| Next changeset 1:0960bd1161fa (2024-02-12) |
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Commit message:
"planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/pathifier commit b94cfc7bf8df30aa8e9249b75ea31332ee2bada1" |
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pathifier.R pathifier.xml test-data/kegg_pathways.gmt test-data/normals.tsv test-data/plot.pdf test-data/plot_noref.pdf test-data/sheffer.kegg.log test-data/sheffer.kegg.pdf test-data/sheffer.kegg.tsv test-data/sheffer.kegg_noref.rdata test-data/sheffer.kegg_noref.tsv test-data/sheffer.tsv test-data/sheffer_noref.tsv |
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| diff -r 000000000000 -r fec313f5c889 pathifier.R --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/pathifier.R Mon Apr 12 09:55:24 2021 +0000 |
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| b'@@ -0,0 +1,311 @@\n+##################################################################################################\n+# Running PATHIFIER (Drier et al., 2013)\n+# Based on the work of Author: Miguel Angel Garcia-Campos - Github: https://github.com/AngelCampos\n+##################################################################################################\n+\n+\n+options(show.error.messages = F, error = function() {\n+ cat(geterrmessage(), file = stderr()); q("no", 1, F)\n+ }\n+)\n+# we need that to not crash galaxy with an UTF8 error on German LC settings.\n+loc <- Sys.setlocale("LC_MESSAGES", "en_US.UTF-8")\n+\n+library(pathifier)\n+library(optparse)\n+library(pheatmap)\n+library(scatterplot3d)\n+library(circlize)\n+\n+option_list <- list(\n+ make_option(\n+ "--exp",\n+ type = "character",\n+ help = "Expression matrix"),\n+ make_option(\n+ "--sep",\n+ type = "character",\n+ default = "\\t",\n+ help = "File separator [default : \'%default\']"\n+ ),\n+ make_option(\n+ "--genes",\n+ type = "character",\n+ help = "Gene sets Pathways : gmt format (one pathway per line : Name, description, genes (one by column), tab separated)"),\n+ make_option(\n+ "--is_normal",\n+ default = F,\n+ type = "logical",\n+ help = "Define normals cells in your data"),\n+ make_option(\n+ "--normals",\n+ type = "character",\n+ help = "A vector of sample status : 1 = Healthy, 0 = Tumor. Must be in the same order as in expression data"),\n+ make_option(\n+ "--logfile",\n+ type = "character",\n+ default = "log.txt",\n+ help = "Log file name [default : \'%default\']"\n+ ),\n+ make_option(\n+ "--max_stability",\n+ type = "logical",\n+ default = T,\n+ help = "If true, throw away components leading to low stability of sampling noise [default : \'%default\']"\n+ ),\n+ make_option(\n+ "--attempts",\n+ type = "integer",\n+ default = 10,\n+ help = "Number of runs to determine stability. [default : \'%default\']"\n+ ),\n+ make_option(\n+ "--min_std",\n+ type = "character",\n+ default = "0.4",\n+ help = "Minimum of standard deviation to filter out low variable genes.\n+ Use --min.std data, to use the minimum std of your data [default : \'%default\']"\n+ ),\n+ make_option(\n+ "--min_exp",\n+ type = "character",\n+ default = "4",\n+ help = "Minimum of gene expression to filter out low expressed genes.\n+ Use --min.exp data, to use the minimum expression of your data [default : \'%default\']"\n+ ),\n+ make_option(\n+ "--pds",\n+ type = "character",\n+ default = "PDS.tsv",\n+ help = "Output PDS (Pathway deregulation score) of Pathifier in tabular file [default : \'%default\']"\n+ ),\n+ make_option(\n+ "--heatmap_cluster_cells",\n+ type = "logical",\n+ default = TRUE,\n+ help = "Cluster columns (cells) in the heatmap [default : \'%default\']"\n+ ),\n+ make_option(\n+ "--heatmap_cluster_pathways",\n+ type = "logical",\n+ default = TRUE,\n+ help = "Cluster rows (pathways) in the heatmap [default : \'%default\']"\n+ ),\n+ make_option(\n+ "--heatmap_show_cell_labels",\n+ type = "logical",\n+ default = FALSE,\n+ help = "Print column names (cells) on the heatmap [default : \'%default\']"\n+ ),\n+ make_option(\n+ "--heatmap_show_pathway_labels",\n+ type = "logical",\n+ default = FALSE,\n+ help = "Print row names (pathways) on the heatmap [default : \'%default\']"\n+ ),\n+ make_option(\n+ "--plot",\n+ type = "character",\n+ default = "./plot.pdf",\n+ help = "Pathifier visualization [default : \'%default\']"\n+ ),\n+ make_option(\n+ "--rdata",\n+ type = "character",\n+ default = "./results.rdata",\n+ help = "Pathifier object (S4) [default : \'%default\']"))\n+parser <- OptionParser(usage = "%prog [options] file", option_list = option_list)\n+args <- parse_args(parser)\n+if (args$sep == "tab") {\n+ args$sep <- "\\t"\n+}\n+\n+\n+# set seed for reproducibility\n+set.seed(123)\n+\n+# Load expression data for PATHIFIER\n+exp_matrix <- as.matrix(read.delim(file = args$exp,\n+ '..b', pch = 19, type = "l")\n+ sc3$points3d(ordered[, 1:3], box = F, pch = 19,\n+ col = col_score_fun(ordered$PDS))\n+\n+ # Plot color scale legend\n+ par(mar = c(5, 3, 0, 3))\n+ plot(seq(min(ordered$PDS), max(ordered$PDS), length = 100), rep(0, 100), pch = 15,\n+ axes = TRUE, yaxt = "n", xlab = "Color scale of PDS", ylab = "", bty = "n",\n+ col = col_score_fun(seq(min(ordered$PDS), max(ordered$PDS), length = 100)))\n+\n+\n+ cols_status <- ifelse(ordered$normal, "blue", "red")\n+ sc3 <- scatterplot3d(ordered[, 1:3],\n+ main = paste("Principal curve of", i),\n+ box = F, pch = "", type = "l")\n+ sc3$points3d(ordered[, 1:3], box = F,\n+ pch = ifelse(ordered$normal, 19, 8),\n+ col = ifelse(ordered$normal, "blue", "red"))\n+ legend("topright", pch = c(19, 8), yjust = 0,\n+ legend = c("normal", "cancer"),\n+ col = c("blue", "red"), cex = 1.1)\n+\n+ ## annotation for heatmap\n+ sample_status <- data.frame(Status = factor(ifelse(df$normal, "normal", "tumor")))\n+ rownames(sample_status) <- colnames(exp_matrix_filtered)\n+ color_status_heatmap <- list(Status = c(normal = "blue", tumor = "red"))\n+ }\n+} else{\n+ pds <- quantify_pathways_deregulation(exp_matrix_filtered,\n+ allgenes,\n+ gs,\n+ pathwaynames,\n+ maximize_stability = args$max_stability,\n+ attempts = args$attempts,\n+ logfile = args$logfile,\n+ min_std = args$min_std,\n+ min_exp = args$min_exp)\n+ for (i in pathwaynames) {\n+ df <- data.frame(pds$curves[[i]][, 1:3],\n+ PDS = as.numeric(pds$scores[[i]]),\n+ curve_order = as.vector(pds$curves_order[[i]]))\n+ ordered <- df[df$curve_order, ]\n+\n+ layout(cbind(1:2, 1:2), heights = c(7, 1))\n+ sc3 <- scatterplot3d(ordered[, 1:3],\n+ main = paste("Principal curve of", i),\n+ box = F, pch = 19, type = "l")\n+ sc3$points3d(ordered[, 1:3], box = F, pch = 19,\n+ col = col_score_fun(ordered$PDS))\n+\n+ # Plot color scale legend\n+ par(mar = c(5, 3, 0, 3))\n+ plot(seq(min(ordered$PDS), max(ordered$PDS), length = 100), rep(0, 100), pch = 15,\n+ axes = TRUE, yaxt = "n", xlab = "Color scale of PDS", ylab = "", bty = "n",\n+ col = col_score_fun(seq(min(ordered$PDS), max(ordered$PDS), length = 100)))\n+\n+\n+ ## annotation for heatmap (for the moment none for this situation)\n+ sample_status <- NA\n+ color_status_heatmap <- NA\n+ }\n+}\n+\n+## Create dataframe from Pathifier list and round score to 4 digits\n+pds_scores <- mapply(FUN = function(x) cbind(round(x, 4)), pds$scores)\n+dimnames(pds_scores) <- list(colnames(exp_matrix_filtered), names(pds$scores))\n+\n+## plot heatmap\n+if (ncol(pds_scores) > 1) {\n+ pheatmap(t(pds_scores),\n+ main = "Heatmap of Pathway Deregulation Score", # heat map title\n+ cluster_rows = args$heatmap_cluster_pathways, # apply clustering method\n+ cluster_cols = args$heatmap_cluster_cells, # apply clustering method\n+\n+ #Additional Options\n+ ## Color labeled columns\n+ annotation_col = sample_status,\n+ annotation_colors = color_status_heatmap,\n+ show_rownames = args$heatmap_show_pathway_labels,\n+ show_colnames = args$heatmap_show_cell_labels,\n+ border_color = NA,\n+ legend = TRUE)\n+}\n+dev.off()\n+\n+\n+## write table\n+write.table(pds_scores,\n+ args$pds,\n+ row.names = T,\n+ col.names = T,\n+ quote = F,\n+ sep = "\\t")\n+\n+## write S4 pathifier object\n+save(pds, file = args$rdata)\n' |
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| diff -r 000000000000 -r fec313f5c889 pathifier.xml --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/pathifier.xml Mon Apr 12 09:55:24 2021 +0000 |
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| b'@@ -0,0 +1,192 @@\n+<tool id="pathifier" name="Pathifier" version="1.0.1">\n+ <description>: Quantify deregulation of pathways in cancer</description>\n+ <requirements>\n+ <requirement type="package" version="1.6.2=r35h6115d3f_0">r-optparse</requirement>\n+ <requirement type="package" version="1.22.0=r351_0">bioconductor-pathifier</requirement>\n+ <requirement type="package" version="1.0.12=r351h6115d3f_0">r-pheatmap</requirement>\n+ <requirement type="package" version="0.3_41=r351h6115d3f_0">r-scatterplot3d</requirement>\n+ <requirement type="package" version="0.4.7=r35h6115d3f_0">r-circlize</requirement>\n+ </requirements>\n+ <stdio>\n+ <exit_code range="1:" level="fatal" description="Tool exception" />\n+ </stdio>\n+ <command detect_errors="exit_code"><![CDATA[ \n+ Rscript $__tool_directory__/pathifier.R \n+ --exp \'$input\'\n+ --sep \'$input_sep\'\n+ --genes \'$genes\'\n+\n+ #if $reference.is_normal == "Yes":\n+ --is_normal \'TRUE\'\n+ --normals \'$reference.normals\'\n+ #end if\n+\n+ --max_stability \'$max_stability\'\n+ --attempts \'$attempts\'\n+ --min_std \'$min_std\'\n+ --min_exp \'$min_exp\'\n+\n+ --heatmap_cluster_cells \'$heatmap_cluster_cells\'\n+ --heatmap_cluster_pathways \'$heatmap_cluster_pathways\'\n+ --heatmap_show_cell_labels \'$heatmap_show_cell_labels\'\n+ --heatmap_show_pathway_labels \'$heatmap_show_pathway_labels\'\n+\n+ --pds \'$pds\'\n+ --logfile \'$logfile\'\n+ --plot \'$plot\'\n+ --rdata \'$rdatafile\'\n+ \n+]]></command>\n+ <inputs>\n+ <param name="input" type="data" format="txt,tabular" label="expression data"/>\n+ <param name="input_sep" type="select" label="Input column separator">\n+ <option value="tab" selected="true">Tabs</option>\n+ <option value=",">Comma</option>\n+ </param>\n+ <param name="genes" type="data" format="txt" label="Gene sets Pathways" \n+ help="Must be in gmt format (one pathway per line : Name, description, genes (one by column), tab separated)" />\n+ <conditional name="reference">\n+ <param name="is_normal" label="Do you have non cancer transcriptomes in your data set ?" type="boolean" truevalue="Yes" falsevalue="" checked="false" \n+ help="If set the starting curve depends on the matrix of points with in a certain row order (first \'normal\' then \'cancer\' samples), otherwise the first principal component is used. See help for more informations"/>\n+ <when value="Yes">\n+ <param name="normals" type="data" format="tabular" label="Sample status"\n+ help="A two-column data frame, first column contains data labels, second column the levels of sample status : 1 = Healthy, 0 = Tumor (no header)" />\n+ </when>\n+ <when value="">\n+ </when>\n+ </conditional>\n+ <param name="max_stability" label="Throw away components leading to low stability of sampling noise" type="boolean" truevalue="TRUE" \n+ falsevalue="FALSE" checked="true" />\n+ <param name="attempts" type="integer" label="Number of runs to determine stability" value="100"/>\n+ <param name="min_std" type="text" value="0.4" label="Minimum of standard deviation to filter out low variable genes"\n+ help="Use \'data\' to use the minimum standard deviation of your data" />\n+ <param name="min_exp" type="text" value="4" label="Minimum of gene expression to filter out low variable genes"\n+ help="Use \'data\' to use the minimum expression of your data" />\n+ <param name="heatmap_cluster_cells" label="Cluster samples on heatmap" type="boolean" truevalue="TRUE" falsevalue="FALSE" checked="true" />\n+ <param name="heatmap_cluster_pathways" label="Cluster pathways on heatmap" typ'..b'name="rdatafile" file="sheffer.kegg_noref.rdata" ftype="rdata" compare="sim_size" />\n+ <output name="plot" file="plot_noref.pdf" ftype="pdf" compare="sim_size" />\n+ </test>\n+ </tests>\n+ <help>\n+\n+**What it does**\n+\n+Pathifier is an algorithm that infers pathway deregulation scores for each (tumor) sample on the basis\n+of expression data. This score is determined, in a context-specific manner, for every particular dataset\n+and type of cancer that is being investigated. The algorithm transforms gene-level information into\n+pathway-level information, generating a compact and biologically relevant representation of each sample.\n+\n+For each pathway analysed, the transcriptome datasets are plotted in the gene pathway space using a\n+Principal Component analysis (PCA) and a principal curve is regressed from these points. All transcriptomes \n+are projected on the nearest point of this curve. Pathifier finally computes a score which corresponds to \n+the distance (normalized to 1) of each point (transcriptome) to the curve origin. \n+\n+**Inputs**\n+\n+ * a matrix of n columns of observations (generally RNAseq experiments) and k rows of variables (generally k genes).\n+ * a Gene Matrix Transposed file (GMT format) where each row represents a gene set :\n+ * first column : gene set name (pathway name)\n+ * second : description of gene set\n+ * third and + : list of genes that composed the gene set tab-separated \n+ * (Optional) a two column table with no header, to described transcriptome status (Tumor or not) : \n+ * first column : sample labels\n+ * second : levels of sample status : 1 = Healthy, 0 = Tumor\n+\n+**Outputs**\n+\n+ * Table of Pathway Deregulation Scores : one by pathway (column) and by transcriptome (row)\n+ * Visualization of PDS (pdf) : \n+ * Principal curve of different PDS \n+ * Heatmap of PDS that allows (through clustering) to see pattern in pathway deregulation\n+ * (Optional) Log file of Pathifier algorithm\n+ * (Optional) Pathifier S4 object which contains all informations and results generated by Pathifier, for each pathway :\n+ * `scores` : PDS scores\n+ * `genesinpathway` : Gene identifiers in each pathway\n+ * `newmeanstd`\n+ * `origmeanstd`\n+ * `pathwaysize` : Number of genes retained in pathway\n+ * `curves` : Coordinates of transcriptomes projected on the principal curve\n+ * `curves_order` : Order of transcriptomes along the principal curve\n+ * `z` : z-scores matrix\n+ * `compin`\n+ * `xm`\n+ * `xs`\n+ * `center`\n+ * `rot`\n+ * `pctaken` : Number of principal component retained for pathifier analysis\n+ * `samplings`\n+ * `sucess` : List of pathway index that passed Pathfiier filters (more info in log file)\n+ * `logfile` : Name of logfile\n+\n+ </help>\n+ <citations>\n+ <citation type="bibtex">@Manual{,\n+ title = {{pathifier}: Quantify deregulation of pathways in cancer},\n+ author = {Yotam Drier},\n+ year = {2013-06-27},\n+ note = {R package version 1.22.0},\n+ url = {https://git.bioconductor.org/packages/pathifier},\n+ }\n+ </citation>\n+ <citation type="bibtex">@article {Drier6388,\n+ author = {Drier, Yotam and Sheffer, Michal and Domany, Eytan},\n+ title = {Pathway-based personalized analysis of cancer},\n+ volume = {110},\n+ number = {16},\n+ pages = {6388--6393},\n+ year = {2013},\n+ doi = {10.1073/pnas.1219651110},\n+ publisher = {National Academy of Sciences},\n+ issn = {0027-8424},\n+ URL = {https://www.pnas.org/content/110/16/6388},\n+ eprint = {https://www.pnas.org/content/110/16/6388.full.pdf},\n+ journal = {Proceedings of the National Academy of Sciences}\n+ }\n+ </citation>\n+ </citations>\n+</tool>\n' |
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| diff -r 000000000000 -r fec313f5c889 test-data/kegg_pathways.gmt --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/kegg_pathways.gmt Mon Apr 12 09:55:24 2021 +0000 |
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| @@ -0,0 +1,2 @@ +MISMATCH_REPAIR NA EXO1 LIG1 MLH1 MLH3 MSH2 MSH3 MSH6 PCNA PMS2 POLD1 POLD2 POLD3 POLD4 RFC1 RFC2 RFC3 RFC4 RFC5 RPA1 RPA2 RPA3 RPA4 SSBP1 +REGULATION_OF_AUTOPHAGY NA ATG12 ATG3 ATG4A ATG4B ATG4C ATG4D ATG5 ATG7 BECN1 BECN1L1 GABARAP GABARAPL1 GABARAPL2 IFNA1 IFNA10 IFNA13 IFNA14 IFNA16 IFNA17 IFNA2 IFNA21 IFNA4 IFNA5 IFNA6 IFNA7 IFNA8 IFNG INS PIK3C3 PIK3R4 PRKAA1 PRKAA2 ULK1 ULK2 ULK3 |
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| diff -r 000000000000 -r fec313f5c889 test-data/normals.tsv --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/normals.tsv Mon Apr 12 09:55:24 2021 +0000 |
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| b |
| diff -r 000000000000 -r fec313f5c889 test-data/plot.pdf |
| b |
| Binary file test-data/plot.pdf has changed |
| b |
| diff -r 000000000000 -r fec313f5c889 test-data/plot_noref.pdf |
| b |
| Binary file test-data/plot_noref.pdf has changed |
| b |
| diff -r 000000000000 -r fec313f5c889 test-data/sheffer.kegg.log --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/sheffer.kegg.log Mon Apr 12 09:55:24 2021 +0000 |
| b |
| @@ -0,0 +1,4 @@ +robust_score_bydist. min_exp= 4 , min_std= 0.4 +pathway 1 > sig: 0.06070369 +pathway 2 > sig: 0.1010493 +2 pathways processed with start= by ranks |
| b |
| diff -r 000000000000 -r fec313f5c889 test-data/sheffer.kegg.pdf |
| b |
| Binary file test-data/sheffer.kegg.pdf has changed |
| b |
| diff -r 000000000000 -r fec313f5c889 test-data/sheffer.kegg.tsv --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/sheffer.kegg.tsv Mon Apr 12 09:55:24 2021 +0000 |
| b |
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| b |
| diff -r 000000000000 -r fec313f5c889 test-data/sheffer.kegg_noref.rdata |
| b |
| Binary file test-data/sheffer.kegg_noref.rdata has changed |
| b |
| diff -r 000000000000 -r fec313f5c889 test-data/sheffer.kegg_noref.tsv --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/sheffer.kegg_noref.tsv Mon Apr 12 09:55:24 2021 +0000 |
| b |
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| b |
| diff -r 000000000000 -r fec313f5c889 test-data/sheffer.tsv --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/sheffer.tsv Mon Apr 12 09:55:24 2021 +0000 |
| b |
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|
| b |
| diff -r 000000000000 -r fec313f5c889 test-data/sheffer_noref.tsv --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/sheffer_noref.tsv Mon Apr 12 09:55:24 2021 +0000 |
| b |
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