function_data): - The first column must be the Genus names and - any other column(s) can be any property or metabolic function of the individual Genera. Output ====== Heatmap in the chosen output format. If table output is chosen the data presented in the heatmap is written into a tabular dataset. ]]></help> <expand macro="citations"/> </tool>