# HG changeset patch
# User recetox
# Date 1647965356 0
# Node ID 36104baf75da6c1bb7d842ead023b2b5e6c9bd7a
"planemo upload for repository https://github.com/RECETOX/galaxytools/tree/master/tools/ramclustr commit 4d2ac914c951166e386a94d8ebb8cb1becfac122"
diff -r 000000000000 -r 36104baf75da macros.xml
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/macros.xml Tue Mar 22 16:09:16 2022 +0000
@@ -0,0 +1,306 @@
+
+ 1.2.2
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+ not msp_output_details['merge_msp']
+
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+ msp_output_details['merge_msp']
+
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+
+
+ @article{Broeckling2014e,
+ abstract = {Metabolomic data are frequently acquired using chromatographically coupled mass spectrometry
+ (MS) platforms. For such datasets, the first step in data analysis relies on feature detection, where a
+ feature is defined by a mass and retention time. While a feature typically is derived from a single
+ compound, a spectrum of mass signals is more a more-accurate representation of the mass spectrometric
+ signal for a given metabolite. Here, we report a novel feature grouping method that operates in an
+ unsupervised manner to group signals from MS data into spectra without relying on predictability of the
+ in-source phenomenon. We additionally address a fundamental bottleneck in metabolomics, annotation of MS
+ level signals, by incorporating indiscriminant MS/MS (idMS/MS) data implicitly: feature detection is
+ performed on both MS and idMS/MS data, and feature-feature relationships are determined simultaneously
+ from the MS and idMS/MS data. This approach facilitates identification of metabolites using in-source MS
+ and/or idMS/MS spectra from a single experiment, reduces quantitative analytical variation compared to
+ single-feature measures, and decreases false positive annotations of unpredictable phenomenon as novel
+ compounds. This tool is released as a freely available R package, called RAMClustR, and is sufficiently
+ versatile to group features from any chromatographic-spectrometric platform or feature-finding software.
+ {\textcopyright} 2014 American Chemical Society.},
+ author = {Broeckling, C. D. and Afsar, F. A. and Neumann, S. and Ben-Hur, A. and Prenni, J. E.},
+ doi = {10.1021/ac501530d},
+ issn = {15206882},
+ journal = {Analytical Chemistry},
+ number = {14},
+ pages = {6812--6817},
+ pmid = {24927477},
+ title = {{RAMClust: A novel feature clustering method enables spectral-matching-based annotation for
+ metabolomics data}},
+ volume = {86},
+ year = {2014}
+ }
+
+
+
+
+
+
+
+
+
+ Background
+ Metabolomics
+ Metabolomics is frequently performed using chromatographically coupled mass spectrometry, with gas
+ chromatography, liquid chromatography, and capillary electrophoresis being the most frequently utilized
+ methods of separation. The coupling of chromatography to mass spectrometry is enabled with an
+ appropriate ionization source - electron impact (EI) for gas phase separations and electrospray
+ ionization (ESI) for liquid phase separations. XCMS is a commonly used tool to detect all the signals
+ from a metabolomics dataset, generating aligned features, where a feature is represented by a mass and
+ retention time. Each feature is presumed to derive from a single compound. However, each compound is
+ represented by several features. With any ionization method, isotopic peaks will be observed reflective
+ of the elemental composition of the analyte. In EI, fragmentation is a byproduct of ionization, and has
+ driven the generation of large mass spectral libraries. In ESI, in-source fragmentation frequently
+ occurs, the magnitude of which is compound dependent, with more labile compounds being more prone to
+ in-source fragmentation. ESI can also product multiple adduct forms (protonated, potassiated, sodiated,
+ ammoniated...), and can produce multimers (i.e. [2M+H]+, [3M+K]+, etc) and multiple charged species
+ ([M+2H]++). This can become further complicated by considering combinations of these phenomena. For
+ example [2M+3H]+++ (triply charged dimer) or an in-source fragment of a dimer.
+
+ RAMClustR approach
+ RAMClustR was designed to group features designed from the same compound using an approach which is
+ **1.** unsupervised, **2.** platform agnostic, and **3.** devoid of curated rules, as the depth of
+ understanding of these processes is insufficient to enable accurate curation/prediction of all phenomenon
+ that may occur. We achieve this by making two assumptions. The first is that two features derived
+ from the same compound with have (approximately) the same retention time. The second is that two
+ features derived from the same compound will have (approximately) the same quantitative trend across
+ all samples in the xcms sample set. From these assumptions, we can calculate a retention time
+ similarity score and a correlational similarity score for each feature pair. A high similarity score
+ for both retention time and correlation indicates a strong probability that two features derive from
+ the same compound. Since both conditions must be met, the product of the two similarity scores provides
+ the best approximation of the total similarity score - i.e. a feature pair with retention time similarity
+ of 1 and correlational similarity of 0 is unlikely to derive from one compound - 1 x 0 = 0, the final
+ similarity score is zero, indicating the two features represent two different compounds. Similarly, a
+ feature pair with retention time similarity of 0 and correlational similarity of 1 is unlikely to derive
+ from one compound - 0 x 1 = 0. Alternatively - a feature pair with retention time similarity of 1 and
+ correlational similarity of 1 is likely to derive from one compound - 1 x 1 = 1.
+
+ The RAMClustR algorithm is built on creating similarity scores for all pairs of features, submitting
+ this score matrix for hierarchical clustering, and then cutting the resulting dendrogram into neat
+ chunks using the dynamicTreeCut package - where each 'chunk' of the dendrogram results in a group of
+ features likely to be derived from a single compound. Importantly, this is achieved without looking for
+ specific phenomenon (i.e. sodiation), meaning that grouping can be performed on any dataset, whether it
+ is positive or negative ionization mode, EI or ESI, LC-MS GC-MS or CE-MS, in-source fragment or complex
+ adduction event, and predictable or unpredictable signals.
+
+
+
+
+
+
diff -r 000000000000 -r 36104baf75da ramclustr.xml
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/ramclustr.xml Tue Mar 22 16:09:16 2022 +0000
@@ -0,0 +1,175 @@
+
+
+ macros.xml
+
+
+
+
+ r-ramclustr
+ bioconductor-xcms
+
+
+
+
+
+
+ store_output(
+ #if $filetype.type_choice == "xcms":
+ ramclustr_xcms(
+ input_xcms = "$filetype.xcms.input_xcms",
+ use_pheno = $filetype.xcms.usePheno,
+ #else:
+ ramclustr_csv(
+ ms = "$filetype.ms_csv.ms",
+ idmsms = "$filetype.ms_csv.idmsms",
+ #end if
+ sr = $filetype.required.sr,
+ #if $filetype.type_choice == "xcms":
+ #if $filetype.required.st
+ st = $filetype.required.st,
+ #end if
+ #else:
+ st = $filetype.required.st,
+ #end if
+ cor_method = "$filetype.required.cor_method",
+ maxt = $filetype.required.maxt,
+ linkage = "$clustering.linkage",
+ min_module_size = $clustering.minModuleSize,
+ hmax = $clustering.hmax,
+ deep_split = "$clustering.deepSplit",
+ normalize = "$normalisation.normalisation_method.normalize",
+ #if "$normalisation.normalisation_method.normalize" == "batch.qc":
+ metadata_file = "$normalisation.normalisation_method.batch_order_qc",
+ qc_inj_range = $normalisation.normalisation_method.qc_inj_range,
+ #end if
+ block_size = $performance.blocksize,
+ mult = $performance.mult,
+ mzdec = $msp_output_details.mzdec,
+ rt_only_low_n = $extras.rt_only_low_n,
+ replace_zeros = $extras.replace_zeros,
+ #if $extras.ExpDes:
+ exp_design = "${$extras.ExpDes}"
+ #end if
+ ),
+ $msp_output_details.merge_msp,
+ "$spec_abundance",
+ #if $msp_output_details.merge_msp:
+ "$mass_spectra_merged"
+ #else:
+ NULL
+ #end if
+ )
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ `_
+ .. [2] Hierarchical Clustering - `stats::hclust `_
+ .. [3] Dynamic Dendrogram Pruning Based on Dendrogram Only - `dynamicTreeCut::cutreeDynamicTree `_
+ ]]>
+
+
+
+
diff -r 000000000000 -r 36104baf75da ramclustr_wrapper.R
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/ramclustr_wrapper.R Tue Mar 22 16:09:16 2022 +0000
@@ -0,0 +1,174 @@
+store_output <- function(
+ ramclustr_obj,
+ output_merge_msp,
+ output_spec_abundance,
+ msp_file) {
+ RAMClustR::write.msp(ramclustr_obj, one.file = output_merge_msp)
+ write.csv(ramclustr_obj$SpecAbund, file = output_spec_abundance, row.names = TRUE)
+
+ if (!is.null(msp_file)) {
+ exp.name <- ramclustr_obj$ExpDes[[1]][which(row.names(ramclustr_obj$ExpDes[[1]]) == "Experiment"), 1]
+ filename <- paste("spectra/", exp.name, ".msp", sep = "")
+ file.copy(from = filename, to = msp_file, overwrite = TRUE)
+ }
+}
+
+load_experiment_definition <- function(filename) {
+ experiment <- RAMClustR::defineExperiment(csv = filename)
+ return(experiment)
+}
+
+read_metadata <- function(filename) {
+ data <- read.csv(filename, header = TRUE, stringsAsFactors = FALSE)
+
+ if (!"qc" %in% colnames(data)) {
+ if ("sampleType" %in% colnames(data)) {
+ data$qc <- ifelse(data$sampleType == "qc", TRUE, FALSE)
+ }
+ }
+
+ if (!"order" %in% colnames(data)) {
+ if ("injectionOrder" %in% colnames(data)) {
+ names(data)[names(data) == "injectionOrder"] <- "order"
+ }
+ }
+
+ return(data)
+}
+
+ramclustr_xcms <- function(
+ input_xcms,
+ use_pheno,
+ sr,
+ st = NULL,
+ cor_method,
+ maxt,
+ linkage,
+ min_module_size,
+ hmax,
+ deep_split,
+ normalize,
+ metadata_file = NULL,
+ qc_inj_range,
+ block_size,
+ mult,
+ mzdec,
+ rt_only_low_n,
+ replace_zeros,
+ exp_design = NULL
+) {
+ obj <- load(input_xcms)
+
+ batch <- NULL
+ order <- NULL
+ qc <- NULL
+
+ if (!is.null(metadata_file)) {
+ metadata <- read_metadata(metadata_file)
+ batch <- metadata$batch
+ order <- metadata$order
+ qc <- metadata$qc
+ }
+
+ experiment <- NULL
+
+ if (!is.null(exp_design)) {
+ experiment <- load_experiment_definition(exp_design)
+ }
+
+ x <- RAMClustR::ramclustR(
+ xcmsObj = xdata,
+ st = st,
+ maxt = maxt,
+ sr = sr,
+ deepSplit = deep_split,
+ blocksize = block_size,
+ mult = mult,
+ hmax = hmax,
+ usePheno = use_pheno,
+ mspout = FALSE,
+ qc.inj.range = qc_inj_range,
+ normalize = normalize,
+ minModuleSize = min_module_size,
+ linkage = linkage,
+ mzdec = mzdec,
+ cor.method = cor_method,
+ rt.only.low.n = rt_only_low_n,
+ fftempdir = NULL,
+ replace.zeros = replace_zeros,
+ batch = batch,
+ order = order,
+ qc = qc,
+ ExpDes = experiment
+ )
+ return(x)
+}
+
+ramclustr_csv <- function(
+ ms,
+ idmsms,
+ sr,
+ st,
+ cor_method,
+ maxt,
+ linkage,
+ min_module_size,
+ hmax,
+ deep_split,
+ normalize,
+ metadata_file = NULL,
+ qc_inj_range,
+ block_size,
+ mult,
+ mzdec,
+ rt_only_low_n,
+ replace_zeros,
+ exp_design = NULL
+) {
+ if (!file.exists(idmsms))
+ idmsms <- NULL
+
+ batch <- NULL
+ order <- NULL
+ qc <- NULL
+
+ if (!is.null(metadata_file)) {
+ metadata <- read_metadata(metadata_file)
+ batch <- metadata$batch
+ order <- metadata$order
+ qc <- metadata$qc
+ }
+
+ experiment <- NULL
+
+ if (!is.null(exp_design)) {
+ experiment <- load_experiment_definition(exp_design)
+ }
+
+ x <- RAMClustR::ramclustR(
+ ms = ms,
+ idmsms = idmsms,
+ st = st,
+ maxt = maxt,
+ sr = sr,
+ deepSplit = deep_split,
+ blocksize = block_size,
+ mult = mult,
+ hmax = hmax,
+ mspout = FALSE,
+ qc.inj.range = qc_inj_range,
+ normalize = normalize,
+ minModuleSize = min_module_size,
+ linkage = linkage,
+ mzdec = mzdec,
+ cor.method = cor_method,
+ rt.only.low.n = rt_only_low_n,
+ fftempdir = NULL,
+ replace.zeros = replace_zeros,
+ batch = batch,
+ order = order,
+ qc = qc,
+ ExpDes = experiment
+ )
+ return(x)
+}
diff -r 000000000000 -r 36104baf75da test-data/gc-ramclustr-define-experiment.csv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/gc-ramclustr-define-experiment.csv Tue Mar 22 16:09:16 2022 +0000
@@ -0,0 +1,38 @@
+parameter,Value,Description
+,,
+Experimental Design,,
+Experiment,experiment_gc,"Experiment name, no spaces."
+Species,mus musculus,Genus species from which samples are derived.
+Sample,serum,"Type of sample (e.g., serum, leaf)."
+Contributer,recetox,Your or your PI's name.
+platform,GC-MS,Either GC-MS or LC-MS.
+,,
+GC-MS,,
+chrominst,ISQ 7000,Model of LC/GC instrument.
+msinst,ISQ7K-VPI,Model of MS instrument.
+column,These columns enable analysis of ppm levels of amines without column priming,Column description.
+InletTemp,33,Temperature of inlet.
+TransferTemp,23,Temperature of GC to MS transfer line.
+mstype,QTOF,"Type of mass spectrometer (one of QQQ, TOF, QTOF, Orbi, Q)."
+msmode,positive,Positive or negative ion mode.
+ionization,AP,"Ionization (EI, AP, or CI)."
+msscanrange,100,Scan range used for acquisition.
+scantime,0.2,Time for each full scan spectrum (e.g. 0.2 seconds).
+deriv,TMS,"Derivitization (TMS, TBDMS, or None)."
+MSlevs,1.0,Number of levels of energy acquired - 1 typically.
+,,
+LC-MS,,
+chrominst,fill,Model of LC/GC instrument.
+msinst,fill,Model of MS instrument.
+column,fill,Column description.
+solvA,fill,Solvent A composition.
+solvB,fill,Solvent B composition.
+CE1,fill,Collision energy of acquisition of MS data.
+CE2,fill,Collision energy of acquisition for MSe/idMSMS data (when applicable).
+mstype,fill,"Type of mass spectrometer (one of QQQ, TOF, QTOF, Orbi, Q)."
+msmode,fill,Positive or negative ion mode.
+ionization,fill,"Ionization (EI, AP, or CI)."
+colgas,fill,Gas used for collisional dissociation.
+msscanrange,fill,Scan range used for acquisition.
+conevol,fill,Cone voltage used for acquisition.
+MSlevs,fill,Number of levels of energy acquired - 1 typically.
diff -r 000000000000 -r 36104baf75da test-data/lc-ramclustr-define-experiment.csv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/lc-ramclustr-define-experiment.csv Tue Mar 22 16:09:16 2022 +0000
@@ -0,0 +1,38 @@
+parameter,Value,Description
+,,
+Experimental Design,,
+Experiment,experiment_lc,"Experiment name, no spaces."
+Species,mus musculus,Genus species from which samples are derived.
+Sample,serum,"Type of sample (e.g., serum, leaf)."
+Contributer,recetox,Your or your PI's name.
+platform,LC-MS,Either GC-MS or LC-MS.
+,,
+GC-MS,,
+chrominst,fill,Model of LC/GC instrument.
+msinst,fill,Model of MS instrument.
+column,fill,Column description.
+InletTemp,fill,Temperature of inlet.
+TransferTemp,fill,Temperature of GC to MS transfer line.
+mstype,fill,"Type of mass spectrometer (one of QQQ, TOF, QTOF, Orbi, Q)."
+msmode,fill,Positive or negative ion mode.
+ionization,fill,"Ionization (EI, AP, or CI)."
+msscanrange,fill,Scan range used for acquisition.
+scantime,fill,Time for each full scan spectrum (e.g. 0.2 seconds).
+deriv,fill,"Derivitization (TMS, TBDMS, or None)."
+MSlevs,fill,Number of levels of energy acquired - 1 typically.
+,,
+LC-MS,,
+chrominst,UltiMateX 3000 BioRS System,Model of LC/GC instrument.
+msinst,FSN04-10000,Model of MS instrument.
+column,These columns enable analysis of ppm levels of amines without column priming,Column description.
+solvA,H20,Solvent A composition.
+solvB,CO2,Solvent B composition.
+CE1,50,Collision energy of acquisition of MS data.
+CE2,100,Collision energy of acquisition for MSe/idMSMS data (when applicable).
+mstype,Q,"Type of mass spectrometer (one of QQQ, TOF, QTOF, Orbi, Q)."
+msmode,negative,Positive or negative ion mode.
+ionization,ESI,"Ionization (EI, AP, or CI)."
+colgas,He,Gas used for collisional dissociation.
+msscanrange,1000,Scan range used for acquisition.
+conevol,12,Cone voltage used for acquisition.
+MSlevs,1.0,Number of levels of energy acquired - 1 typically.
diff -r 000000000000 -r 36104baf75da test-data/test1_fill_xcms_1.msp
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/test1_fill_xcms_1.msp Tue Mar 22 16:09:16 2022 +0000
@@ -0,0 +1,1991 @@
+NAME:C001
+IONMODE:Negative
+SPECTRUMTYPE:Centroid
+RETENTIONTIME:38.74
+Num Peaks:57
+216.9205 32607700
+256.8215 31377637
+175.0641 26780143
+206.9034 26130980
+254.8252 23747536
+198.8647 21688594
+196.8658 21390430
+372.7383 19374863
+258.8237 15532799
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+392.7685 10913351
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+440.7322 10603010
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+486.7743 4886062
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+349.9455 2050695
+612.6927 2005587
+676.6436 1982714
+351.941 1965882
+148.9337 1008656
+
+NAME:C002
+IONMODE:Negative
+SPECTRUMTYPE:Centroid
+RETENTIONTIME:520.25
+Num Peaks:35
+525.375 1073323842
+310.1623 295359836
+526.3783 181668883
+1047.7378 150394804
+551.3321 111616808
+1048.7399 90978863
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+
+NAME:C003
+IONMODE:Negative
+SPECTRUMTYPE:Centroid
+RETENTIONTIME:483.67
+Num Peaks:26
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+523.354 1201714423
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+
+NAME:C004
+IONMODE:Negative
+SPECTRUMTYPE:Centroid
+RETENTIONTIME:473.48
+Num Peaks:24
+496.34 12577588056
+497.3442 3337125302
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+
+NAME:C005
+IONMODE:Negative
+SPECTRUMTYPE:Centroid
+RETENTIONTIME:41.72
+Num Peaks:20
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+
+NAME:C006
+IONMODE:Negative
+SPECTRUMTYPE:Centroid
+RETENTIONTIME:452.08
+Num Peaks:19
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+
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diff -r 000000000000 -r 36104baf75da test-data/test1_spec_abundance_xcms_1.csv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/test1_spec_abundance_xcms_1.csv Tue Mar 22 16:09:16 2022 +0000
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diff -r 000000000000 -r 36104baf75da test-data/test1_xcmsObj_1.rdata.xcms.fillpeaks
Binary file test-data/test1_xcmsObj_1.rdata.xcms.fillpeaks has changed
diff -r 000000000000 -r 36104baf75da test-data/test2_fill_xcms_2.msp
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/test2_fill_xcms_2.msp Tue Mar 22 16:09:16 2022 +0000
@@ -0,0 +1,11378 @@
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+NAME:C945
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+NAME:C946
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+NAME:C947
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+NAME:C948
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+NAME:C949
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diff -r 000000000000 -r 36104baf75da test-data/test2_sample_metadata_xcms_2.csv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/test2_sample_metadata_xcms_2.csv Tue Mar 22 16:09:16 2022 +0000
@@ -0,0 +1,6 @@
+sample_name,class,sampleType,injectionOrder,batch
+VT_160120_002,sample,sample,1,1
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+VT_160120_006,sample,sample,3,1
+VT_160120_008,sample,sample,4,1
+VT_160120_010,sample,sample,5,1
diff -r 000000000000 -r 36104baf75da test-data/test2_spec_abundance_xcms_2.csv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/test2_spec_abundance_xcms_2.csv Tue Mar 22 16:09:16 2022 +0000
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diff -r 000000000000 -r 36104baf75da test-data/test2_xcmsObj_2.rdata.xcms.fillpeaks
Binary file test-data/test2_xcmsObj_2.rdata.xcms.fillpeaks has changed
diff -r 000000000000 -r 36104baf75da test-data/test3_csv_test-input_1_2.csv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/test3_csv_test-input_1_2.csv Tue Mar 22 16:09:16 2022 +0000
@@ -0,0 +1,4 @@
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diff -r 000000000000 -r 36104baf75da test-data/test3_spec_abundance_csv_1.csv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
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diff -r 000000000000 -r 36104baf75da test-data/test3_spectra_csv_1.msp
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
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diff -r 000000000000 -r 36104baf75da test-data/test4_sample_metadata_csv_2.csv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/test4_sample_metadata_csv_2.csv Tue Mar 22 16:09:16 2022 +0000
@@ -0,0 +1,4 @@
+sample_name,class,sampleType,injectionOrder,batch
+dataset_10908,sample,sample,1,1
+dataset_10909,sample,sample,2,1
+dataset_10910,sample,sample,3,1
diff -r 000000000000 -r 36104baf75da test-data/test4_spec_abundance_csv_2.csv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/test4_spec_abundance_csv_2.csv Tue Mar 22 16:09:16 2022 +0000
@@ -0,0 +1,4 @@
+"","C01","C02","C03","C04","C05","C06","C07","C08","C09","C10","C11","C12","C13","C14","C15","C16","C17","C18","C19","C20","C21","C22","C23","C24","C25","C26","C27","C28","C29","C30","C31","C32","C33","C34","C35","C36","C37","C38"
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+"dataset_10910",15486747.5366514,705676.707142857,29822.3430533531,224421.528087479,240472.056093119,83802.7176826829,53891.3450571771,46940.0774103402,22283.2365363616,398852.491270866,16487.928248967,1983470.1118411,11998.5253787137,55783.8355817233,185478.847522515,315657.07173388,39349.4112699936,21728.8824232737,32441.4747147792,119901.384914687,461198.718995128,19834.4473795901,43602.3586534436,31889.6464337142,68360.3997127846,21854.49991187,1073398.26666055,156861.055191184,493341.849474475,16176.4044227296,10125.6569474277,37890.4782477985,29454.7192721113,66717.3172710142,4822.46628554095,24485.0599767888,21288.8896720112,103775.906887161
diff -r 000000000000 -r 36104baf75da test-data/test4_spectra_csv_2.msp
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/test4_spectra_csv_2.msp Tue Mar 22 16:09:16 2022 +0000
@@ -0,0 +1,430 @@
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