Mercurial > repos > fgiacomoni > xseekerpreparator
diff XSeekerPreparator.R @ 0:1660665c081e draft
#issue9 branch Updating - - Fxx
| author | fgiacomoni |
|---|---|
| date | Thu, 19 Nov 2020 14:28:46 +0000 |
| parents | |
| children |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/XSeekerPreparator.R Thu Nov 19 14:28:46 2020 +0000 @@ -0,0 +1,917 @@ + + +TOOL_NAME <- "XSeekerPreparator" +VERSION <- "1.1.2" + +OUTPUT_SPECIFIC_TOOL <- "XSeeker_Galaxy" + +ENRICHED_RDATA_VERSION <- paste("1.1.2", OUTPUT_SPECIFIC_TOOL, sep="-") +ENRICHED_RDATA_DOC <- sprintf(" +Welcome to the enriched <Version %s> of the output of CAMERA/xcms. +This doc was generated by the tool: %s - Version %s +To show the different variables contained in this rdata, type: + - `load('this_rdata.rdata', rdata_env <- new.env())` + - `names(rdata_env)` + +Sections +###### + + +This tools helpers +------ + The version number is somewhat special because the evolution of the + rdata's format is non-linear. + There may be different branches, each evolving separatly. + To reflect these branches's diversions, there may be a prepended + branch name following this format: + major.minor.patch-branch_name + Like this, we can process rdata with the same tool, and output + rdata formated differently, for each tool. + + + - enriched_rdata: + - Description: flag created by that tool to tell it was enriched. + - Retrieval method: enriched_rdata <- TRUE + + - enriched_rdata_version: + - Description: A flag created by that tool to tell which version of + this tool has enriched the rdata. + - Retrieval method: enriched_rdata_version <- sprintf(\"%s\", ENRICHED_RDATA_VERSION) + + - enriched_rdata_doc: + - Description: Contains the documentation string. + +Data from original mzxml file +------ + - tic: + - Description: Those are the tic values from the original mzxml + file, extracted using xcms 2. + - Retrieval method: xcms::xcmsRaw('original_file.mzxml')@tic + - xcms version: 2.0 + + - mz: + - Description: Those are the m/z values from the original mzxml + file, extracted using xcms 2. + - Retrieval method: xcms::xcmsRaw('original_file.mzxml')@env$mz + - xcms version: 2.0 + + - scanindex: + - Description: Those are the scanindex values from the original mzxml + file, extracted using xcms 2. + - Retrieval method: xcms::xcmsRaw('original_file.mzxml')@scanindex + - xcms version: 2.0 + + - scantime: + - Description: Those are the scantime values from the original mzxml + file, extracted using xcms 2. + - Retrieval method: xcms::xcmsRaw('original_file.mzxml')@scantime + - xcms version: 2.0 + + - intensity: + - Description: Those are the intensity values from the original mzxml + file, extracted using xcms 2. + - Retrieval method: xcms::xcmsRaw('original_file.mzxml')@env$intensity + - xcms version: 2.0 + + - polarity: + - Description: Those are the polarity values from the original mzxml + file, extracted using xcms 2. + - Retrieval method: as.character(xcms::xcmsRaw('original_file.mzxml')@polarity[[1]]) + - xcms version: 2.0 + +Data taken from incoming rdata +------ + - variableMetadata: + - Description: Unmodified copy of variableMetadata from incoming rdata. + - Retrieval method: rdata_file$variableMetadata + + - process_params: + - Description: Those are the processing parameters values from the + curent rdata. They have been simplified to allow easy access like: + for (params in process_params) { + if (params[[\"xfunction\"]] == \"annotatediff\") { + process_peak_picking_params(params) + } + } + - Retrieval method: + ## just he same list, but simplified + process_params <- list() + for (list_name in names(rdata_file$listOFlistArguments)) { + param_list <- list() + for (param_name in names(rdata_file$listOFlistArguments[[list_name]])) { + param_list[[param_name]] <- rdata_file$listOFlistArguments[[list_name]][[param_name]] + } + process_params[[length(process_params)+1]] <- param_list + } +", ENRICHED_RDATA_VERSION, TOOL_NAME, VERSION, ENRICHED_RDATA_VERSION) + + + +get_models <- function(path) { + if (is.null(path)) { + stop("No models to define the database schema") + } else { + message(sprintf("Loading models from %s", path)) + } + ## galaxy mangles the "@" to a "__at__" + if (substr(path, 1, 9) == "git__at__") { + path <- sub("^git__at__", "git@", path, perl=TRUE) + } + if ( + substr(path, 1, 4) == "git@" + || substr(path, length(path)-4, 4) == ".git" + ) { + return (get_models_from_git(path)) + } + if (substr(path, 1, 4) == "http") { + return (get_models_from_url(path)) + } + return (source(path)$value) +} + +get_models_from_git <- function (url, target_file="models.R", rm=TRUE) { + tmp <- tempdir() + message(sprintf("Cloning %s", url)) + system2("git", c("clone", url, tmp)) + result <- search_tree(file.path(tmp, dir), target_file) + if (!is.null(result)) { + models <- source(result)$value + if (rm) { + unlink(tmp, recursive=TRUE) + } + return (models) + } + if (rm) { + unlink(tmp, recursive=TRUE) + } + stop(sprintf( + "Could not find any file named \"%s\" in this repo", + target_file + )) +} + +get_models_from_url <- function (url, target_file="models.R", rm=TRUE) { + tmp <- tempdir() + message(sprintf("Downloading %s", url)) + result <- file.path(tmp, target_file) + if (download.file(url, destfile=result) == 0) { + models <- source(result)$value + if (rm) { + unlink(tmp, recursive=TRUE) + } + return (models) + } + if (rm) { + unlink(tmp, recursive=TRUE) + } + stop("Could not download any file at this adress.") +} + +search_tree <- function(path, target) { + target <- tolower(target) + for (file in list.files(path)) { + if (is.dir(file)) { + result <- search_tree(file.path(path, file), target) + if (!is.null(result)) { + return (result) + } + } else if (tolower(file) == target) { + return (file.path(path, file)) + } + } + return (NULL) +} + +create_database <- function(orm) { + orm$recreate_database(no_exists=FALSE) + set_database_version(orm, "created") +} + +insert_adducts <- function(orm) { + message("Creating adducts...") + adducts <- list( + list("[M-H2O-H]-",1,-1,-48.992020312000001069,1,0,0.5,"H0","H1O3"), + list("[M-H-Cl+O]-",1,-1,-19.981214542000000022,2,0,0.5,"O1","H1Cl1"), + list("[M-Cl+O]-",1,-1,-18.973389510000000512,3,0,0.5,"O1","Cl1"), + list("[M-3H]3-",1,-3,-3.0218293560000000219,4,0,1.0,"H0","H3"), + list("[2M-3H]3-",2,-3,-3.0218293560000000219,4,0,0.5,"H0","H3"), + list("[3M-3H]3-",3,-3,-3.0218293560000000219,4,0,0.5,"H0","H3"), + list("[M-2H]2-",1,-2,-2.0145529039999998666,5,0,1.0,"H0","H2"), + list("[2M-2H]2-",2,-2,-2.0145529039999998666,5,0,0.5,"H0","H2"), + list("[3M-2H]2-",3,-2,-2.0145529039999998666,5,0,0.5,"H0","H2"), + list("[M-H]-",1,-1,-1.0072764519999999333,6,1,1.0,"H0","H1"), + list("[2M-H]-",2,-1,-1.0072764519999999333,6,0,0.5,"H0","H1"), + list("[3M-H]-",3,-1,-1.0072764519999999333,6,0,0.5,"H0","H1"), + list("[M]+",1,1,-0.00054858000000000000945,7,1,1.0,"H0","H0"), + list("[M]-",1,-1,0.00054858000000000000945,8,1,1.0,"H0","H0"), + list("[M+H]+",1,1,1.0072764519999999333,9,1,1.0,"H1","H0"), + list("[2M+H]+",2,1,1.0072764519999999333,9,0,0.5,"H1","H0"), + list("[3M+H]+",3,1,1.0072764519999999333,9,0,0.25,"H1","H0"), + list("[M+2H]2+",1,2,2.0145529039999998666,10,0,0.75,"H2","H0"), + list("[2M+2H]2+",2,2,2.0145529039999998666,10,0,0.5,"H2","H0"), + list("[3M+2H]2+",3,2,2.0145529039999998666,10,0,0.25,"H2","H0"), + list("[M+3H]3+",1,3,3.0218293560000000219,11,0,0.75,"H3","H0"), + list("[2M+3H]3+",2,3,3.0218293560000000219,11,0,0.5,"H3","H0"), + list("[3M+3H]3+",3,3,3.0218293560000000219,11,0,0.25,"H3","H0"), + list("[M-2H+NH4]-",1,-1,16.019272654000001665,12,0,0.25,"N1H4","H2"), + list("[2M-2H+NH4]-",2,-1,16.019272654000001665,12,0,0.0,"N1H4","H2"), + list("[3M-2H+NH4]-",3,-1,16.019272654000001665,12,0,0.25,"N1H4","H2"), + list("[M+NH4]+",1,1,18.033825558000000199,13,1,1.0,"N1H4","H0"), + list("[2M+NH4]+",2,1,18.033825558000000199,13,0,0.5,"N1H4","H0"), + list("[3M+NH4]+",3,1,18.033825558000000199,13,0,0.25,"N1H4","H0"), + list("[M+H+NH4]2+",1,2,19.041102009999999467,14,0,0.5,"N1H5","H0"), + list("[2M+H+NH4]2+",2,2,19.041102009999999467,14,0,0.5,"N1H5","H0"), + list("[3M+H+NH4]2+",3,2,19.041102009999999467,14,0,0.25,"N1H5","H0"), + list("[M+Na-2H]-",1,-1,20.974668176000001551,15,0,0.75,"Na1","H2"), + list("[2M-2H+Na]-",2,-1,20.974668176000001551,15,0,0.25,"Na1","H2"), + list("[3M-2H+Na]-",3,-1,20.974668176000001551,15,0,0.25,"Na1","H2"), + list("[M+Na]+",1,1,22.989221080000000086,16,1,1.0,"Na1","H0"), + list("[2M+Na]+",2,1,22.989221080000000086,16,0,0.5,"Na1","H0"), + list("[3M+Na]+",3,1,22.989221080000000086,16,0,0.25,"Na1","H0"), + list("[M+H+Na]2+",1,2,23.996497531999999353,17,0,0.5,"Na1H1","H0"), + list("[2M+H+Na]2+",2,2,23.996497531999999353,17,0,0.5,"Na1H1","H0"), + list("[3M+H+Na]2+",3,2,23.996497531999999353,17,0,0.25,"Na1H1","H0"), + list("[M+2H+Na]3+",1,3,25.003773983999998619,18,0,0.25,"H2Na1","H0"), + list("[M+CH3OH+H]+",1,1,33.033491200000000276,19,0,0.25,"C1O1H5","H0"), + list("[M-H+Cl]2-",1,-2,33.962124838000001148,20,0,1.0,"Cl1","H1"), + list("[2M-H+Cl]2-",2,-2,33.962124838000001148,20,0,0.5,"Cl1","H1"), + list("[3M-H+Cl]2-",3,-2,33.962124838000001148,20,0,0.5,"Cl1","H1"), + list("[M+Cl]-",1,-1,34.969401290000000416,21,1,1.0,"Cl1","H0"), + list("[2M+Cl]-",2,-1,34.969401290000000416,21,0,0.5,"Cl1","H0"), + list("[3M+Cl]-",3,-1,34.969401290000000416,21,0,0.5,"Cl1","H0"), + list("[M+K-2H]-",1,-1,36.948605415999999479,22,0,0.5,"K1","H2"), + list("[2M-2H+K]-",2,-1,36.948605415999999479,22,0,0.0,"K1","H2"), + list("[3M-2H+K]-",3,-1,36.948605415999999479,22,0,0.0,"K1","H2"), + list("[M+K]+",1,1,38.963158319999998013,23,1,1.0,"K1","H0"), + list("[2M+K]+",2,1,38.963158319999998013,23,0,0.5,"K1","H0"), + list("[3M+K]+",3,1,38.963158319999998013,23,0,0.25,"K1","H0"), + list("[M+H+K]2+",1,2,39.970434771999997281,24,0,0.5,"K1H1","H0"), + list("[2M+H+K]2+",2,2,39.970434771999997281,24,0,0.5,"K1H1","H0"), + list("[3M+H+K]2+",3,2,39.970434771999997281,24,0,0.25,"K1H1","H0"), + list("[M+ACN+H]+",1,1,42.033825557999996646,25,0,0.25,"C2H4N1","H0"), + list("[2M+ACN+H]+",2,1,42.033825557999996646,25,0,0.25,"C2H4N1","H0"), + list("[M+2Na-H]+",1,1,44.971165708000000902,26,0,0.5,"Na2","H1"), + list("[2M+2Na-H]+",2,1,44.971165708000000902,26,0,0.25,"Na2","H1"), + list("[3M+2Na-H]+",3,1,44.971165708000000902,26,0,0.25,"Na2","H1"), + list("[2M+FA-H]-",2,-1,44.998202851999998586,27,0,0.25,"C1O2H2","H1"), + list("[M+FA-H]-",1,-1,44.998202851999998586,27,0,0.5,"C1O2H2","H1"), + list("[M+2Na]2+",1,2,45.978442160000000172,28,0,0.5,"Na2","H0"), + list("[2M+2Na]2+",2,2,45.978442160000000172,28,0,0.5,"Na2","H0"), + list("[3M+2Na]2+",3,2,45.978442160000000172,28,0,0.25,"Na2","H0"), + list("[M+H+2Na]3+",1,3,46.985718611999999438,29,0,0.25,"H1Na2","H0"), + list("[M+H+FA]+",1,1,47.012755755999997122,30,0,0.25,"C1O2H3","H0"), + list("[M+Hac-H]-",1,-1,59.013852915999997607,31,0,0.25,"C2O2H4","H1"), + list("[2M+Hac-H]-",2,-1,59.013852915999997607,31,0,0.25,"C2O2H4","H1"), + list("[M+IsoProp+H]+",1,1,61.064791327999998317,32,0,0.25,"C3H9O1","H0"), + list("[M+Na+K]2+",1,2,61.9523793999999981,33,0,0.5,"Na1K1","H0"), + list("[2M+Na+K]2+",2,2,61.9523793999999981,33,0,0.5,"Na1K1","H0"), + list("[3M+Na+K]2+",3,2,61.9523793999999981,33,0,0.25,"Na1K1","H0"), + list("[M+NO3]-",1,-1,61.988366450000000895,34,0,0.5,"N1O3","H0"), + list("[M+ACN+Na]+",1,1,64.015770185999997464,35,0,0.25,"C2H3N1Na1","H0"), + list("[2M+ACN+Na]+",2,1,64.015770185999997464,35,0,0.25,"C2H3N1Na1","H0"), + list("[M+NH4+FA]+",1,1,64.039304861999994502,36,0,0.25,"N1C1O2H6","H0"), + list("[M-2H+Na+FA]-",1,-1,66.980147479999999405,37,0,0.5,"NaC1O2H2","H2"), + list("[M+3Na]3+",1,3,68.967663239999993153,38,0,0.25,"Na3","H0"), + list("[M+Na+FA]+",1,1,68.99470038399999794,39,0,0.25,"Na1C1O2H2","H0"), + list("[M+2Cl]2-",1,-2,69.938802580000000832,40,0,1.0,"Cl2","H0"), + list("[2M+2Cl]2-",2,-2,69.938802580000000832,40,0,0.5,"Cl2","H0"), + list("[3M+2Cl]2-",3,-2,69.938802580000000832,40,0,0.5,"Cl2","H0"), + list("[M+2K-H]+",1,1,76.919040187999996758,41,0,0.5,"K2","H1"), + list("[2M+2K-H]+",2,1,76.919040187999996758,41,0,0.25,"K2","H1"), + list("[3M+2K-H]+",3,1,76.919040187999996758,41,0,0.25,"K2","H1"), + list("[M+2K]2+",1,2,77.926316639999996028,42,0,0.5,"K2","H0"), + list("[2M+2K]2+",2,2,77.926316639999996028,42,0,0.5,"K2","H0"), + list("[3M+2K]2+",3,2,77.926316639999996028,42,0,0.25,"K2","H0"), + list("[M+Br]-",1,-1,78.918886479999997619,43,1,1.0,"Br1","H0"), + list("[M+Cl+FA]-",1,-1,80.974880593999998268,44,0,0.5,"Cl1C1O2H2","H0"), + list("[M+AcNa-H]-",1,-1,80.995797543999998426,45,0,0.25,"C2H3Na1O2","H1"), + list("[M+2ACN+2H]2+",1,2,84.067651115999993292,46,0,0.25,"C4H8N2","H0"), + list("[M+K+FA]+",1,1,84.968637623999995868,47,0,0.25,"K1C1O2H2","H0"), + list("[M+Cl+Na+FA-H]-",1,-1,102.95682522200000619,48,0,0.5,"Cl1Na1C1O2H2","H1"), + list("[2M+3H2O+2H]+",2,1,104.03153939599999944,49,0,0.25,"H8O6","H0"), + list("[M+TFA-H]-",1,-1,112.98558742000000165,50,0,0.5,"C2F3O2H1","H1"), + list("[M+H+TFA]+",1,1,115.00014032400000019,51,0,0.25,"C2F3O2H2","H0"), + list("[M+3ACN+2H]2+",1,2,125.09420022199999778,52,0,0.25,"C6H11N3","H0"), + list("[M+NH4+TFA]+",1,1,132.02668943000000468,53,0,0.25,"N1C2F3O2H5","H0"), + list("[M+Na+TFA]+",1,1,136.98208495200000811,54,0,0.25,"Na1C2F3O2H1","H0"), + list("[M+Cl+TFA]-",1,-1,148.96226516199999423,55,0,0.5,"Cl1C2F3O2H1","H0"), + list("[M+K+TFA]+",1,1,152.95602219200000604,56,0,0.25,"K1C2F3O2H1","H0") + ) + dummy_adduct <- orm$adduct() + for (adduct in adducts) { + i <- 0 + dummy_adduct$set_name(adduct[[i <- i+1]]) + dummy_adduct$set_multi(adduct[[i <- i+1]]) + dummy_adduct$set_charge(adduct[[i <- i+1]]) + dummy_adduct$set_mass(adduct[[i <- i+1]]) + dummy_adduct$set_oidscore(adduct[[i <- i+1]]) + dummy_adduct$set_quasi(adduct[[i <- i+1]]) + dummy_adduct$set_ips(adduct[[i <- i+1]]) + dummy_adduct$set_formula_add(adduct[[i <- i+1]]) + dummy_adduct$set_formula_ded(adduct[[i <- i+1]]) + dummy_adduct$save() + dummy_adduct$clear(unset_id=TRUE) + } + message("Adducts created") +} + +insert_base_data <- function(orm, path, archetype=FALSE) { + if (archetype) { + ## not implemented yet + return () + } + base_data <- readLines(path) + for (sql in strsplit(paste(base_data, collapse=" "), ";")[[1]]) { + orm$execute(sql) + } + set_database_version(orm, "enriched") +} + +insert_compounds <- function(orm, compounds_path) { + compounds <- read.csv(file=compounds_path, sep="\t") + if (is.null(compounds <- translate_compounds(compounds))) { + stop("Could not find asked compound's attributes in csv file.") + } + dummy_compound <- orm$compound() + compound_list <- list() + for (i in seq_len(nrow(compounds))) { + dummy_compound$set_mz(compounds[i, "mz"]) + dummy_compound$set_name(compounds[i, "name"]) + dummy_compound$set_common_name(compounds[i, "common_name"]) + dummy_compound$set_formula(compounds[i, "formula"]) + # dummy_compound$set_mz(compounds[i, "mz"]) + # dummy_compound$set_mz(compounds[i, "mz"]) + compound_list[[length(compound_list)+1]] <- as.list( + dummy_compound, + c("mz", "name", "common_name", "formula") + ) + dummy_compound$clear(unset_id=TRUE) + } + dummy_compound$save(bulk=compound_list) +} + +translate_compounds <- function(compounds) { + recognized_headers <- list( + c("HMDB_ID", "MzBank", "X.M.H..", "X.M.H...1", "MetName", "ChemFormula", "INChIkey") + ) + header_translators <- list( + hmdb_header_translator + ) + for (index in seq_along(recognized_headers)) { + headers <- recognized_headers[[index]] + if (identical(colnames(compounds), headers)) { + return (header_translators[[index]](compounds)) + } + } + if (is.null(translator <- guess_translator(colnames(compounds)))) { + return (NULL) + } + return (csv_header_translator(translator, compounds)) +} + +guess_translator <- function(header) { + result <- list( + # HMDB_ID=NULL,< + mz=NULL, + name=NULL, + common_name=NULL, + formula=NULL, + # inchi_key=NULL + ) + asked_cols <- names(result) + for (asked_col in asked_cols) { + for (col in header) { + if ((twisted <- tolower(col)) == asked_col + || gsub("-", "_", twisted) == asked_col + || gsub(" ", "_", twisted) == asked_col + || tolower(gsub("(.)([A-Z])", "\\1_\\2", col)) == asked_col + ) { + result[[asked_col]] <- col + next + } + } + } + if (any(mapply(is.null, result))) { + return (NULL) + } + return (result) +} + +hmdb_header_translator <- function(compounds) { + return (csv_header_translator( + list( + HMDB_ID="HMDB_ID", + mz="MzBank", + name="MetName", + common_name="MetName", + formula="ChemFormula", + inchi_key="INChIkey" + ), compounds + )) +} + +csv_header_translator <- function(translation_table, csv) { + header_names <- names(translation_table) + result <- data.frame(1:nrow(csv)) + # colnames(result) <- header_names + for (i in seq_along(header_names)) { + result[, header_names[[i]]] <- csv[, translation_table[[i]]] + } + print(result[, "mz"]) + result[, "mz"] <- as.numeric(result[, "mz"]) + print(result[, "mz"]) + return (result) +} + +set_database_version <- function(orm, version) { + orm$set_tag( + version, + tag_name="database_version", + tag_table_name="XSeeker_tagging_table" + ) +} + +process_rdata <- function(orm, rdata, options) { + mzml_tmp_dir <- gather_mzml_files(rdata) + samples <- names(rdata$singlefile) + if (!is.null(options$samples)) { + samples <- samples[options$samples %in% samples] + } + show_percent <- ( + is.null(options$`not-show-percent`) + || options$`not-show-percent` == FALSE + ) + error <- tryCatch({ + process_sample_list( + orm, rdata, samples, + show_percent=show_percent + ) + NULL + }, error=function(e) { + message(e) + e + }) + if (!is.null(mzml_tmp_dir)) { + unlink(mzml_tmp_dir, recursive=TRUE) + } + if (!is.null(error)) { + stop(error) + } +} + +gather_mzml_files <- function(rdata) { + if (is.null(rdata$singlefile)) { + message("Extracting mxml files") + tmp <- tempdir() + rdata$singlefile <- utils::unzip(rdata$zipfile, exdir=tmp) + names(rdata$singlefile) <- tools::file_path_sans_ext(basename(rdata$singlefile)) + message("Extracted") + return (tmp) + } + return (NULL) +} + +process_sample_list <- function(orm, radta, sample_names, show_percent) { + file_grouping_var <- find_grouping_var(rdata$variableMetadata) + message("Processing samples.") + message(sprintf("File grouping variable: %s", file_grouping_var)) + if(is.null(file_grouping_var)) { + stop("Malformed variableMetada.") + } + + process_arg_list <- rdata$listOFlistArguments + process_params <- list() + for (list_name in names(process_arg_list)) { + param_list <- list() + for (param_name in names(process_arg_list[[list_name]])) { + param_list[[param_name]] <- process_arg_list[[list_name]][[param_name]] + } + process_params[[length(process_params)+1]] <- param_list + } + message("Parameters from previous processes extracted.") + + var_meta <- rdata$variableMetadata + align_group <- rep(0, nrow(var_meta)) + var_meta <- cbind(var_meta, align_group) + context <- new.env() + context$clusters <- list() + context$groupidx <- rdata$xa@xcmsSet@groupidx + context$peaks <- rdata$xa@xcmsSet@peaks + context$show_percent <- show_percent + + indices <- as.numeric(unique(var_meta[, file_grouping_var])) + smol_xcms_set <- orm$smol_xcms_set() + mz_tab_info <- new.env() + xcms_set <- rdata$xa@xcmsSet + g <- xcms::groups(xcms_set) + mz_tab_info$group_length <- nrow(g) + mz_tab_info$dataset_path <- xcms::filepaths(xcms_set) + mz_tab_info$sampnames <- xcms::sampnames(xcms_set) + mz_tab_info$sampclass <- xcms::sampclass(xcms_set) + mz_tab_info$rtmed <- g[,"rtmed"] + mz_tab_info$mzmed <- g[,"mzmed"] + mz_tab_info$smallmolecule_abundance_assay <- xcms::groupval(xcms_set, value="into") + blogified <- blob::blob(fst::compress_fst(serialize(mz_tab_info, NULL), compression=100)) + smol_xcms_set$set_raw(blogified)$save() + for (no in indices) { + sample_name <- names(rdata$singlefile)[[no]] + sample_path <- rdata$singlefile[[no]] + if ( + is.na(no) + || is.null(sample_path) + || !(sample_name %in% sample_names) + ) { + next + } + ms_file=xcms::xcmsRaw(sample_path) + env <- new.env() + env$variableMetadata <- var_meta[var_meta[, file_grouping_var]==no,] + env$tic <- ms_file@tic + env$mz <- ms_file@env$mz + env$scanindex <- ms_file@scanindex + env$scantime <- ms_file@scantime + env$intensity <- ms_file@env$intensity + env$polarity <- as.character(ms_file@polarity[[1]]) + env$sample_name <- sample_name + env$dataset_path <- sample_path + env$process_params <- process_params + env$enriched_rdata <- TRUE + env$enriched_rdata_version <- ENRICHED_RDATA_VERSION + env$tool_name <- TOOL_NAME + env$enriched_rdata_doc <- ENRICHED_RDATA_DOC + context$sample_no <- no + add_sample_to_database(orm, env, context, smol_xcms_set) + } + message("Features enrichment") + complete_features(orm, context) + message("Features enrichment done.") + return (NULL) +} + +find_grouping_var <- function(var_meta) { + for (grouping_var in c(".", "Bio")) { + if (!is.null(rdata$variableMetadata[[grouping_var]])) { + return (grouping_var) + } + } + return (NULL) +} + +add_sample_to_database <- function(orm, env, context, smol_xcms_set) { + message(sprintf("Processing sample %s", env$sample_name)) + sample <- ( + orm$sample() + $set_name(env$sample_name) + $set_path(env$dataset_path) + $set_kind("enriched_rdata") + $set_polarity( + if (is.null(env$polarity) || identical(env$polarity, character(0))) "" + else env$polarity + ) + $set_smol_xcms_set(smol_xcms_set) + $set_raw(blob::blob(fst::compress_fst( + serialize(env, NULL), + compression=100 + ))) + $save() + ) + load_variable_metadata(orm, sample, env$variableMetadata, context) + load_process_params(orm, sample, env$process_params) + message(sprintf("Sample %s inserted.", env$sample_name)) + return (sample) +} + + +load_variable_metadata <- function(orm, sample, var_meta, context) { + all_clusters <- orm$cluster()$all() + + next_feature_id <- get_next_id(orm$feature()$all(), "featureID") + next_cluster_id <- get_next_id(all_clusters, "clusterID") + next_pc_group <- get_next_id(all_clusters, "pc_group") + next_align_group <- get_next_id(all_clusters, "align_group") + message("Extracting features") + invisible(create_features( + orm, sample, var_meta, context, + next_feature_id, next_cluster_id, + next_pc_group, next_align_group + )) + message("Extracting features done.") + return (NULL) +} + +get_next_id <- function(models, attribute) { + if ((id <- models$max(attribute)) == Inf || id == -Inf) { + return (1) + } + return (id + 1) +} + +create_features <- function( + orm, sample, var_meta, context, + next_feature_id, next_cluster_id, + next_pc_group, next_align_group +) { + field_names <- as.list(names(orm$feature()$fields__)) + field_names[field_names=="id"] <- NULL + + features <- list() + dummy_feature <- orm$feature() + + if (show_percent <- context$show_percent) { + percent <- -1 + total <- nrow(var_meta) + } + for (row in seq_len(nrow(var_meta))) { + if (show_percent && (row / total) * 100 > percent) { + percent <- percent + 1 + message("\r", sprintf("\r%d %%", percent), appendLF=FALSE) + } + + curent_var_meta <- var_meta[row, ] + + peak_list <- context$peaks[context$groupidx[[row]], ] + sample_peak_list <- peak_list[peak_list[, "sample"] == context$sample_no, , drop=FALSE] + if (!identical(sample_peak_list, numeric(0)) && !is.null(nrow(sample_peak_list)) && nrow(sample_peak_list) != 0) { + if (!is.na(int_o <- extract_peak_var(sample_peak_list, "into"))) { + dummy_feature$set_int_o(int_o) + } + if (!is.na(int_b <- extract_peak_var(sample_peak_list, "intb"))) { + dummy_feature$set_int_b(int_b) + } + if (!is.na(max_o <- extract_peak_var(sample_peak_list, "maxo"))) { + dummy_feature$set_max_o(max_o) + } + } + + set_feature_fields_from_var_meta(dummy_feature, curent_var_meta) + + dummy_feature$set_featureID(next_feature_id) + next_feature_id <- next_feature_id + 1 + fake_iso <- dummy_feature$get_iso() + iso <- extract_iso(fake_iso) + clusterID <- extract_clusterID(fake_iso, next_cluster_id) + context$clusterID <- clusterID + dummy_feature$set_iso(iso) + create_associated_cluster( + sample, dummy_feature, clusterID, + context, curent_var_meta, next_pc_group, + next_align_group + ) + next_align_group <- next_align_group + 1 + features[[length(features)+1]] <- as.list(dummy_feature, field_names) + dummy_feature$clear() + } + message("")## +\n for previous message + message("Saving features") + dummy_feature$save(bulk=features) + message("Saved.") + return (context$clusters) +} + +extract_peak_var <- function(peak_list, var_name, selector=max) { + value <- peak_list[, var_name] + names(value) <- NULL + return (selector(value)) +} + +set_feature_fields_from_var_meta <- function(feature, var_meta) { + if (!is.null(mz <- var_meta[["mz"]]) && !is.na(mz)) { + feature$set_mz(mz) + } + if (!is.null(mzmin <- var_meta[["mzmin"]]) && !is.na(mzmin)) { + feature$set_mz_min(mzmin) + } + if (!is.null(mzmax <- var_meta[["mzmax"]]) && !is.na(mzmax)) { + feature$set_mz_max(mzmax) + } + if (!is.null(rt <- var_meta[["rt"]]) && !is.na(rt)) { + feature$set_rt(rt) + } + if (!is.null(rtmin <- var_meta[["rtmin"]]) && !is.na(rtmin)) { + feature$set_rt_min(rtmin) + } + if (!is.null(rtmax <- var_meta[["rtmax"]]) && !is.na(rtmax)) { + feature$set_rt_max(rtmax) + } + if (!is.null(isotopes <- var_meta[["isotopes"]]) && !is.na(isotopes)) { + feature$set_iso(isotopes) + } + return (feature) +} + +extract_iso <- function(weird_data) { + if (grepl("^\\[\\d+\\]", weird_data)[[1]]) { + return (sub("^\\[\\d+\\]", "", weird_data, perl=TRUE)) + } + return (weird_data) +} + +extract_clusterID <- function(weird_data, next_cluster_id){ + if (grepl("^\\[\\d+\\]", weird_data)[[1]]) { + clusterID <- stringr::str_extract(weird_data, "^\\[\\d+\\]") + clusterID <- as.numeric(stringr::str_extract(clusterID, "\\d+")) + } else { + clusterID <- 0 + } + return (clusterID + next_cluster_id) +} + +create_associated_cluster <- function( + sample, feature, grouping_variable, + context, curent_var_meta, next_pc_group, next_align_group +) { + pcgroup <- as.numeric(curent_var_meta[["pcgroup"]]) + adduct <- as.character(curent_var_meta[["adduct"]]) + annotation <- curent_var_meta[["isotopes"]] + grouping_variable <- as.character(grouping_variable) + if (is.null(cluster <- context$clusters[[grouping_variable]])) { + cluster <- context$clusters[[grouping_variable]] <- orm$cluster( + pc_group=pcgroup + next_pc_group, + adduct=adduct, + align_group=next_align_group, + # curent_group=curent_group, + clusterID=context$clusterID, + annotation=annotation + )$set_sample(sample) + } else { + if (context$clusterID != 0 && cluster$get_clusterID() == 0) { + cluster$set_clusterID(context$clusterID) + } + } + cluster$save() + feature$set_cluster(cluster) + return (feature) +} + +complete_features <- function(orm, context) { + for (cluster in context$clusters) { + features <- orm$feature()$load_by(cluster_id=cluster$get_id()) + if (features$any()) { + if (!is.null(rt <- features$mean("rt"))) { + cluster$set_mean_rt(rt)$save() + } + features_df <- as.data.frame(features) + central_feature <- features_df[grepl("^\\[M\\]", features_df[, "iso"]), ] + central_feature_into <- central_feature[["int_o"]] + if (!identical(central_feature_into, numeric(0)) && central_feature_into != 0) { + for (feature in as.vector(features)) { + feature$set_abundance( + feature$get_int_o() / central_feature_into * 100 + )$save() + } + } + } + } + return (NULL) +} + +load_process_params <- function(orm, sample, params) { + for (param_list in params) { + if (is.null(param_list[["xfunction"]])) { + next + } + if (param_list[["xfunction"]] == "annotatediff") { + load_process_params_peak_picking(orm, sample, param_list) + } + } + return (sample) +} + +load_process_params_peak_picking <- function(orm, sample, peak_picking_params) { + return (add_sample_process_parameters( + params=peak_picking_params, + params_translation=list( + ppm="ppm", + maxcharge="maxCharge", + maxiso="maxIso" + ), + param_model_generator=orm$peak_picking_parameters, + sample_param_setter=sample$set_peak_picking_parameters + )) +} + +add_sample_process_parameters <- function( + params, + params_translation, + param_model_generator, + sample_param_setter +) { + model_params <- list() + for (rdata_param_name in names(params_translation)) { + database_param_name <- params_translation[[rdata_param_name]] + if (is.null(rdata_param <- params[[rdata_param_name]])) { + next + } + model_params[[database_param_name]] <- rdata_param + } + params_models <- do.call(param_model_generator()$load_by, model_params) + if (params_models$any()) { + params_model <- params_models$first() + } else { + params_model <- do.call(param_model_generator, model_params) + params_model$save() + } + return (sample_param_setter(params_model)$save()) +} + + +library(optparse) + +option_list <- list( + optparse::make_option( + c("-v", "--version"), + action="store_true", + help="Display this tool's version and exits" + ), + optparse::make_option( + c("-i", "--input"), + type="character", + help="The rdata path to import in XSeeker" + ), + optparse::make_option( + c("-s", "--samples"), + type="character", + help="Samples to visualise in XSeeker" + ), + optparse::make_option( + c("-B", "--archetype"), + type="character", + help="The name of the base database" + ), + optparse::make_option( + c("-b", "--database"), + type="character", + help="The base database's path" + ), + optparse::make_option( + c("-c", "--compounds-csv"), + type="character", + help="The csv containing compounds" + ), + optparse::make_option( + c("-m", "--models"), + type="character", + help="The path or url (must begin with http[s]:// or git@) to the database's models" + ), + optparse::make_option( + c("-o", "--output"), + type="character", + help="The path where to output sqlite" + ), + optparse::make_option( + c("-P", "--not-show-percent"), + action="store_true", + help="Flag not to show the percents", + default=FALSE + ) +) + +options(error=function(){traceback(3)}) + +parser <- OptionParser(usage="%prog [options] file", option_list=option_list) +args <- parse_args(parser, positional_arguments=0) + +err_code <- 0 + +if (!is.null(args$options$version)) { + message(sprintf("%s %s", TOOL_NAME, VERSION)) + quit() +} + +models <- get_models(args$options$models) +orm <- DBModelR::ORM( + connection_params=list(dbname=args$options$output), + dbms="SQLite" +) + +invisible(orm$models(models)) +invisible(create_database(orm)) + +message("Database model created") + +insert_adducts(orm) + +if (!is.null(args$options$database)) { + insert_base_data(orm, args$options$database) +} +message(sprintf("Base data inserted using %s.", args$options$database)) + +if (!is.null(args$options$archetype)) { + insert_base_data(orm, args$options$archetype, archetype=TRUE) +} +if (!is.null(args$options$`compounds-csv`)) { + insert_compounds(orm, args$options$`compounds-csv`) +} + +# if (!is.null(args$options$rdata)) { +# load_rdata_in_base(args$options$rdata, args$options$samples, args$options$`not-show-percent`) +# } + + +load(args$options$input, rdata <- new.env()) + +process_rdata(orm, rdata, args$options) + +quit(status=err_code) + +