| Previous changeset 1:817eb707bbf4 (2021-11-26) Next changeset 3:8c64a2da3869 (2022-02-10) |
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Commit message:
"planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/music/ commit 20f8561478535013e111d982b99639f48f1bea79" |
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modified:
inspect_eset.xml macros.xml scripts/dendrogram.R scripts/estimateprops.R |
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added:
test-data/default_output_no_disease.pdf test-data/mouse_scrna_exprs.tabular test-data/mouse_scrna_pheno.tabular |
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removed:
scripts/inspect.R |
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| diff -r 817eb707bbf4 -r 577435e5e6b2 inspect_eset.xml --- a/inspect_eset.xml Fri Nov 26 15:54:31 2021 +0000 +++ b/inspect_eset.xml Sat Jan 29 12:51:27 2022 +0000 |
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| @@ -6,7 +6,7 @@ </macros> <expand macro="requirements"/> <command detect_errors="exit_code"><![CDATA[ -Rscript --vanilla '$__tool_directory__/scripts/inspect.R' '$conf' +Rscript --vanilla '$conf' ]]></command> <configfiles> <configfile name="conf" > @@ -26,10 +26,35 @@ inspector = null_str_vec('$inspector') outfile_tab='$out_tab' +suppressWarnings(suppressPackageStartupMessages(library(xbioc))) +suppressWarnings(suppressPackageStartupMessages(library(MuSiC))) + +printout = function(text) { + if (typeof(text) %in% c("list", "vector", "integer", "double", "numeric")) { + write.table(text, file = outfile_tab, quote = F, sep = "\t", + col.names = NA) + } else { + ## text + print(typeof(text)) + capture.output(text, file = outfile_tab) # nolint + } +} + +if (inspector %in% c("print", "pData", "fData", "dims", + "experimentData", "protocolData", "exprs", + "signature", "annotation", "abstract")) { + op = get(inspector) + tab = op(rds_eset) + printout(tab) +} else { + stop(paste0("No such option:", inspector)) +} + + </configfile> </configfiles> <inputs> - <param name="rds_eset" label="ESet Dataset" type="data" format="rdata.eset" /> + <param name="rds_eset" label="ESet Dataset" type="data" format="@RDATATYPE@" /> <param name="inspector" label="Inspect" type="select" help="Inspect an aspect of the ESet dataset" > <!-- See: https://www.rdocumentation.org/packages/Biobase/versions/2.32.0/topics/eSet --> |
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| diff -r 817eb707bbf4 -r 577435e5e6b2 macros.xml --- a/macros.xml Fri Nov 26 15:54:31 2021 +0000 +++ b/macros.xml Sat Jan 29 12:51:27 2022 +0000 |
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| @@ -1,9 +1,14 @@ <macros> - <token name="@VERSION_SUFFIX@">1</token> + <token name="@VERSION_SUFFIX@">2</token> <!-- The ESet inspector/constructor and MuSiC tool can have independent Galaxy versions but should reference the same package version always. --> <token name="@TOOL_VERSION@">0.1.1</token> + <token name="@RDATATYPE@">rdata</token> + <!-- Below is disabled until Galaxy supports it. Still not present + in 21.09 + <token name="@RDATATYPE@">rdata.eset</token> + --> <xml name="requirements"> <requirements> <requirement type="package" version="@TOOL_VERSION@" >music-deconvolution</requirement> |
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| diff -r 817eb707bbf4 -r 577435e5e6b2 scripts/dendrogram.R --- a/scripts/dendrogram.R Fri Nov 26 15:54:31 2021 +0000 +++ b/scripts/dendrogram.R Sat Jan 29 12:51:27 2022 +0000 |
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| @@ -10,7 +10,7 @@ if (lfile == "None") { return(NULL) } - return(read.table(file = lfile, header = FALSE, + return(read.table(file = lfile, header = FALSE, check.names = FALSE, stringsAsFactors = FALSE)$V1) } |
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| diff -r 817eb707bbf4 -r 577435e5e6b2 scripts/estimateprops.R --- a/scripts/estimateprops.R Fri Nov 26 15:54:31 2021 +0000 +++ b/scripts/estimateprops.R Sat Jan 29 12:51:27 2022 +0000 |
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| b'@@ -17,13 +17,21 @@\n estimated_music_props <- est_prop$Est.prop.weighted\n estimated_nnls_props <- est_prop$Est.prop.allgene\n \n+scale_yaxes <- function(gplot, value) {\n+ if (is.na(value)) {\n+ gplot\n+ } else {\n+ gplot + scale_y_continuous(lim = c(0, value))\n+ }\n+}\n+\n ## Show different in estimation methods\n ## Jitter plot of estimated cell type proportions\n-jitter_fig <- Jitter_Est(\n+jitter_fig <- scale_yaxes(Jitter_Est(\n list(data.matrix(estimated_music_props),\n data.matrix(estimated_nnls_props)),\n method.name = methods, title = "Jitter plot of Est Proportions",\n- size = 2, alpha = 0.7) + theme_minimal()\n+ size = 2, alpha = 0.7) + theme_minimal(), maxyscale)\n \n \n ## Make a Plot\n@@ -42,11 +50,6 @@\n message(celltypes)\n }\n \n-if (phenotype_target_threshold == -99) {\n- phenotype_target_threshold <- -Inf\n- message("phenotype target threshold set to -Inf")\n-}\n-\n if (is.null(phenotype_factors)) {\n phenotype_factors <- colnames(pData(bulk_eset))\n }\n@@ -54,67 +57,94 @@\n phenotype_factors <- phenotype_factors[\n !(phenotype_factors %in% phenotype_factors_always_exclude)]\n message("Phenotype Factors to use:")\n-message(phenotype_factors)\n-\n+message(paste0(phenotype_factors, collapse = ", "))\n \n m_prop$CellType <- factor(m_prop$CellType, levels = celltypes) # nolint\n m_prop$Method <- factor(rep(methods, each = nrow(estimated_music_props_flat)), # nolint\n levels = methods)\n-m_prop$Disease_factor <- rep(bulk_eset[[phenotype_target]], 2 * length(celltypes)) # nolint\n-m_prop <- m_prop[!is.na(m_prop$Disease_factor), ]\n-## Generate a TRUE/FALSE table of Normal == 1 and Disease == 2\n-sample_groups <- c("Normal", sample_disease_group)\n-m_prop$Disease <- factor(sample_groups[(m_prop$Disease_factor > phenotype_target_threshold) + 1], # nolint\n- levels = sample_groups)\n+\n+if (use_disease_factor) {\n+\n+ if (phenotype_target_threshold == -99) {\n+ phenotype_target_threshold <- -Inf\n+ message("phenotype target threshold set to -Inf")\n+ }\n+\n+ m_prop$Disease_factor <- rep(bulk_eset[[phenotype_target]], 2 * length(celltypes)) # nolint\n+ m_prop <- m_prop[!is.na(m_prop$Disease_factor), ]\n+ ## Generate a TRUE/FALSE table of Normal == 1 and Disease == 2\n+ sample_groups <- c("Normal", sample_disease_group)\n+ m_prop$Disease <- factor(sample_groups[(m_prop$Disease_factor > phenotype_target_threshold) + 1], # nolint\n+ levels = sample_groups)\n \n-## Binary to scale: e.g. TRUE / 5 = 0.2\n-m_prop$D <- (m_prop$Disease == # nolint\n- sample_disease_group) / sample_disease_group_scale\n-## NA\'s are not included in the comparison below\n-m_prop <- rbind(subset(m_prop, Disease != sample_disease_group),\n- subset(m_prop, Disease == sample_disease_group))\n+ ## Binary to scale: e.g. TRUE / 5 = 0.2\n+ m_prop$D <- (m_prop$Disease == # nolint\n+ sample_disease_group) / sample_disease_group_scale\n+ ## NA\'s are not included in the comparison below\n+ m_prop <- rbind(subset(m_prop, Disease != sample_disease_group),\n+ subset(m_prop, Disease == sample_disease_group))\n \n-jitter_new <- ggplot(m_prop, aes(Method, Prop)) +\n- geom_point(aes(fill = Method, color = Disease, stroke = D, shape = Disease),\n- size = 2, alpha = 0.7,\n- position = position_jitter(width = 0.25, height = 0)) +\n- facet_wrap(~ CellType, scales = "free") +\n- scale_colour_manual(values = c("white", "gray20")) +\n- scale_shape_manual(values = c(21, 24)) + theme_minimal()\n+ jitter_new <- scale_yaxes(ggplot(m_prop, aes(Method, Prop)) +\n+ geom_point(aes(fill = Method, color = Disease, stroke = D, shape = Disease),\n+ size = 2, alpha = 0.7,\n+ position = position_jitter(width = 0.25, height = 0)) +\n+ facet_wrap(~ CellType, scales = "free") +\n+ scale_colour_manual(values = c("white", "gray20")) '..b'type_target), " vs. ",\n+ toupper(phenotype_scrna_target), " Cell Type Proportion")) +\n+ theme_minimal() +\n+ ylab(paste0("Proportion of ",\n+ phenotype_scrna_target, " cells")) +\n+ xlab(paste0("Level of bulk factor (", phenotype_target, ")")) +\n+ scale_colour_manual(values = c("white", "gray20")) +\n+ scale_shape_manual(values = c(21, 24)), maxyscale)\n+}\n \n ## BoxPlot\n-plot_box <- Boxplot_Est(list(\n+plot_box <- scale_yaxes(Boxplot_Est(list(\n data.matrix(estimated_music_props),\n data.matrix(estimated_nnls_props)),\n method.name = c("MuSiC", "NNLS")) +\n theme(axis.text.x = element_text(angle = -90),\n axis.text.y = element_text(size = 8)) +\n- ggtitle(element_blank()) + theme_minimal()\n+ ggtitle(element_blank()) + theme_minimal(), maxyscale)\n \n ## Heatmap\n plot_hmap <- Prop_heat_Est(list(\n@@ -125,8 +155,15 @@\n axis.text.y = element_text(size = 6))\n \n pdf(file = outfile_pdf, width = 8, height = 8)\n-plot_grid(jitter_fig, plot_box, labels = "auto", ncol = 1, nrow = 2)\n-plot_grid(jitter_new, jitt_compare, labels = "auto", ncol = 1, nrow = 2)\n+if (length(celltypes) <= 8) {\n+ plot_grid(jitter_fig, plot_box, labels = "auto", ncol = 1, nrow = 2)\n+} else {\n+ print(jitter_fig)\n+ plot_box\n+}\n+if (use_disease_factor) {\n+ plot_grid(jitter_new, jitt_compare, labels = "auto", ncol = 1, nrow = 2)\n+}\n plot_hmap\n message(dev.off())\n \n@@ -159,29 +196,32 @@\n quote = F, sep = "\\t", col.names = NA)\n \n \n-## Summary table\n-for (meth in methods) {\n- ##lm_beta_meth = lm(ct.prop ~ age + bmi + hba1c + gender, data =\n- sub_data <- subset(m_prop_ana, Method == meth)\n- ## We can only do regression where there are more than 1 factors\n- ## so we must find and exclude the ones which are not\n- gt1_facts <- sapply(phenotype_factors, function(facname) {\n- return(length(unique(sort(sub_data[[facname]]))) == 1)\n- })\n- form_factors <- phenotype_factors\n- exclude_facts <- names(gt1_facts)[gt1_facts]\n- if (length(exclude_facts) > 0) {\n- message("Factors with only one level will be excluded:")\n- message(exclude_facts)\n- form_factors <- phenotype_factors[\n- !(phenotype_factors %in% exclude_facts)]\n+if (use_disease_factor) {\n+ ## Summary table of linear regressions of disease factors\n+ for (meth in methods) {\n+ ##lm_beta_meth = lm(ct.prop ~ age + bmi + hba1c + gender, data =\n+ sub_data <- subset(m_prop_ana, Method == meth)\n+\n+ ## We can only do regression where there are more than 1 factors\n+ ## so we must find and exclude the ones which are not\n+ gt1_facts <- sapply(phenotype_factors, function(facname) {\n+ return(length(unique(sort(sub_data[[facname]]))) == 1)\n+ })\n+ form_factors <- phenotype_factors\n+ exclude_facts <- names(gt1_facts)[gt1_facts]\n+ if (length(exclude_facts) > 0) {\n+ message("Factors with only one level will be excluded:")\n+ message(exclude_facts)\n+ form_factors <- phenotype_factors[\n+ !(phenotype_factors %in% exclude_facts)]\n+ }\n+ lm_beta_meth <- lm(as.formula(\n+ paste("ct.prop", paste(form_factors, collapse = " + "),\n+ sep = " ~ ")), data = sub_data)\n+ message(paste0("Summary: ", meth))\n+ capture.output(summary(lm_beta_meth),\n+ file = paste0("report_data/summ_Log of ",\n+ meth,\n+ " fitting.txt"))\n }\n- lm_beta_meth <- lm(as.formula(\n- paste("ct.prop", paste(form_factors, collapse = " + "),\n- sep = " ~ ")), data = sub_data)\n- message(paste0("Summary: ", meth))\n- capture.output(summary(lm_beta_meth),\n- file = paste0("report_data/summ_Log of ",\n- meth,\n- " fitting.txt"))\n }\n' |
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| diff -r 817eb707bbf4 -r 577435e5e6b2 scripts/inspect.R --- a/scripts/inspect.R Fri Nov 26 15:54:31 2021 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 |
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| @@ -1,27 +0,0 @@ - -suppressWarnings(suppressPackageStartupMessages(library(xbioc))) -suppressWarnings(suppressPackageStartupMessages(library(MuSiC))) - -args <- commandArgs(trailingOnly = TRUE) -source(args[1]) - -printout <- function(text) { - if (typeof(text) %in% c("list", "vector", "integer", "double", "numeric")) { - write.table(text, file = outfile_tab, quote = F, sep = "\t", - col.names = NA) - } else { - ## text - print(typeof(text)) - capture.output(text, file = outfile_tab) # nolint - } -} - -if (inspector %in% c("print", "pData", "fData", "dims", - "experimentData", "protocolData", "exprs", - "signature", "annotation", "abstract")) { - op <- get(inspector) - tab <- op(rds_eset) - printout(tab) -} else { - stop(paste0("No such option:", inspector)) -} |
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| diff -r 817eb707bbf4 -r 577435e5e6b2 test-data/default_output_no_disease.pdf |
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| Binary file test-data/default_output_no_disease.pdf has changed |
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| diff -r 817eb707bbf4 -r 577435e5e6b2 test-data/mouse_scrna_exprs.tabular --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/mouse_scrna_exprs.tabular Sat Jan 29 12:51:27 2022 +0000 |
| b |
| b'@@ -0,0 +1,101 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|
| b |
| diff -r 817eb707bbf4 -r 577435e5e6b2 test-data/mouse_scrna_pheno.tabular --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/mouse_scrna_pheno.tabular Sat Jan 29 12:51:27 2022 +0000 |
| b |
| @@ -0,0 +1,101 @@ + sampleID SubjectName cellTypeID cellType +TGGTTCCGTCGGCTCA-2 2 Mouse2 3 PT +CGAGCCAAGCGTCAAG-4 4 Mouse4 5 DCT +GAATGAAGTTTGGGCC-5 5 Mouse5 3 PT +CTCGTACGTTGCCTCT-7 7 Mouse7 3 PT +TTCTCAATCCACGCAG-5 5 Mouse5 4 LOH +CCTTCCCCATACCATG-4 4 Mouse4 14 T lymph +ACTTTCACAGCTGGCT-7 7 Mouse7 3 PT +TGGGAAGCAAAGTGCG-7 7 Mouse7 3 PT +TCTATTGAGTAGGCCA-7 7 Mouse7 3 PT +TCGGTAACATCACGTA-2 2 Mouse2 3 PT +GGGTTGCCAGCTGTAT-2 2 Mouse2 2 Podo +TGCGGGTGTCATATCG-6 6 Mouse6 3 PT +ACTTGTTTCATATCGG-5 5 Mouse5 14 T lymph +CCAATCCCACGGCGTT-2 2 Mouse2 5 DCT +CTAAGACCACCAGGCT-7 7 Mouse7 3 PT +TTAACTCAGTAGGCCA-6 6 Mouse6 3 PT +GTACTCCGTAACGCGA-1 1 Mouse1 3 PT +GCCTCTAGTTGTACAC-2 2 Mouse2 3 PT +TTCGAAGTCCTGCAGG-3 3 Mouse3 3 PT +TTCTACAAGTTGTAGA-7 7 Mouse7 3 PT +CCGTTCAGTTGAACTC-7 7 Mouse7 7 CD-IC +GTGTTAGTCAGCTCGG-1 1 Mouse1 4 LOH +GGATTACGTGTGCGTC-6 6 Mouse6 3 PT +TACGGTATCCGTTGTC-6 6 Mouse6 3 PT +TTAGTTCGTATTAGCC-5 5 Mouse5 3 PT +CCCAATCGTAGCGATG-3 3 Mouse3 3 PT +ACACCAATCTGCGTAA-7 7 Mouse7 5 DCT +AATCCAGTCCAAACTG-7 7 Mouse7 5 DCT +CAGAATCAGCAATATG-1 1 Mouse1 3 PT +GCACATAAGCCGGTAA-5 5 Mouse5 5 DCT +CCTTCCCAGGAGTTTA-5 5 Mouse5 3 PT +CGGAGCTAGGACTGGT-5 5 Mouse5 4 LOH +TACGGATGTAAATGTG-4 4 Mouse4 3 PT +GGCAATTCATTCACTT-2 2 Mouse2 3 PT +CTCGGGAGTCTGCGGT-4 4 Mouse4 6 CD-PC +CATTCGCGTCCTCTTG-2 2 Mouse2 8 CD-Trans +CGCGTTTAGATCGATA-1 1 Mouse1 6 CD-PC +GGGTTGCCACCAACCG-4 4 Mouse4 7 CD-IC +TGTGTTTCATCGATGT-2 2 Mouse2 3 PT +AGAGTGGAGCTGTTCA-7 7 Mouse7 3 PT +CTCACACGTCTCACCT-3 3 Mouse3 3 PT +AGTTGGTTCCACGAAT-7 7 Mouse7 3 PT +ATCTGCCAGACCACGA-6 6 Mouse6 3 PT +TGTATTCCATTGAGCT-7 7 Mouse7 3 PT +TGAAAGAGTAGCCTAT-7 7 Mouse7 3 PT +AAATGCCAGAACTGTA-7 7 Mouse7 5 DCT +TTTGCGCTCTACCAGA-4 4 Mouse4 3 PT +ACATACGGTTTCCACC-6 6 Mouse6 3 PT +GCCTCTAGTTCCACAA-7 7 Mouse7 3 PT +GGGAGATGTACTCTCC-6 6 Mouse6 1 Endo +GAACGGATCTTGTACT-7 7 Mouse7 3 PT +TACCTTATCCTAGAAC-1 1 Mouse1 3 PT +GCGCGATAGATGCCAG-2 2 Mouse2 3 PT +GACAGAGCAAGTTGTC-7 7 Mouse7 3 PT +TGACTAGGTATGAATG-3 3 Mouse3 4 LOH +CACACTCAGTCACGCC-6 6 Mouse6 3 PT +ATTGGTGGTTAGGGTG-5 5 Mouse5 3 PT +AGCAGCCCAGCGTAAG-2 2 Mouse2 1 Endo +CATTCGCAGCCTTGAT-6 6 Mouse6 3 PT +GCGAGAACATAGACTC-2 2 Mouse2 14 T lymph +AGTCTTTGTAATAGCA-7 7 Mouse7 3 PT +TCGCGAGCAGACACTT-7 7 Mouse7 3 PT +CGGAGTCCAGCAGTTT-2 2 Mouse2 3 PT +GGTGTTACACACATGT-7 7 Mouse7 3 PT +TTCTCAAGTAAGTGTA-2 2 Mouse2 1 Endo +TGCTGCTAGTCAATAG-2 2 Mouse2 3 PT +GATGAGGTCTACCAGA-2 2 Mouse2 3 PT +ACATACGGTTGTACAC-5 5 Mouse5 3 PT +ACGAGGACAGCTATTG-7 7 Mouse7 4 LOH +CGATGTATCGGCGGTT-2 2 Mouse2 3 PT +CTGCGGATCACAACGT-2 2 Mouse2 13 B lymph +CGAACATAGTTGAGTA-5 5 Mouse5 3 PT +TAGTTGGTCGCGATCG-6 6 Mouse6 5 DCT +GCAGCCACAATGTAAG-4 4 Mouse4 1 Endo +CTCACACCAATAACGA-7 7 Mouse7 3 PT +CCTTTCTCATGAAGTA-2 2 Mouse2 7 CD-IC +AGTGTCAAGAGCAATT-7 7 Mouse7 3 PT +AGCATACGTAAAGGAG-1 1 Mouse1 6 CD-PC +ACACCAATCTCGCTTG-5 5 Mouse5 3 PT +GGGATGAGTATCAGTC-6 6 Mouse6 3 PT +TGACAACAGAAGCCCA-2 2 Mouse2 3 PT +CGAATGTTCACAATGC-1 1 Mouse1 1 Endo +GCACTCTTCCGCATAA-1 1 Mouse1 3 PT +CACCAGGTCCCAAGAT-2 2 Mouse2 3 PT +GTTACAGCACCGCTAG-6 6 Mouse6 3 PT +TAGCCGGCAGTACACT-2 2 Mouse2 11 Macro +ACGATGTGTTAAAGAC-2 2 Mouse2 9 Novel1 +CCTTCCCAGTCTCGGC-7 7 Mouse7 3 PT +TAGTGGTTCTCTGTCG-7 7 Mouse7 7 CD-IC +TAGCCGGAGGCTAGCA-5 5 Mouse5 7 CD-IC +TTGTAGGTCAGCACAT-1 1 Mouse1 4 LOH +GAATAAGCAGCTTCGG-7 7 Mouse7 3 PT +TCGCGAGAGTCCGGTC-3 3 Mouse3 14 T lymph +TCAACGAAGAGTAAGG-2 2 Mouse2 5 DCT +CAGGTGCCACGAAATA-5 5 Mouse5 3 PT +TGTGTTTCACTATCTT-2 2 Mouse2 3 PT +TGGCCAGAGTGAAGAG-6 6 Mouse6 3 PT +ACCAGTAAGTAGCCGA-2 2 Mouse2 6 CD-PC +GCGGGTTAGAAGGTTT-1 1 Mouse1 3 PT +CAGTCCTGTCATTAGC-2 2 Mouse2 7 CD-IC |