Mercurial > repos > iuc > raceid_inspectclusters
view macros_cluster.xml @ 1:64c5c1bbbdbe draft
planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/raceid3 commit 71e6b205841c83391ea8fc69e10eac03f212f4d6
author | iuc |
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date | Thu, 28 Feb 2019 13:00:52 -0500 |
parents | 9fec5dd8fbb9 |
children | 0fa80752a314 |
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<macros> <macro name="cluster_inputs" > <param name="intable" type="data" format="tabular" label="Count Matrix" /> <section name="filt" title="Filtering" expanded="true" > <param name="mintotal" type="integer" min="1" value="3000" label="Min Transcripts" help="The minimum total transcripts required. Cells with less than mintotal transcripts are filtered out." /> <param name="minexpr" type="integer" min="1" value="5" label="Min Expression" help="The minimum required transcript counts of a gene in the minimum number of cells (below)" /> <param name="minnumber" type="integer" min="1" value="5" label="Min Cells" help="The minumum number of cells for gene expression to be counted" /> <expand macro="use_defaults_no" > <param name="knn" type="integer" min="0" value="10" label="K-nearest-neighbours" help="Number of nearest neighbors used to infer corresponding cell types in different batches" /> <param name="CGenes" type="text" optional="true" label="CGenes" help="Filter out genes with correlated expression for cell type inference" > <expand macro="sanitize_string_vector" /> </param> <param name="FGenes" type="text" optional="true" label="FGenes" help="Explicitly filter out genes for cell type inference" > <expand macro="sanitize_string_vector" /> </param> <param name="LBatch_regexes" type="text" optional="true" label="Batch Regex" help="List of regexes to capture experimental batches for batch effect correction" > <expand macro="sanitize_string_vector" /> </param> <param name="ccor" type="float" value="0.4" label="CCor" help="Correlation coefficient used as a threshold for determining correlated genes" /> <param name="bmode" type="select" label="Batch Mode" help="Method to regress out batch effects" > <option value="RaceID" selected="true" >RaceID</option> <option value="scran">SCRAN</option> </param> <conditional name="ccc" > <param name="use" type="select" label="Perform Cell-cycle correction?" > <option value="yes" >Yes</option> <option value="no" selected="true" >No</option> </param> <when value="no" /> <when value="yes" > <param name="vset" type="text" optional="true" label="List of Gene Sets" > <expand macro="sanitize_string_vector" /> </param> <param name="pvalue" type="float" value="0.01" min="0" max="1" label="P-value Cutoff" help="P-value cutoff for determining enriched components" /> <param name="quant" type="float" value="0.01" min="0" max="1" label="Quantification Fraction" help="Upper and lower fraction of gene loadings use for determining enriched components" /> <param name="ncomp" type="integer" min="0" optional="true" label="Number of components to use" help="If left blank, the maximum number of components are used" /><!-- 0 = NULL --> <param name="dimr" type="boolean" value="true" label="Derive Components from saturation criterion" /> <param name="mode" type="select" label="Type of Component Analysis" help="If ICA is selected, ensure that the number of components value above is sufficiently high" > <option value="pca" selected="true">PCA</option> <option value="ica">ICA</option> </param> <param name="logscale" type="boolean" value="false" label="Log-transform data prior to PCA or ICA" help="" /> </when> </conditional> </expand> </section> <section name="clust" title="Clustering" expanded="true" > <!-- CompDist --> <param name="metric" type="select" label="Distance Metric" > <option value="pearson" selected="true" >Pearson</option> <option value="spearman">Spearman</option> <option value="logpearson">Log Pearson</option> <option value="euclidean">Euclidean</option> </param> <!-- ClustExp --> <param name="funcluster" type="select" label="Clustering method" > <option value="kmedoids" selected="true" >K-medoids</option> <option value="kmeans">K-means</option> <option value="hclust">H-Clust</option> </param> <expand macro="use_defaults_no" > <!-- CompDist --> <param name="fselect" type="boolean" value="true" label="Perform feature selection" /> <param name="knn" type="integer" min="0" optional="true" label="KNN" help="Number of nearest neighbours for imputing gene expression" /><!-- 0: NULL --> <!-- ClustExp --> <param name="sat" type="boolean" checked="true" label="Saturation-based clustering?" help="Determine number of clusters on saturation point of the mean within-cluster dispersion as a function of the cluster number." /> <param name="clustnr" type="integer" min="0" value="30" label="Max number of clusters using Saturation-by-mean" help="Max number of clusters for the derivation of the cluster number by the saturation of mean within-cluster-dispersion." /> <param name="samp" type="integer" min="0" optional="true" label="Sample random number of cells" help="Number of random sample of cells used for the inference of cluster number and Jaccard similarity" /><!-- 0:NULL --> <param name="cln" type="integer" min="0" optional="true" label="Number of clusters" /><!-- 0:Null --> <param name="bootnr" type="integer" min="0" value="50" label="Number of booststrapping runs" /> <param name="rseed" type="integer" value="17000" label="Random seed" /> </expand> </section> <section name="outlier" title="Outliers" expanded="true" > <!-- Find Outliers --> <param name="outminc" type="integer" min="0" value="5" label="Minimum Transcripts" help="minimal transcript count of a gene in a clusters to be tested for being an outlier gene" /> <param name="outlg" type="integer" min="1" value="2" label="Minimum Genes" help="Minimum number of outlier genes required for being an outlier cell" /> <!-- RFCorrect --> <param name="final" type="boolean" value="true" label="Plot Final Clusters?" help="Reclassification of cell types using out-of-bag analysis is performed based on the final clusters after outlier identification. If 'FALSE', then the cluster partition prior to outlier identification is used for reclassification." /> <expand macro="use_defaults_no" > <!-- Find Outliers --> <param name="probthr" type="float" min="0" value="0.001" label="Outlier Probability Threshold" help="Probability threshold for the above specified minimum number of genes to be an outlier cell. This probability is computed from a negative binomial background model of expression in a cluster" /> <param name="outdistquant" type="float" min="0" max="1" value="0.95" label="Outlier Distance Quantile" help="Outlier cells are merged to outlier clusters if their distance smaller than the outdistquant-quantile of the distance distribution of pairs of cells in the orginal clusters after outlier removal" /> <!-- RFCorrect --> <param name="nbtree" type="integer" optional="true" label="Number of trees to be built" /><!-- 0:Null --> <param name="nbfactor" type="integer" min="0" value="5" label="Tree Factor" help="Number of trees based on the number of cells multiplied by this factor. Effective only if the number of trees parameter is set to 0" /> <param name="rfseed" type="integer" value="12345" label="Random Seed" /> </expand> </section> <section name="tsne" title="tSNE and FR" expanded="true" > <!-- CompTSNE --> <param name="perplexity" type="integer" min="0" value="30" label="Perplexity" help="Perplexity of the t-SNE map" /> <!-- CompFR --> <param name="knn" type="integer" min="0" value="10" label="KNN" help="Number of nearest neighbours used for the inference of the Fruchterman-Rheingold layout" /> <expand macro="use_defaults_no" > <!-- CompTSNE --> <param name="initial_cmd" type="boolean" checked="true" label="tSNE map initialised by classical multidimensional scaling" /> <param name="rseed_tsne" type="integer" value="15555" label="Random Seed (tSNE)" /> <!-- CompFR --> <param name="rseed_fr" type="integer" min="0" value="15555" label="Random Seed (FR)" /> </expand> </section> <section name="extra" title="Extra Parameters" expanded="false" > <param name="tablelim" type="integer" min="1" value="25" label="Table Limit" help="Top N genes to print per cluster" /> <param name="plotlim" type="integer" min="1" value="10" label="Plot Limit" help="Top N genes to plot. Must be less than or equal to the Table Limit" /> <param name="foldchange" type="float" min="0" value="1" label="Fold change" /> <param name="pvalue" type="float" min="0" max="1" value="0.01" label="P-value Cutoff" help="P-value cutoff for the inference of differential gene expression" /> </section> </macro> <macro name="cluster_tests" > <test> <!-- default test --> <conditional name="tool" > <param name="mode" value="cluster" /> <!-- This is a file with a single word 'test', which prompts the scripts to use the test intestinalData in the library --> <param name="intable" value="use.intestinal" /> </conditional> <output name="outgenelist" value="intestinal.genelist" /> <output name="outpdf" value="intestinal.pdf" compare="sim_size" delta="50" /> </test> <test> <!-- defaults, feeding in a matrix with reduced filtering --> <conditional name="tool" > <param name="mode" value="cluster" /> <param name="intable" value="matrix.tabular" /> <section name="filt" > <param name="mintotal" value="1000" /> <param name="minexpr" value="1" /> <param name="minnumber" value="3" /> </section> <param name="use_log" value="true" /> <output name="outgenelist" value="matrix.genelist" /> <output name="outrdat" value="matrix.rdat" compare="sim_size" delta="15" /> <output name="outpdf" value="matrix.pdf" compare="sim_size" delta="10" /> <output name="outlog" value="matrix.log" /> </conditional> </test> <test> <!-- defaults, but manually specified. No opts, no CC. Generates identical to above --> <conditional name="tool" > <param name="mode" value="cluster" /> <param name="intable" value="use.intestinal" /> <section name="filt" > <param name="mintotal" value="3000" /> <param name="minexpr" value="5" /> <param name="minnumber" value="5" /> <expand macro="test_nondef" > <param name="knn" value="10" /> <param name="ccor" value="0.4" /> <param name="bmode" value="RaceID" /> </expand> </section> <section name="clust" > <param name="metric" value="pearson" /> <param name="funcluster" value="kmedoids" /> <expand macro="test_nondef" > <param name="fselect" value="true" /> <param name="sat" value="true" /> <param name="clustnr" value="30" /> <param name="bootnr" value="50" /> <param name="rseed" value="17000" /> </expand> </section> <section name="outlier" > <param name="outminc" value="5" /> <param name="outlg" value="2" /> <param name="final" value="false" /> <expand macro="test_nondef" section_name="outlier" > <param name="probthr" value="0.001" /> <param name="outdistquant" value="0.95" /> <param name="rfseed" value="12345" /> <param name="nbfactor" value="5" /> </expand> </section> <section name="tsne" > <param name="perplexity" value="30" /> <param name="knn" value="10" /> <expand macro="test_nondef" section_name="tsne" > <param name="initial_cmd" value="true" /> <param name="rseed_tsne" value="15555" /> <param name="rfseed_fr" value="15555" /> </expand> </section> </conditional> <output name="outgenelist" value="intestinal.genelist" /> <output name="outpdf" value="intestinal.pdf" compare="sim_size" delta="50" /> </test> <test> <!-- Advanced. Opts, CC used --> <conditional name="tool" > <param name="mode" value="cluster" /> <param name="intable" value="use.intestinal" /> <section name="filt" > <param name="mintotal" value="2000" /> <param name="minexpr" value="3" /> <param name="minnumber" value="2" /> <expand macro="test_nondef" > <param name="knn" value="5" /> <param name="ccor" value="0.5" /> <param name="CGenes" value="Gga3,Ggact,Ggct" /> <param name="FGenes" value="Zxdc,Zyg11a,Zyg11b,Zyx" /> <param name="LBatch_regexes" value="^I5,^II5,^III5,^IV5d,^V5d" /> <param name="bmode" value="scran" /> <conditional name="ccc" > <param name="use" value="yes" /> <param name="pvalue" value="0.05" /> <param name="quant" value="0.05" /> <param name="ncomp" value="3" /> <param name="dimr" value="true" /> <param name="mode" value="pca" /> <param name="logscale" value="true" /> </conditional> </expand> </section> <section name="clust" > <param name="metric" value="euclidean" /> <param name="funcluster" value="hclust" /> <expand macro="test_nondef" > <param name="fselect" value="false" /> <param name="knn" value="5" /> <param name="sat" value="false" /> <param name="samp" value="10" /> <param name="cln" value="10" /> <param name="clustnr" value="10" /> <param name="bootnr" value="30" /> <param name="rseed" value="17000" /> </expand> </section> <section name="outlier" > <param name="outminc" value="3" /> <param name="outlg" value="5" /> <param name="final" value="true" /> <expand macro="test_nondef" > <param name="probthr" value="0.01" /> <param name="outdistquant" value="0.5" /> <param name="rfseed" value="12345" /> <param name="nbfactor" value="5" /> <param name="nbtree" value="10" /> </expand> </section> <section name="tsne" > <param name="perplexity" value="20" /> <param name="knn" value="6" /> <expand macro="test_nondef" > <param name="initial_cmd" value="false" /> <param name="rseed_tsne" value="15555" /> <param name="rfseed_fr" value="15555" /> </expand> </section> </conditional> <output name="outgenelist" value="intestinal_advanced.genelist" /> <output name="outpdf" value="intestinal_advanced.pdf" compare="sim_size" delta="150" /> </test> </macro> <token name="@FILTNORM_CHEETAH@"><![CDATA[ ## Perform do.filter use.filtnormconf = TRUE ## Perform do.cluster, do.outlier, do.clustmap, mkgenelist use.cluster = FALSE in.table = read.table( '${intable}', stringsAsFactors = F, na.strings=c("NA", "-", "?", "."), sep='\t', header=TRUE, row.names=1 ) ## Hidden flag to use test data instead ## see: test-data/use.intestinal use.test.data = (names(in.table)[1] == "test") sc = NULL if (use.test.data) { sc = SCseq(intestinalData) message("Loading test data from library") } else { sc = SCseq(in.table) } filt = formals(filterdata) filt.ccc = formals(CCcorrect) filt.use.ccorrect = FALSE filt.lbatch.regexes = NULL filt\$mintotal = as.integer( '$filt.mintotal' ) filt\$minexpr = as.integer( '$filt.minexpr' ) filt\$minnumber = as.integer( '$filt.minnumber' ) #if str($filt.use.def) == "no": filt\$knn = as.integer( '$filt.use.knn' ) filt\$ccor = as.numeric( '$filt.use.ccor' ) filt\$bmode = as.character( '$filt.use.bmode' ) #if $filt.use.LBatch_regexes: filt.lbatch.regexes = string2textvector( '$filt.use.LBatch_regexes' ) #end if #if $filt.use.CGenes: filt\$CGenes = string2textvector( '$filt.use.CGenes' ) #end if #if $filt.use.FGenes: filt\$FGenes = string2textvector( '$filt.use.FGenes' ) #end if #if str($filt.use.ccc.use) == "yes" filt.use.ccorrect = TRUE #if $filt.use.ccc.vset: filt.ccc\$vset = string2textvector( '$filt.use.ccc.vset' ) #end if #if $filt.use.ccc.ncomp: filt.ccc\$nComp = as.integer( '$filt.use.ccc.ncomp' ) #end if filt.ccc\$pvalue = as.numeric( '$filt.use.ccc.pvalue' ) filt.ccc\$quant = as.numeric( '$filt.use.ccc.quant' ) filt.ccc\$dimR = as.logical( '$filt.use.ccc.dimr' ) filt.ccc\$mode = as.character( '$filt.use.ccc.mode.value' ) filt.ccc\$logscale = as.logical( '$filt.use.ccc.logscale' ) #end if #end if out.pdf = '${outpdf}' out.rdat = '${outrdat}' ]]></token> <token name="@CLUSTER_CHEETAH@"><![CDATA[ in.rdat = readRDS('${inputrds}') sc = in.rdat ## Perform do.filter use.filtnormconf = FALSE ## Perform do.cluster, do.outlier, do.clustmap, mkgenelist use.cluster = TRUE clust.compdist = formals(compdist) clust.clustexp = formals(clustexp) clust.compdist\$metric = as.character( '$clust.metric' ) clust.clustexp\$FUNcluster = as.character( '$clust.funcluster' ) #if str($clust.use.def) == "no": clust.compdist\$FSelect = as.logical( '$clust.use.fselect' ) #if $clust.use.knn: clust.compdist\$knn = as.integer( '$clust.use.knn' ) #end if clust.clustexp\$sat = as.logical( '$clust.use.sat' ) #if $clust.use.samp: clust.clustexp\$samp = as.integer( '$clust.use.samp' ) #end if #if $clust.use.cln: clust.clustexp\$cln = as.integer( '$clust.use.cln' ) clust.clustexp\$clustnr = as.integer( '$clust.use.clustnr' ) clust.clustexp\$bootnr = as.integer( '$clust.use.bootnr' ) ##clust.clustexp\$rseed = as.integer( '$clust.use.rseed' ) #end if #end if outlier.use.randomforest = FALSE outlier.findoutliers = formals(findoutliers) outlier.clustheatmap = formals(clustheatmap) outlier.rfcorrect = formals(rfcorrect) outlier.findoutliers\$outminc = as.integer( '$outlier.outminc' ) outlier.findoutliers\$outlg = as.integer( '$outlier.outlg' ) outlier.rfcorrect\$final = as.logical( '$outlier.final' ) #if str($outlier.use.def) == "no": #if $outlier.use.nbtree: outlier.rfcorrect\$nbtree = as.integer( '$outlier.use.nbtree' ) #end if outlier.findoutliers\$probthr = as.numeric( '$outlier.use.probthr' ) outlier.findoutliers\$outdistquant = as.numeric( '$outlier.use.outdistquant' ) ##outlier.rfcorrect\$rfseed = as.integer( '$outlier.use.rfseed' ) outlier.rfcorrect\$nbfactor = as.integer( '$outlier.use.nbfactor' ) #end if cluster.comptsne = formals(comptsne) cluster.compfr = formals(compfr) cluster.comptsne\$perplexity = as.integer( '$tsne.perplexity' ) cluster.compfr\$knn = as.integer( '$tsne.knn' ) #if str($tsne.use.def) == "no": cluster.comptsne\$initial_cmd = as.logical( '$tsne.use.initial_cmd' ) cluster.comptsne\$rseed = as.integer( '$tsne.use.rseed_tsne' ) cluster.compfr\$rseed = as.integer( '$tsne.use.rseed_fr' ) #end if genelist.tablelim = as.integer( '$extra.tablelim' ) genelist.plotlim = as.integer( '$extra.plotlim' ) genelist.foldchange = as.integer( '$extra.foldchange' ) genelist.pvalue = as.numeric( '$extra.pvalue' ) out.pdf = '${outpdf}' out.rdat = '${outrdat}' out.genelist = '${outgenelist}' ]]> </token> </macros>