Mercurial > repos > iuc > baredsc_2d
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planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/baredsc commit 01d58fe886f6ab256b6eb8d4a65b978f81b81262
author | iuc |
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date | Fri, 01 Dec 2023 11:55:11 +0000 |
parents | aa4a6f0916b4 |
children | a90f8efe08b4 |
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<macros> <token name="@TOOL_VERSION@">1.1.2</token> <token name="@VERSION_SUFFIX@">1</token> <xml name="requirements"> <requirements> <requirement type="package" version="@TOOL_VERSION@">baredsc</requirement> <requirement type="package" version="1.12">gzip</requirement> </requirements> <version_command><![CDATA[baredSC_1d --version]]></version_command> </xml> <xml name="helpcitations"> <help><![CDATA[ .. class:: infomark **BARED (Bayesian Approach to Retreive Expression Distribution of) Single Cell** baredSC is a tool that uses a Monte-Carlo Markov Chain to estimate a confidence interval on the probability density function (PDF) of expression of one or two genes from single-cell RNA-seq data. It uses the raw counts and the total number of UMI for each cell. The PDF is approximated by a number of 1d or 2d gaussians provided by the user. The likelihood is estimated using the asumption that the raw counts follow a Poisson distribution of parameter equal to the proportion of mRNA for the gene in the cell multiplied by the total number of UMI identified in this cell. To get a description of outputs, please read the `Documentation <https://baredsc.readthedocs.io/en/latest/index.html>`_ This is a description of the figure with the results. - When the 1d version is used, it displays the mean PDF in solid red line, the median in black dashed lines (/!\backslash the integral of the median is not equal to 1) with the confidence interval of 1 sigma (68%), 2 sigma (95%) and 3 sigma (99.7%) as well as in green, the kernel density estimate of the input values, the detected expression (``log(1 + targetSum * raw / total UMI)``). - When the 2d version is used, it displays the PDF as a heatmap as well as a projection on the x and y axis. On the projection, the confidence interval 68% is indicated as a shaded area as well as the mean with a solid red line and the median with a dashed black line. On the top right corner, the correlation is indicated with the confidence interval 68% as well as a confidence interval on the one-sided p-value (the probability that the correlation is the opposite sign of the mean, one sigma confidence interval). Usually you should run baredSC_1d or baredSC_2d with 1 to 4 gaussians. Then you combine the different models with combineMultipleModels_1d or combineMultipleModels_2d. ]]></help> <citations> <citation type="doi">10.1186/s12859-021-04507-8</citation> </citations> </xml> <xml name="edam_topics"> <edam_topics> <edam_topic>topic_3170</edam_topic> <edam_topic>topic_4028</edam_topic> <edam_topic>topic_2269</edam_topic> </edam_topics> </xml> <xml name="macro_input_counts"> <conditional name="input_counts"> <param name="filetype" type="select" label="Input type"> <option value="tabular">Tabular</option> <option value="anndata">Anndata (for example from Scanpy)</option> </param> <when value="tabular"> <param argument="--input" type="data" format="tabular" label="Input table (with header)" help="Expected format is one line per cell, columns with raw counts and one column 'nCount_RNA' with the total number of UMI per cell (optionally other meta data to filter)" /> </when> <when value="anndata"> <param argument="--inputAnnData" type="data" format="h5ad" label="AnnData containing raw counts" /> </when> </conditional> </xml> <xml name="macro_single_gene"> <param argument="--geneColName" type="text" value="" label="Name of the column with gene counts."/> </xml> <xml name="macro_two_genes"> <param argument="--geneXColName" type="text" value="" label="Name of the column with gene counts for gene in x."/> <param argument="--geneYColName" type="text" value="" label="Name of the column with gene counts for gene in y."/> </xml> <xml name="macro_filter_cells"> <conditional name="filter"> <param name="nb" type="select" label="How many filters columns do you need?"> <option value="0">0 (keep all cells from file)</option> <option value="1">1</option> <option value="2">2</option> <option value="3">3</option> </param> <when value="0"/> <when value="1"> <param argument="--metadata1ColName" type="text" value="" label="Name of the column with first filter."/> <param argument="--metadata1Values" type="text" value="" label="Values accepted in this column (separated by comma)."/> </when> <when value="2"> <param argument="--metadata1ColName" type="text" value="" label="Name of the column with first filter."/> <param argument="--metadata1Values" type="text" value="" label="Values accepted in this column (separated by comma)."/> <param argument="--metadata2ColName" type="text" value="" label="Name of the column with second filter."/> <param argument="--metadata2Values" type="text" value="" label="Values accepted in this column (separated by comma)."/> </when> <when value="3"> <param argument="--metadata1ColName" type="text" value="" label="Name of the column with first filter."/> <param argument="--metadata1Values" type="text" value="" label="Values accepted in this column (separated by comma)."/> <param argument="--metadata2ColName" type="text" value="" label="Name of the column with second filter."/> <param argument="--metadata2Values" type="text" value="" label="Values accepted in this column (separated by comma)."/> <param argument="--metadata3ColName" type="text" value="" label="Name of the column with third filter."/> <param argument="--metadata3Values" type="text" value="" label="Values accepted in this column (separated by comma)."/> </when> </conditional> </xml> <xml name="macro_MCMC_params_common_axis" token_axis="x"> <param argument="--@AXIS@min" type="float" value="0" label="Minimum value to consider in @AXIS@ axis." help="Choose value small enough to go below smallest value."/> <param argument="--@AXIS@max" type="float" value="2.5" label="Maximum value to consider in @AXIS@ axis." help="Choose value large enough to go above largest value."/> <param argument="--n@AXIS@" type="integer" min="1" value="100" label="Number of values in @AXIS@ to check how your evaluated PDF is compatible with the model." help="Larger values will increase computing time while smaller values will decrease the resolution of your PDF." /> <param argument="--minScale@AXIS@" type="float" value="0.1" label="Minimal value of the scale of Gaussians on @AXIS@" help="Cannot be smaller than max of twice the bin size of PDF evaluation and half the bin size on @AXIS@ axis."/> </xml> <xml name="macro_scale_seed"> <conditional name="scale"> <param name="type" type="select" label="Scale for gene expression"> <option value="Seurat">Like in Seurat (log(1+targetSum*X))</option> <option value="log">simply log</option> </param> <when value="Seurat"> <param argument="--targetSum" type="float" value="10000" label="targetSum" help="use 0 for the median of nRNA_Counts"/> </when> <when value="log"/> </conditional> <param argument="--seed" type="integer" value="1" label="Seed value to control randomness." help="Change seed value to get new result"/> </xml> <xml name="macro_MCMC_common_baredSC"> <param argument="--nnorm" type="integer" min="1" value="2" label="Number of Gaussians to fit." /> <param argument="--nsampMCMC" type="integer" min="1" value="100000" label="Number of samplings (iterations) of MCMC." /> <conditional name="automaticRestart"> <param name="set_minNeff" type="select" label="Auto-rerun in case of obvious non-convergence"> <option value="yes">Yes (the job may never stop)</option> <option value="no">No</option> </param> <when value="yes"> <param argument="--minNeff" type="float" value="200" label="Minimum number of effective samples to output result." help="If the number of effective samples is below this threshold, the MCMC is automatically rerun with 10 times more samples"/> </when> <when value="no"/> </conditional> </xml> <xml name="combine_outputs" token_d="1"> <param argument="--outputs" type="data" format="npz" label="Numpy archives from baredSC_@D@d with different number of Gaussians." multiple="true"/> </xml> <xml name="macro_plots"> <param name="image_file_format" type="select" label="Image output format"> <option value="png">png</option> <option value="svg">svg</option> <option value="pdf">pdf</option> </param> <param argument="--title" type="text" value="" label="Title to set to all figures."/> <param argument="--removeFirstSamples" type="integer" value="-1" label="Number of samples to ignore before making the plots" help="Use -1 to use a fourth of the number of samples"/> <param argument="--nsampInPlot" type="integer" value="100000" min="1" label="Approximate number of samples to use in plots"/> </xml> <xml name="macro_prettybins_1d"> <param argument="--prettyBins" type="integer" value="-1" min="-1" label="Number of bins to use in plots." help="Use -1 to use the number of bins used in MCMC"/> </xml> <xml name="macro_prettybins_axis" token_axis="x"> <param argument="--prettyBins@AXIS@" type="integer" value="-1" min="-1" label="Number of bins to use in @AXIS@ in plots." help="Use -1 to use the number of bins used in MCMC"/> </xml> <xml name="macro_splity"> <param argument="--splity" type="text" value="" label="Threshold values separated by space to plot the density for genex for 2 categories in geney values" help="Leave empty if you don't need this type of analysis."> <validator type="regex">(-?[0-9]+( -?[0-9]+)*)?</validator> </param> </xml> <xml name="macro_colorscale"> <param argument="--log1pColorScale" type="boolean" truevalue="--log1pColorScale" falsevalue="" checked="false" label="Enable to see regions in plot with low proportion of cells"/> </xml> <xml name="macro_advanced_common_axis" token_axis="x" token_default_osamppdf="5"> <param argument="--osamp@AXIS@" type="integer" min="1" value="10" label="Oversampling factor of @AXIS@ values when evaluating PDF of Poisson distribution." /> <param argument="--osamp@AXIS@pdf" type="integer" value="@DEFAULT_OSAMPPDF@" label="Oversampling factor of @AXIS@ values when evaluating PDF at each step of the MCMC."/> </xml> <xml name="macro_advanced_evidence"> <param argument="--coviscale" type="float" value="1" label="Scale factor to apply to covariance of parameters to get random parameters in logevidence evaluation." /> <param argument="--nis" type="integer" value="1000" label="Size of sampling of random parameters in logevidence evaluation." /> </xml> <xml name="macro_advanced_common_baredSC"> <conditional name="burn"> <param name="custom" type="select" label="Custom parameters of the burning phase of MCMC"> <option value="no">No</option> <option value="yes">Yes</option> </param> <when value="no"/> <when value="yes"> <param argument="--nsampBurnMCMC" type="integer" value="-1" label="Number of samplings (iterations) in the burning phase of mcmc (Set -1 for a fourth of total number of samples)" /> <param argument="--T0BurnMCMC" type="float" value="100" label="Initial temperature in the burning phase of MCMC" min="1"/> </when> </conditional> </xml> <xml name="macro_scaleprior"> <param argument="--scalePrior" type="float" value="0.3" label="Scale of the truncnorm used in the prior for the correlation."/> </xml> <token name="@REQUIRED_INPUTS_1D@" ><![CDATA[ #if str( $input_counts.filetype ) == "tabular": --input '$input_counts.input' #elif str( $input_counts.filetype ) == "anndata": --inputAnnData '$input_counts.inputAnnData' #end if --geneColName '$geneColName' ]]></token> <token name="@REQUIRED_INPUTS_2D@" ><![CDATA[ #if str( $input_counts.filetype ) == "tabular": --input '$input_counts.input' #elif str( $input_counts.filetype ) == "anndata": --inputAnnData '$input_counts.inputAnnData' #end if --geneXColName '$geneXColName' --geneYColName '$geneYColName' ]]></token> <token name="@FILTER_CELLS@" ><![CDATA[ #if str( $filter.nb ) == "1": --metadata1ColName '$filter.metadata1ColName' --metadata1Values '$filter.metadata1Values' #elif str( $filter.nb ) == "2": --metadata1ColName '$filter.metadata1ColName' --metadata1Values '$filter.metadata1Values' --metadata2ColName '$filter.metadata2ColName' --metadata2Values '$filter.metadata2Values' #elif str( $filter.nb ) == "3": --metadata1ColName '$filter.metadata1ColName' --metadata1Values '$filter.metadata1Values' --metadata2ColName '$filter.metadata2ColName' --metadata2Values '$filter.metadata2Values' --metadata3ColName '$filter.metadata3ColName' --metadata3Values '$filter.metadata3Values' #end if ]]></token> <token name="@MCMC_1D@" ><![CDATA[ --xmin $MCMC.xmin --xmax $MCMC.xmax --xscale '$MCMC.scale.type' #if str( $MCMC.scale.type ) == "Seurat": --targetSum $MCMC.scale.targetSum #end if --nx $MCMC.nx --minScale $MCMC.minScalex --seed $MCMC.seed ]]></token> <token name="@MCMC_2D@" ><![CDATA[ --xmin $MCMC.xmin --xmax $MCMC.xmax --nx $MCMC.nx --minScalex $MCMC.minScalex --ymin $MCMC.ymin --ymax $MCMC.ymax --ny $MCMC.ny --minScaley $MCMC.minScaley --scale '$MCMC.scale.type' #if str( $MCMC.scale.type ) == "Seurat": --targetSum $MCMC.scale.targetSum #end if --seed $MCMC.seed ]]></token> <token name="@BAREDSC_COMMON@" ><![CDATA[ --nnorm $MCMC.nnorm --nsampMCMC $MCMC.nsampMCMC #if str( $MCMC.automaticRestart.set_minNeff ) == "yes": --minNeff $MCMC.automaticRestart.minNeff #end if ]]></token> <token name="@PLOTS@" ><![CDATA[ #if str( $plots.title ) != '': --title '$plots.title' #end if #if $plots.removeFirstSamples != -1: --removeFirstSamples $plots.removeFirstSamples #end if --nsampInPlot $plots.nsampInPlot ]]></token> <token name="@PRETTYBINS_1D@" ><![CDATA[ #if $plots.prettyBins != -1: --prettyBins $plots.prettyBins #end if ]]></token> <token name="@PRETTYBINS_SPLITY_COLORSCALE_2D@" ><![CDATA[ #if $plots.prettyBinsx != -1: --prettyBinsx $plots.prettyBinsx #end if #if $plots.prettyBinsy != -1: --prettyBinsy $plots.prettyBinsy #end if ## splity is space separated floats #if str($plots.splity) != '': --splity $plots.splity #end if #if str($plots.log1pColorScale) != '': '$plots.log1pColorScale' #end if ]]></token> <token name="@ADVANCED_COMMON_X@" ><![CDATA[ --osampx $advanced.osampx --osampxpdf $advanced.osampxpdf --coviscale $advanced.coviscale --nis $advanced.nis ]]></token> <token name="@ADVANCED_COMMON_COMPLEMENT_2D@" ><![CDATA[ --osampy $advanced.osampy --osampypdf $advanced.osampypdf --scalePrior $advanced.scalePrior ]]></token> <token name="@ADVANCED_BAREDSC_COMMON@" ><![CDATA[ #if str( $advanced.burn.custom ) == "yes": #if str( $advanced.burn.nsampBurnMCMC ) != "-1": --nsampBurnMCMC $advanced.burn.nsampBurnMCMC #end if --T0BurnMCMC $advanced.burn.T0BurnMCMC #end if ]]></token> <token name="@COMBINE_OUTPUTS@"><![CDATA[ --outputs #for $i, $output in enumerate($MCMC.outputs): $i #end for ]]></token> <token name="@ORDER_OUTPUTS_1D@"><![CDATA[ mv baredSC_pdf.txt output && mv baredSC.$plots.image_file_format baredSC && gunzip baredSC_means.txt.gz ]]></token> <token name="@ORDER_OUTPUTS_2D@"><![CDATA[ mv baredSC_pdf2d.txt output && mv baredSC_pdf2d_flat.txt output && mv baredSC.$plots.image_file_format baredSC #if str($plots.splity) != '': #for $value in str($plots.splity).split(' '): && mv baredSC_split'$value'.txt baredSC_split'$value'_pdf.txt #end for #end if ]]></token> </macros>