| Previous changeset 14:6679616d0c18 (2022-03-22) Next changeset 16:2b9119d7d80a (2022-04-05) |
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Commit message:
"planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/mqppep commit 96659062ea07ac43d139746b0d119f1ee020f9cd" |
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modified:
macros.xml mqppep_anova.R mqppep_anova.xml mqppep_anova_script.Rmd workflow/ppenrich_suite_wf.ga |
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| diff -r 6679616d0c18 -r 2c5f1a2fe16a macros.xml --- a/macros.xml Tue Mar 22 23:12:18 2022 +0000 +++ b/macros.xml Sat Mar 26 02:27:12 2022 +0000 |
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| @@ -1,5 +1,5 @@ <macros> - <token name="@TOOL_VERSION@">0.1.5</token> + <token name="@TOOL_VERSION@">0.1.6</token> <token name="@VERSION_SUFFIX@">0</token> <xml name="requirements"> <requirements> @@ -16,15 +16,18 @@ <requirement type="package" version="1.7.1" >r-optparse</requirement> <requirement type="package" version="2.11" >r-rmarkdown</requirement> <!-- - It would be nice to use conda-forge/texlive-core, but issue 23 blocked PDF-creation. - Also, I got pango font errors (output had missing symbols replaced with boxes) unless - I specified the build as well as the version, i.e. - texlive-core=20210325=h97429d4_0 + It would be nice to use conda-forge/texlive-core rather than r-tinytex because the + former installs texlive when the package is built, but issue 23 blocked PDF-creation. + Also, texlive-core also gave pango font errors (output had missing symbols replaced + with boxes) unless I specified the build as well as the version when building a + conda environment, e.g.: texlive-core=20210325=h97429d4_0 --> <requirement type="package" version="0.37" >r-tinytex</requirement> <requirement type="package" version="3.3.5" >r-ggplot2</requirement> <requirement type="package" version="3.9.10" >python</requirement> <requirement type="package" version="5.26.2" >perl</requirement> + <requirement type="package" version="0.9.4" >r-latex2exp</requirement> + <requirement type="package" version="0.3.7" >r-vioplot</requirement> </requirements> </xml> </macros> |
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| diff -r 6679616d0c18 -r 2c5f1a2fe16a mqppep_anova.R --- a/mqppep_anova.R Tue Mar 22 23:12:18 2022 +0000 +++ b/mqppep_anova.R Sat Mar 26 02:27:12 2022 +0000 |
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| @@ -32,7 +32,7 @@ make_option( c("-f", "--firstDataColumn"), action = "store", - default = "10", + default = "^Intensity[^_]", type = "character", help = "First column of intensity values" ), @@ -110,9 +110,12 @@ if (! file.exists(args$inputFile)) { stop((paste("Input file", args$inputFile, "does not exist"))) } -input_file <- args$inputFile -alpha_file <- args$alphaFile -first_data_column <- args$firstDataColumn +input_file <- args$inputFile +alpha_file <- args$alphaFile +imputed_data_file_name <- args$imputedDataFile +imp_qn_lt_data_filenm <- args$imputedQNLTDataFile +report_file_name <- args$reportFile + imputation_method <- args$imputationMethod print( grepl( @@ -133,42 +136,49 @@ return(-1) } +# read with default values, when applicable mean_percentile <- args$meanPercentile -print("mean_percentile is:") -cat(str(mean_percentile)) - -sd_percentile <- args$sdPercentile -print("sd_percentile is:") -cat(str(mean_percentile)) - +sd_percentile <- args$sdPercentile +# in the case of 'random" these values are ignored by the client script +if (imputation_method == "random") { + print("mean_percentile is:") + cat(str(mean_percentile)) -regex_sample_names <- gsub("^[ \t\n]*", "", - readChar(args$regexSampleNames, 1000) - ) -regex_sample_names <- gsub("[ \t\n]*$", "", - regex_sample_names - ) -cat(regex_sample_names) -cat("\n") + print("sd_percentile is:") + cat(str(mean_percentile)) +} -regex_sample_grouping <- gsub("^[ \t\n]*", "", - readChar(args$regexSampleGrouping, 1000) - ) -regex_sample_grouping <- gsub("[ \t\n]*$", "", - regex_sample_grouping - ) -cat(regex_sample_grouping) -cat("\n") - -imputed_data_file_name <- args$imputedDataFile -imp_qn_lt_data_filenm <- args$imputedQNLTDataFile -report_file_name <- args$reportFile - -print("regex_sample_names is:") -cat(str(regex_sample_names)) - -print("regex_sample_grouping is:") -cat(str(regex_sample_grouping)) +# convert string parameters that are passed in via config files: +# - firstDataColumn +# - regexSampleNames +# - regexSampleGrouping +read_config_file_string <- function(fname, limit) { + # eliminate any leading whitespace + result <- gsub("^[ \t\n]*", "", readChar(fname, limit)) + # eliminate any trailing whitespace + result <- gsub("[ \t\n]*$", "", result) + # substitute characters escaped by Galaxy sanitizer + result <- gsub("__lt__", "<", result) + result <- gsub("__le__", "<=", result) + result <- gsub("__eq__", "==", result) + result <- gsub("__ne__", "!=", result) + result <- gsub("__gt__", ">", result) + result <- gsub("__ge__", ">=", result) + result <- gsub("__sq__", "'", result) + result <- gsub("__dq__", '"', result) + result <- gsub("__ob__", "[", result) + result <- gsub("__cb__", "]", result) +} +cat(paste0("first_data_column file: ", args$firstDataColumn, "\n")) +cat(paste0("regex_sample_names file: ", args$regexSampleNames, "\n")) +cat(paste0("regex_sample_grouping file: ", args$regexSampleGrouping, "\n")) +nc <- 1000 +regex_sample_names <- read_config_file_string(args$regexSampleNames, nc) +regex_sample_grouping <- read_config_file_string(args$regexSampleGrouping, nc) +first_data_column <- read_config_file_string(args$firstDataColumn, nc) +cat(paste0("first_data_column: ", first_data_column, "\n")) +cat(paste0("regex_sample_names: ", regex_sample_names, "\n")) +cat(paste0("regex_sample_grouping: ", regex_sample_grouping, "\n")) # from: https://github.com/molgenis/molgenis-pipelines/wiki/ # How-to-source-another_file.R-from-within-your-R-script |
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| diff -r 6679616d0c18 -r 2c5f1a2fe16a mqppep_anova.xml --- a/mqppep_anova.xml Tue Mar 22 23:12:18 2022 +0000 +++ b/mqppep_anova.xml Sat Mar 26 02:27:12 2022 +0000 |
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| @@ -22,7 +22,7 @@ \${CONDA_PREFIX}/bin/Rscript \$TEMP/mqppep_anova.R --inputFile '$input_file' --alphaFile '$alpha_file' - --firstDataColumn $first_data_column + --firstDataColumn $intensity_column_regex_f --imputationMethod $imputation.imputation_method #if $imputation.imputation_method == "random" --meanPercentile '$imputation.meanPercentile' @@ -45,6 +45,9 @@ <configfile name="sample_grouping_regex_f"> $sample_grouping_regex </configfile> + <configfile name="intensity_column_regex_f"> + $intensity_column_regex + </configfile> </configfiles> <inputs> <param name="input_file" type="data" format="tabular" label="Filtered Phosphopeptide Intensities" @@ -53,9 +56,9 @@ <param name="alpha_file" type="data" format="tabular" label="alpha cutoff level" help="[alpha_file] List of alpha cutoff values for significance testing; text file having one column and no header" /> - <param name="first_data_column" type="text" value="Intensity" - label="First data column" - help="[first_data_column] First column having intensity values (integer or PERL-compatible regular expression matching column label)" + <param name="intensity_column_regex" type="text" value="^Intensity[^_]" + label="Intensity-column pattern" + help="[intensity_column_regex] Pattern matching columns that have peptide intensity data (PERL-compatible regular expression matching column label)" /> <!-- imputation_method <- c("group-median","median","mean","random")[1] --> <conditional name="imputation"> @@ -75,15 +78,15 @@ label="Mean percentile for random values" help="[meanPercentile] Percentile center of random values; range [1,99]" /> - <param name="sdPercentile" type="float" value="0.2" + <param name="sdPercentile" type="float" value="1.0" label="Percentile std. dev. for random values" help="[sdPercentile] Standard deviation adjustment-factor for random values; real number. (1.0 means SD equal to the SD for the entire data set.)" /> </when> </conditional> <param name="sample_names_regex" type="text" value="\.\d+[A-Z]$" - help="[sample_names_regex] PERL-compatible regular expression extracting sample-names from the the name of a spectrum file (without extension)" - label="Sample-extraction regex"> + help="[sample_names_regex] Pattern extracting sample-names from names of columns that have peptide intensity data (PERL-compatible regular expression)" + label="Sample-extraction pattern"> <sanitizer> <valid initial="string.printable"> <remove value="'"/> @@ -91,8 +94,8 @@ </sanitizer> </param> <param name="sample_grouping_regex" type="text" value="\d+" - help="[sample_grouping_regex] PERL-compatible regular expression extracting sample-group from each sample-name (i.e., extracted by previous regex pattern)" - label="Group-extraction regex"> + help="[sample_grouping_regex] Pattern extracting sample-group from the sample-names that are extracted by 'Sample-extraction pattern' (PERL-compatible regular expression)" + label="Group-extraction pattern"> <sanitizer> <valid initial="string.printable"> <remove value="'"/> @@ -112,7 +115,7 @@ <test> <param name="input_file" ftype="tabular" value="test_input_for_anova.tabular"/> <param name="alpha_file" ftype="tabular" value="alpha_levels.tabular"/> - <param name="first_data_column" value="10"/> + <param name="intensity_column_regex" value="^Intensity[^_]"/> <param name="imputation_method" value="group-median"/> <param name="sample_names_regex" value="\.\d+[A-Z]$"/> <param name="sample_grouping_regex" value="\d+"/> @@ -128,10 +131,10 @@ <test> <param name="input_file" ftype="tabular" value="test_input_for_anova.tabular"/> <param name="alpha_file" ftype="tabular" value="alpha_levels.tabular"/> - <param name="first_data_column" value="10"/> + <param name="intensity_column_regex" value="^Intensity[^_]"/> <param name="imputation_method" value="random"/> <param name="meanPercentile" value="1" /> - <param name="sdPercentile" value="0.2" /> + <param name="sdPercentile" value="1.0" /> <param name="sample_names_regex" value="\.\d+[A-Z]$"/> <param name="sample_grouping_regex" value="\d+"/> <output name="imp_qn_lt_file"> @@ -167,7 +170,7 @@ **Input parameters** -``first_data_column`` +``intensity_column_regex`` First column of ``input_file`` having intensity values (integer or PERL-compatible regular expression matching column label). Default: **Intensity** ``imputation_method`` |
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| diff -r 6679616d0c18 -r 2c5f1a2fe16a mqppep_anova_script.Rmd --- a/mqppep_anova_script.Rmd Tue Mar 22 23:12:18 2022 +0000 +++ b/mqppep_anova_script.Rmd Sat Mar 26 02:27:12 2022 +0000 |
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| b'@@ -8,24 +8,24 @@\n latex_document:\n toc: true\n params:\n- inputFile: "test-data/test_input_for_anova.tabular"\n alphaFile: "test-data/alpha_levels.tabular"\n- firstDataColumn: "Intensity"\n+ inputFile: "test-data/UT_Phospho_ST_Sites.preproc.tabular"\n+ firstDataColumn: "^Intensity[^_]"\n imputationMethod: !r c("group-median", "median", "mean", "random")[4]\n meanPercentile: 1\n sdPercentile: 1.0\n regexSampleNames: "\\\\.\\\\d+[A-Z]$"\n regexSampleGrouping: "\\\\d+"\n- imputedDataFilename: "test-data/imputedDataFilename.txt"\n- imputedQNLTDataFile: "test-data/imputedQNLTDataFile.txt"\n+ imputedDataFilename: "test-data/limbo/imputedDataFilename.txt"\n+ imputedQNLTDataFile: "test-data/limbo/imputedQNLTDataFile.txt"\n show_toc: true\n ---\n <!--\n- latex_document: default\n+ alphaFile: "test-data/alpha_levels.tabular"\n inputFile: "test-data/test_input_for_anova.tabular"\n+ inputFile: "test-data/UT_Phospho_ST_Sites.preproc.tabular"\n inputFile: "test-data/density_failure.preproc_tab.tabular"\n- inputFile: "test-data/UT_Phospho_STY_Sites.preproc_tab"\n-date: "May 28, 2018; Mar 16, 2022"\n+ latex_document: default\n -->\n ```{r setup, include = FALSE}\n # ref for parameterizing Rmd document: https://stackoverflow.com/a/37940285\n@@ -44,6 +44,7 @@\n sqrt(const_stripchart_cex * const_stripchart_cex / 2)\n const_stripchart_jitter <- 0.3\n const_write_debug_files <- FALSE\n+const_table_anchor <- "tbp"\n \n ### FUNCTIONS\n \n@@ -103,7 +104,7 @@\n }\n \n # Use this like print.data.frame, from which it is adapted:\n-print_data_frame_latex <-\n+data_frame_latex <-\n function(\n x,\n ...,\n@@ -116,7 +117,7 @@\n # string with justification of each column\n justification = NULL,\n # TRUE to center on page\n- centered = FALSE,\n+ centered = TRUE,\n # optional capttion\n caption = NULL,\n # h(inline); b(bottom); t (top) or p (separate page)\n@@ -200,13 +201,10 @@\n \n ```\n \n-## Purpose:\n+## Purpose\n \n Perform imputation of missing values, quantile normalization, and ANOVA.\n \n-<!--\n-## Variables to change for each input file\n--->\n ```{r include = FALSE}\n # Input Filename\n input_file <- params$inputFile\n@@ -214,19 +212,25 @@\n # First data column - ideally, this could be detected via regexSampleNames,\n # but for now leave it as is.\n first_data_column <- params$firstDataColumn\n-fdc_is_integer <- TRUE\n-first_data_column <- withCallingHandlers(\n- as.integer(first_data_column)\n- , warning = function(w) fdc_is_integer <<- FALSE\n- )\n-if (FALSE == fdc_is_integer) {\n- first_data_column <- params$firstDataColumn\n+fdc_is_integer <- is.integer(first_data_column)\n+if (fdc_is_integer) {\n+ first_data_column <- as.integer(params$firstDataColumn)\n }\n \n # False discovery rate adjustment for ANOVA\n # Since pY abundance is low, set to 0.10 and 0.20 in addition to 0.05\n val_fdr <-\n- read.table(file = params$alphaFile, sep = "\\t", header = F, quote = "")[, 1]\n+ read.table(file = params$alphaFile, sep = "\\t", header = F, quote = "")\n+\n+if (\n+ ncol(val_fdr) != 1 ||\n+ sum(!is.numeric(val_fdr[, 1])) ||\n+ sum(val_fdr[, 1] < 0) ||\n+ sum(val_fdr[, 1] > 1)\n+) {\n+ stop("alphaFile should be one column of numbers within the range [0.0,1.0]")\n+}\n+val_fdr <- val_fdr[, 1]\n \n #Imputed Data filename\n imputed_data_filename <- params$imputedDataFilename\n@@ -274,32 +278,15 @@\n )\n ```\n \n-### Parse column names, sample names, and factor levels from input file\n+## Extract Sample Names and Factor Levels\n+\n+Column names parsed from input file are shown in Table 1; sample names and factor levels, in Table 2.\n \n ```{r echo = FALSE, results = \'asis\'}\n-# Write column naames as an enumerated list.\n-column_name_df <- data.frame(\n- column = seq_len(length(colnames(full_data))),\n- name = colnames(full_data)\n- )\n-print_data_frame_latex(\n- x = column_name_df,\n- justification = "l l",\n- centered = TRUE,\n- caption = "Input data column name",\n- anchor = "h"\n- )\n \n data_column_indices <- grep(first_data_column, names(full_data), perl = TRUE)\n-cat(\n- sprintf(\n-'..b' stripchart(\n+ red_dots, # Data\n+ method = "jitter", # Random noise\n+ jitter = const_stripchart_jitter,\n+ pch = 19, # Pch symbols\n+ cex = const_stripsmall_cex, # Size of symbols reduced\n+ col = "red", # Color of the symbol\n+ vertical = TRUE, # Vertical mode\n+ add = TRUE # Add it over\n+ )\n+\n+ } else {\n+ # violin plot\n+ cat("\\\\leavevmode\\n\\\\quad\\n\\n\\\\quad\\n\\n")\n+ vioplot::vioplot(\n+ x = lapply(blue_dots, function(x) x[!is.na(x)]),\n+ col = "lightblue1",\n+ side = "left",\n+ plotCentre = "line",\n+ ylim = ylim_save,\n+ main = "Distributions of observed and imputed data",\n+ sub = "Light blue = observed data; Pink = imputed data",\n+ xlab = "Sample",\n+ ylab = latex2exp::TeX("$log_{10}$(peptide intensity)")\n+ )\n+ vioplot::vioplot(\n+ x = lapply(red_dots, function(x) x[!is.na(x)]),\n+ col = "lightpink1",\n+ side = "right",\n+ plotCentre = "line",\n+ add = T\n+ )\n+ }\n+\n par(old_par)\n \n # density plot\n@@ -738,7 +784,7 @@\n "Black = combined"\n ),\n main = "Density of peptide intensity before and after imputation",\n- xlab = "log10(peptide intensity)",\n+ xlab = latex2exp::TeX("$log_{10}$(peptide intensity)"),\n ylab = "Probability density"\n )\n lines(d_original, col = "blue")\n@@ -909,18 +955,9 @@\n quant_data_log\n , las = 1\n , col = const_boxplot_fill\n+ , ylab = latex2exp::TeX("$log_{10}$(peptide intensity)")\n+ , xlab = "Sample"\n )\n- # Points\n- stripchart(\n- quant_data_log, # Data\n- method = "jitter", # Random noise\n- jitter = const_stripchart_jitter,\n- pch = 19, # Pch symbols\n- cex = const_stripchart_cex, # Size of symbols reduced\n- col = "goldenrod", # Color of the symbol\n- vertical = TRUE, # Vertical mode\n- add = TRUE # Add it over\n- )\n par(old_par)\n } else {\n cat("There are no peptides to plot\\n")\n@@ -936,7 +973,8 @@\n ggplot(\n quant_data_log_stack,\n aes(x = values)\n- ) +\n+ ) + xlab(latex2exp::TeX("$log_{10}$(peptide intensity)")) +\n+ ylab("Probability density") +\n geom_density(\n aes(group = ind, colour = ind),\n na.rm = TRUE\n@@ -949,7 +987,7 @@\n cat("\\\\leavevmode\\\\newpage\\n")\n ```\n \n-## Perform ANOVA filters\n+## Perform ANOVA Filters\n \n ```{r, echo = FALSE}\n # Make new data frame containing only Phosphopeptides\n@@ -1125,24 +1163,13 @@\n main = "Imputed, normalized intensities", # no line plot\n las = 1,\n col = const_boxplot_fill,\n- ylab = expression(log[10](intensity))\n+ ylab = latex2exp::TeX("$log_{10}$(peptide intensity)")\n )\n- # Points\n- stripchart(\n- filtered_data_filtered, # Data\n- method = "jitter", # Random noise\n- jitter = const_stripchart_jitter,\n- pch = 19, # Pch symbols\n- cex = const_stripchart_cex, # Size of symbols reduced\n- col = "goldenrod", # Color of the symbol\n- vertical = TRUE, # Vertical mode\n- add = TRUE # Add it over\n- )\n par(old_par)\n } else {\n cat(sprintf(\n "%s < %0.2f\\n\\n\\n\\n\\n",\n- "No peptides were found to have cutoff adjusted p-value <",\n+ "No peptides were found to have cutoff adjusted p-value",\n cutoff\n ))\n }\n@@ -1229,11 +1256,12 @@\n )\n } else {\n if (nrow(m) == 1) {\n+ next\n+ } else {\n cat(\n sprintf("Heatmap for %d usable peptides whose", nrow(m)),\n sprintf("adjusted p-value < %0.2f\\n", cutoff)\n )\n- next\n }\n }\n cat("\\n\\n\\n")\n@@ -1263,9 +1291,3 @@\n }\n cat("\\\\leavevmode\\n\\n\\n")\n ```\n-\n-<!--\n-## Peptide IDs, etc.\n-\n-See output files.\n--->\n' |
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| diff -r 6679616d0c18 -r 2c5f1a2fe16a workflow/ppenrich_suite_wf.ga --- a/workflow/ppenrich_suite_wf.ga Tue Mar 22 23:12:18 2022 +0000 +++ b/workflow/ppenrich_suite_wf.ga Sat Mar 26 02:27:12 2022 +0000 |
| [ |
| b'@@ -28,27 +28,155 @@\n "name": "Input dataset",\n "outputs": [],\n "position": {\n- "bottom": 346.3999938964844,\n- "height": 81.89999389648438,\n- "left": 495,\n- "right": 695,\n- "top": 264.5,\n- "width": 200,\n- "x": 495,\n- "y": 264.5\n+ "bottom": 336.19168853759766,\n+ "height": 82.20000457763672,\n+ "left": 482.5333557128906,\n+ "right": 682.5333709716797,\n+ "top": 253.99168395996094,\n+ "width": 200.00001525878906,\n+ "x": 482.5333557128906,\n+ "y": 253.99168395996094\n },\n "tool_id": null,\n- "tool_state": "{\\"optional\\": false, \\"format\\": [\\"tabular\\"]}",\n+ "tool_state": "{\\"optional\\": false, \\"format\\": [\\"tabular\\"], \\"tag\\": \\"\\"}",\n "tool_version": null,\n "type": "data_input",\n- "uuid": "21c3c29d-9e8c-4ece-b585-9e68fed7a93f",\n+ "uuid": "78170155-4d6c-461b-a289-bcf0196b87db",\n "workflow_outputs": []\n },\n "1": {\n+ "annotation": "Pattern matching columns that have peptide intensity data (PERL-compatible regular expression matching column label)",\n+ "content_id": null,\n+ "errors": null,\n+ "id": 1,\n+ "input_connections": {},\n+ "inputs": [\n+ {\n+ "description": "Pattern matching columns that have peptide intensity data (PERL-compatible regular expression matching column label)",\n+ "name": "Intensity-column pattern"\n+ }\n+ ],\n+ "label": "Intensity-column pattern",\n+ "name": "Input parameter",\n+ "outputs": [],\n+ "position": {\n+ "bottom": 443.9083480834961,\n+ "height": 82.20000457763672,\n+ "left": 510.5917053222656,\n+ "right": 710.5917205810547,\n+ "top": 361.7083435058594,\n+ "width": 200.00001525878906,\n+ "x": 510.5917053222656,\n+ "y": 361.7083435058594\n+ },\n+ "tool_id": null,\n+ "tool_state": "{\\"default\\": \\"^Intensity[^_]\\", \\"parameter_type\\": \\"text\\", \\"optional\\": true}",\n+ "tool_version": null,\n+ "type": "parameter_input",\n+ "uuid": "b1a27840-417c-4e81-9fc3-7d3e3dee6753",\n+ "workflow_outputs": []\n+ },\n+ "2": {\n+ "annotation": "Pattern extracting sample-names from names of columns that have peptide intensity data (PERL-compatible regular expression)",\n+ "content_id": null,\n+ "errors": null,\n+ "id": 2,\n+ "input_connections": {},\n+ "inputs": [\n+ {\n+ "description": "Pattern extracting sample-names from names of columns that have peptide intensity data (PERL-compatible regular expression)",\n+ "name": "Sample-extraction pattern"\n+ }\n+ ],\n+ "label": "Sample-extraction pattern",\n+ "name": "Input parameter",\n+ "outputs": [],\n+ "position": {\n+ "bottom": 555.9083480834961,\n+ "height": 82.20000457763672,\n+ "left": 526.6583862304688,\n+ "right": 726.6584014892578,\n+ "top": 473.7083435058594,\n+ "width": 200.00001525878906,\n+ "x": 526.6583862304688,\n+ "y": 473.7083435058594\n+ },\n+ "tool_id": null,\n+ "tool_state": "{\\"default\\": \\"\\\\\\\\.\\\\\\\\d+[A-Z]$\\", \\"parameter_type\\": \\"text\\", \\"optional\\": true}",\n+ "tool_version": null,\n+ "type": "parameter_input",\n+ "uuid": "05fe662c-b0a9-4ae7-8232-1b0a09261ac7",'..b'utput"\n }\n },\n "inputs": [],\n@@ -627,17 +773,17 @@\n }\n ],\n "position": {\n- "bottom": 1609.6000061035156,\n- "height": 255.60000610351562,\n- "left": 1617,\n- "right": 1817,\n- "top": 1354,\n- "width": 200,\n- "x": 1617,\n- "y": 1354\n+ "bottom": 1994.1084289550781,\n+ "height": 367.6000061035156,\n+ "left": 1319.6083984375,\n+ "right": 1519.608413696289,\n+ "top": 1626.5084228515625,\n+ "width": 200.00001525878906,\n+ "x": 1319.6083984375,\n+ "y": 1626.5084228515625\n },\n "post_job_actions": {\n- "RenameDatasetActionimputed_data_file": {\n+ "RenameDatasetActionimp_qn_lt_file": {\n "action_arguments": {\n "newname": "#{input_file}.intensities_randomly-imputed_QN_LT"\n },\n@@ -653,31 +799,32 @@\n },\n "RenameDatasetActionreport_file": {\n "action_arguments": {\n- "newname": "#{input_file}.intensities_randomly-imputed_report (download/unzip to view)"\n+ "newname": "#{input_file}.intensities_randomly-imputed_report"\n },\n "action_type": "RenameDatasetAction",\n "output_name": "report_file"\n }\n },\n "tool_id": "mqppep_anova",\n- "tool_state": "{\\"alpha_file\\": {\\"__class__\\": \\"ConnectedValue\\"}, \\"first_data_column\\": \\"Intensity\\", \\"imputation\\": {\\"imputation_method\\": \\"random\\", \\"__current_case__\\": 3, \\"meanPercentile\\": \\"1\\", \\"sdPercentile\\": \\"0.2\\"}, \\"input_file\\": {\\"__class__\\": \\"ConnectedValue\\"}, \\"sample_grouping_regex\\": \\"(\\\\\\\\d+)\\", \\"sample_names_regex\\": \\"\\\\\\\\.(\\\\\\\\d+)[A-Z]$\\", \\"__page__\\": null, \\"__rerun_remap_job_id__\\": null}",\n+ "tool_state": "{\\"alpha_file\\": {\\"__class__\\": \\"ConnectedValue\\"}, \\"imputation\\": {\\"imputation_method\\": \\"random\\", \\"__current_case__\\": 3, \\"meanPercentile\\": \\"1\\", \\"sdPercentile\\": \\"1.0\\"}, \\"input_file\\": {\\"__class__\\": \\"ConnectedValue\\"}, \\"intensity_column_regex\\": \\"^Intensity[^_]\\", \\"sample_grouping_regex\\": {\\"__class__\\": \\"ConnectedValue\\"}, \\"sample_names_regex\\": {\\"__class__\\": 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