Mercurial > repos > nml > mykrobe_parser
changeset 6:8e7e5a660942 draft
planemo upload for repository https://github.com/phac-nml/mykrobe-parser commit 077a66175f3666924b42f216bbcb671ee0d026f2
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--- a/mykrobe_parser.R Thu May 09 14:16:34 2019 -0400 +++ b/mykrobe_parser.R Fri Sep 22 17:24:02 2023 +0000 @@ -1,13 +1,13 @@ # Copyright Government of Canada 2018 -# +# # Written by: National Microbiology Laboratory, Public Health Agency of Canada -# +# # Licensed under the Apache License, Version 2.0 (the "License"); you may not use # this work except in compliance with the License. You may obtain a copy of the # License at: -# +# # http://www.apache.org/licenses/LICENSE-2.0 -# +# # Unless required by applicable law or agreed to in writing, software distributed # under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR # CONDITIONS OF ANY KIND, either express or implied. See the License for the @@ -18,6 +18,7 @@ # Take the JSON output from Mykrobe, rearrange, output for LIMS # Adrian Zetner # August 2018 +# Updated August 2023 # Libraries #### @@ -35,313 +36,539 @@ # Define custom functions, variables, and paths. Collect and use CL arguments #### -# Here's a function to recreate that output table from the input JSON files +# Here's a function to recreate that output table from the input JSON files for 2019 -getResults <- function(listelement){ +getResults2019 <- function(listelement) { # Define list levels for various elements of the json - species <- names(listelement[[1]][["phylogenetics"]][["species"]]) - lineage <- names(listelement[[1]][["phylogenetics"]][["lineage"]]) - phylo_group <- names(listelement[[1]][["phylogenetics"]][["phylo_group"]]) - if("Non_tuberculosis_mycobacterium_complex" %in% phylo_group){ - warning(paste("Non-tuberculosis mycobacteria detected in file ", names(listelement), ". Skipping.", sep = "")) - return()} - + phylo_group <- + names(listelement[[1]][["phylogenetics"]][["phylo_group"]]) + if ("Non_tuberculosis_mycobacterium_complex" %in% phylo_group) { + warning( + paste( + "Non-tuberculosis mycobacteria detected in file ", + names(listelement), + ". Skipping.", + sep = "" + ) + ) + return() + } + + species <- + names(listelement[[1]][["phylogenetics"]][["species"]]) + lineage <- + if (length(listelement[[1]][["phylogenetics"]][["lineage"]]) == 1) { + names(listelement[[1]][["phylogenetics"]][["lineage"]]) + } else { + listelement[[1]][["phylogenetics"]][["lineage"]][["lineage"]] + } + # Start building a list of all your various elements - temp <- list(mykrobe_version = listelement[[1]][["version"]][["mykrobe-predictor"]], - file = names(listelement), # One element - plate_name = "test", # This probably needs changing - sample = "sequence_calls", # Likewise change this - phylo_group = phylo_group, # As above - species = species, # As above - lineage = lineage, # As above - # The following expressions drill down into the list elements and pull out what is needed. - # It's inelegant and vulnerable to changes in the input formats but if they're consistent it'll work - phylo_group_per_covg = listelement[[1]][["phylogenetics"]][["phylo_group"]][[phylo_group]][["percent_coverage"]], - species_per_covg = listelement[[1]][["phylogenetics"]][["species"]][[species]][["percent_coverage"]], - lineage_per_covg = listelement[[1]][["phylogenetics"]][["lineage"]][[lineage]][["percent_coverage"]], - phylo_group_depth = listelement[[1]][["phylogenetics"]][["phylo_group"]][[phylo_group]][["median_depth"]], - species_depth = listelement[[1]][["phylogenetics"]][["species"]][[species]][["median_depth"]], - lineage_depth = listelement[[1]][["phylogenetics"]][["lineage"]][[lineage]][["median_depth"]], - Mykrobe_Resistance_probe_set = basename(listelement[[1]][["probe_sets"]][2]) # Is it always the second? - ) - + temp <- + list( + mykrobe_version = listelement[[1]][["version"]][["mykrobe-predictor"]], + file = names(listelement), + # One element + plate_name = "test", + # This probably needs changing + sample = "sequence_calls", + # Likewise change this + phylo_group = phylo_group, + # As above + species = species, + # As above + lineage = lineage, + # As above + # The following expressions drill down into the list elements and pull out what is needed. + # It's inelegant and vulnerable to changes in the input formats but if they're consistent it'll work + phylo_group_per_covg = listelement[[1]][["phylogenetics"]][["phylo_group"]][[phylo_group]][["percent_coverage"]], + species_per_covg = listelement[[1]][["phylogenetics"]][["species"]][[species]][["percent_coverage"]], + lineage_per_covg = listelement[[1]][["phylogenetics"]][["lineage"]][[lineage]][["percent_coverage"]], + phylo_group_depth = listelement[[1]][["phylogenetics"]][["phylo_group"]][[phylo_group]][["median_depth"]], + species_depth = listelement[[1]][["phylogenetics"]][["species"]][[species]][["median_depth"]], + lineage_depth = listelement[[1]][["phylogenetics"]][["lineage"]][[lineage]][["median_depth"]], + Mykrobe_Resistance_probe_set = basename(listelement[[1]][["probe_sets"]][2]) # Is it always the second? + ) + # Super cool nested and vectorized (for SPEED!) functions to grab the predictions for drug sensitivity and gene variants # Both produce character vectors of the same length as the number of drugs tested in the same order # All of these also check if there are missing values in drug/susceptibility/variant elements and adds the column anyhow - - if(length(map_chr(listelement[[1]][["susceptibility"]], "predict")) != 0){ - temp$susceptibility <- map_chr(listelement[[1]][["susceptibility"]], "predict") - }else{ + + if (length(map_chr(listelement[[1]][["susceptibility"]], "predict")) != 0) { + temp$susceptibility <- + map_chr(listelement[[1]][["susceptibility"]], "predict") + } else { temp$susceptibility <- NA } - - if(length(names(listelement[[1]][["susceptibility"]])) != 0){ - temp$drug <- names(listelement[[1]][["susceptibility"]]) - }else{ + + if (length(names(listelement[[1]][["susceptibility"]])) != 0) { + temp$drug <- names(listelement[[1]][["susceptibility"]]) + } else { temp$drug <- NA } - - mapped.variants <- map(listelement[[1]][["susceptibility"]], # Dig into the lists, pull out variants and collapse into chr vector - ~ imap(.x[["called_by"]], # imap is shorthand for map2(x, names(x), ...), calling .y gets you the name / index of the current element - ~ paste(.y, - .x[["info"]][["coverage"]][["alternate"]][["median_depth"]], - .x[["info"]][["coverage"]][["reference"]][["median_depth"]], - .x[["info"]][["conf"]], - sep = ":"))) %>% + + mapped.variants <- + map( + listelement[[1]][["susceptibility"]], # Dig into the lists, pull out variants and collapse into chr vector + ~ imap( + .x[["called_by"]], # imap is shorthand for map2(x, names(x), ...), calling .y gets you the name / index of the current element + ~ paste(.y, + .x[["info"]][["coverage"]][["alternate"]][["median_depth"]], + .x[["info"]][["coverage"]][["reference"]][["median_depth"]], + .x[["info"]][["conf"]], + sep = ":" + ) + ) + ) %>% map_chr(~ paste(.x, collapse = "__")) - - if(length(mapped.variants) != 0){ + + if (length(mapped.variants) != 0) { temp$`variants (gene:alt_depth:wt_depth:conf)` <- mapped.variants - }else{ + } else { temp$`variants (gene:alt_depth:wt_depth:conf)` <- NA } - - temp$`genes (prot_mut-ref_mut:percent_covg:depth)` <- NA - + + temp$`genes (prot_mut-ref_mut:percent_covg:depth)` <- NA + + # Take that list and mash all the elements together as columns in a tibble, recycling as needed to fill in space + # eg. phylo_group is repeated/recycled as many times as there are drugs tested + as_tibble(temp) +} + +# Here's a function to recreate that output table from the input JSON files for panel 2020 + +getResults2020 <- function(listelement) { + # Define list levels for various elements of the json + phylo_group <- + names(listelement[[1]][["phylogenetics"]][["phylo_group"]]) + if ("Non_tuberculosis_mycobacterium_complex" %in% phylo_group) { + warning( + paste( + "Non-tuberculosis mycobacteria detected in file ", + names(listelement), + ". Skipping.", + sep = "" + ) + ) + return() + } + + species <- + names(listelement[[1]][["phylogenetics"]][["species"]]) + + # Start building a list of all your various elements + temp <- + list( + mykrobe_version = listelement[[1]][["version"]][["mykrobe-predictor"]], + file = names(listelement), + # One element + plate_name = "test", + # This probably needs changing + sample = "sequence_calls", + # Likewise change this + phylo_group = phylo_group, + # As above + species = species, + # As above + # The following expressions drill down into the list elements and pull out what is needed. + # It's inelegant and vulnerable to changes in the input formats but if they're consistent it'll work + phylo_group_per_covg = listelement[[1]][["phylogenetics"]][["phylo_group"]][[phylo_group]][["percent_coverage"]], + species_per_covg = listelement[[1]][["phylogenetics"]][["species"]][[species]][["percent_coverage"]], + phylo_group_depth = listelement[[1]][["phylogenetics"]][["phylo_group"]][[phylo_group]][["median_depth"]], + species_depth = listelement[[1]][["phylogenetics"]][["species"]][[species]][["median_depth"]], + Mykrobe_Resistance_probe_set = basename(listelement[[1]][["probe_sets"]][2]) # Is it always the second? + ) + + # Super cool nested and vectorized (for SPEED!) functions to grab the predictions for drug sensitivity and gene variants + # Both produce character vectors of the same length as the number of drugs tested in the same order + # All of these also check if there are missing values in drug/susceptibility/variant elements and adds the column anyhow + + if (length(map_chr(listelement[[1]][["susceptibility"]], "predict")) != 0) { + temp$susceptibility <- + map_chr(listelement[[1]][["susceptibility"]], "predict") + } else { + temp$susceptibility <- NA + } + + if (length(names(listelement[[1]][["susceptibility"]])) != 0) { + temp$drug <- names(listelement[[1]][["susceptibility"]]) + } else { + temp$drug <- NA + } + + mapped.variants <- + map( + listelement[[1]][["susceptibility"]], # Dig into the lists, pull out variants and collapse into chr vector + ~ imap( + .x[["called_by"]], # imap is shorthand for map2(x, names(x), ...), calling .y gets you the name / index of the current element + ~ paste(.y, + .x[["info"]][["coverage"]][["alternate"]][["median_depth"]], + .x[["info"]][["coverage"]][["reference"]][["median_depth"]], + .x[["info"]][["conf"]], + sep = ":" + ) + ) + ) %>% + map_chr(~ paste(.x, collapse = "__")) + + if (length(mapped.variants) != 0) { + temp$`variants (gene:alt_depth:wt_depth:conf)` <- mapped.variants + } else { + temp$`variants (gene:alt_depth:wt_depth:conf)` <- NA + } + + temp$`genes (prot_mut-ref_mut:percent_covg:depth)` <- NA + # Take that list and mash all the elements together as columns in a tibble, recycling as needed to fill in space # eg. phylo_group is repeated/recycled as many times as there are drugs tested as_tibble(temp) } # Get command line arguments with optparse -option_list = list( - make_option(c("-f", "--file"), - type="character", - default=NULL, - help='dataset file name or quoted comma separated names: eg. "file1,file2,file3"', - metavar="character"), - make_option(c("-d", "--dir"), - type="character", - default=NULL, - help="directory location of json files", - metavar="character"), - make_option(c("-v", "--version"), - type="character", - default="", - help="Mykrobe Workflow Version", - metavar="character"), - make_option(c("-D", "--depth"), - type="integer", - default=5, - help="Minimum depth of coverage [default= %default]", - metavar="integer"), - make_option(c("-c", "--conf"), - type="integer", - default=10, - help="Minimum genotype confidence for variant genotyping [default= %default]", - metavar="integer"), - make_option(c("-n", "--name"), - type="character", - default="", - help="Name of the run", - metavar="character") +option_list <- list( + make_option( + c("-f", "--file"), + type = "character", + default = NULL, + help = 'dataset file name or quoted comma separated names: eg. "file1,file2,file3"', + metavar = "character" + ), + make_option( + c("-d", "--dir"), + type = "character", + default = NULL, + help = "directory location of json files", + metavar = "character" + ), + make_option( + c("-v", "--version"), + type = "character", + default = "", + help = "Mykrobe Workflow Version", + metavar = "character" + ), + make_option( + c("-p", "--panel"), + type = "character", + default = "2019", + help = "Mykrobe Panel Version: 2019 or 2020. [default= %default]", + metavar = "character" + ), + make_option( + c("-D", "--depth"), + type = "integer", + default = 5, + help = "Minimum depth of coverage [default= %default]", + metavar = "integer" + ), + make_option( + c("-c", "--conf"), + type = "integer", + default = 10, + help = "Minimum genotype confidence for variant genotyping [default= %default]", + metavar = "integer" + ), + make_option( + c("-n", "--name"), + type = "character", + default = "", + help = "Name of the run", + metavar = "character" + ), + make_option( + c("-r", "--reportfile"), + type = "character", + default = "report", + help = "File name for susceptibility report data", + metavar = "character" + ), + make_option( + c("-s", "--speciationfile"), + type = "character", + default = "jsondata", + help = "File name for speciation data", + metavar = "character" + ) ) -opt_parser = OptionParser(option_list=option_list) -opt = parse_args(opt_parser) +opt_parser <- OptionParser(option_list = option_list) +opt <- parse_args(opt_parser) -if (is.null(opt$file) & is.null(opt$dir)){ +if (is.null(opt$file) && is.null(opt$dir)) { print_help(opt_parser) - stop("At least one argument must be supplied to input file or directory", call.=FALSE) + stop("At least one argument must be supplied to input file or directory", + call. = FALSE + ) +} + +if (opt$panel != "2019" && opt$panel != "2020") { + print_help(opt_parser) + stop("Panel must be one of 2019 or 2020", call. = FALSE) } # Parameters to take from Galaxy/CL as args or however works best -params <- c("", # Lims_Comment - "", # Lims_INTComment - opt$version, # Mykrobe_Workflow_Version - opt$depth, # Mykrobe_min_depth_default_5 - opt$conf, # Mykrobe_min_conf_default_10 - "", # LIMS_file - empty as it's an upload field in LIMS - opt$name) # Mutation_set_version +params <- c( + "", # Lims_Comment + "", # Lims_INTComment + opt$version, # Mykrobe_Workflow_Version + opt$panel, # Mykrobe Panel Version + opt$depth, # Mykrobe_min_depth_default_5 + opt$conf, # Mykrobe_min_conf_default_10 + "", # LIMS_file - empty as it's an upload field in LIMS + opt$name +) # Mutation_set_version -names(params) <- c("Lims_Comment", - "Lims_INTComment", - "Mykrobe_Workflow_Version", - "Mykrobe_min_depth_default_5", - "Mykrobe_min_conf_default_10", - "LIMS_file", - "Mutation_set_version") +names(params) <- c( + "Lims_Comment", + "Lims_INTComment", + "Mykrobe_Workflow_Version", + "Mykrobe_Panel_Version", + "Mykrobe_min_depth_default_5", + "Mykrobe_min_conf_default_10", + "LIMS_file", + "Mutation_set_version" +) # A default report in the order our LIMS requires # Make a default dataframe to combine the rest into and enforce column order / fill missing ones with NAs -columns <- c("file", - "Mykrobe_fabG1", - "Mykrobe_katG", - "Mykrobe_ahpC", - "Mykrobe_inhA", - "Mykrobe_ndh", - "Isoniazid_R_mutations", - "Isoniazid_Prediction", - "Mykrobe_rpoB", - "Rifampicin_R_mutations", - "Rifampicin_Prediction", - "Mykrobe_embB", - "Mykrobe_embA", - "Ethambutol_R_mutations", - "Ethambutol_Prediction", - "Mykrobe_pncA", - "Mykrobe_rpsA", - "Pyrazinamide_R_mutations", - "Pyrazinamide_Prediction", - "Mykrobe_Ofloxacin_gyrA", - "Ofloxacin_R_mutations", - "Ofloxacin_Prediction", - "Mykrobe_Moxifloxacin_gyrA", - "Moxifloxacin_R_mutations", - "Moxifloxacin_Prediction", - "Mykrobe_rpsL", - "Mykrobe_Streptomycin_rrs", - "Mykrobe_Streptomycin_gid", - "Streptomycin_R_mutations", - "Streptomycin_Prediction", - "Mykrobe_Amikacin_rrs", - "Amikacin_R_mutations", - "Amikacin_Prediction", - "Mykrobe_Capreomycin_rrs", - "Mykrobe_Capreomycin_tlyA", - "Capreomycin_R_mutations", - "Capreomycin_Prediction", - "Mykrobe_Kanamycin_rrs", - "Mykrobe_Kanamycin_eis", - "Kanamycin_R_mutations", - "Kanamycin_Prediction", - "Lims_Comment", - "Lims_INTComment", - "Mykrobe_Workflow_Version", - "mykrobe_version", - "Mykrobe_Resistance_probe_set", - "Mykrobe_min_depth_default_5", - "Mykrobe_min_conf_default_10", - "LIMS_file", - "Mutation_set_version") +columns <- c( + "file", + "Mykrobe_fabG1", + "Mykrobe_katG", + "Mykrobe_ahpC", + "Mykrobe_inhA", + "Mykrobe_ndh", + "Isoniazid_R_mutations", + "Isoniazid_Prediction", + "Mykrobe_rpoB", + "Rifampicin_R_mutations", + "Rifampicin_Prediction", + "Mykrobe_embB", + "Mykrobe_embA", + "Ethambutol_R_mutations", + "Ethambutol_Prediction", + "Mykrobe_pncA", + "Mykrobe_rpsA", + "Pyrazinamide_R_mutations", + "Pyrazinamide_Prediction", + "Mykrobe_Ofloxacin_gyrA", + "Ofloxacin_R_mutations", + "Ofloxacin_Prediction", + "Mykrobe_Moxifloxacin_gyrA", + "Moxifloxacin_R_mutations", + "Moxifloxacin_Prediction", + "Mykrobe_Ciprofloxacin_gyrA", + "Ciprofloxacin_R_mutations", + "Ciprofloxacin_Prediction", + "Mykrobe_rpsL", + "Mykrobe_Streptomycin_rrs", + "Mykrobe_Streptomycin_gid", + "Streptomycin_R_mutations", + "Streptomycin_Prediction", + "Mykrobe_Amikacin_rrs", + "Amikacin_R_mutations", + "Amikacin_Prediction", + "Mykrobe_Capreomycin_rrs", + "Mykrobe_Capreomycin_tlyA", + "Capreomycin_R_mutations", + "Capreomycin_Prediction", + "Mykrobe_Kanamycin_rrs", + "Mykrobe_Kanamycin_eis", + "Kanamycin_R_mutations", + "Kanamycin_Prediction", + "Lims_Comment", + "Lims_INTComment", + "Mykrobe_Workflow_Version", + "mykrobe_version", + "Mykrobe_Resistance_probe_set", + "Mykrobe_min_depth_default_5", + "Mykrobe_min_conf_default_10", + "LIMS_file", + "Mutation_set_version" +) -report <- setNames(data.frame(matrix("", ncol = length(columns), nrow = 1), stringsAsFactors = F), columns) +report <- + setNames(data.frame(matrix( + "", + ncol = length(columns), nrow = 1 + ), stringsAsFactors = FALSE), columns) +report_cols <- c( + "file", + "phylo_group", + "species", + "lineage", + "phylo_group_per_covg", + "species_per_covg", + "lineage_per_covg", + "phylo_group_depth", + "species_depth", + "lineage_depth" +) # List of drugs that are tested -all_drugs <- c("Isoniazid", - "Rifampicin", - "Ethambutol", - "Pyrazinamide", - "Moxifloxacin", - "Ofloxacin", - "Streptomycin", - "Amikacin", - "Capreomycin", - "Kanamycin") +all_drugs <- c( + "Isoniazid", + "Rifampicin", + "Ethambutol", + "Pyrazinamide", + "Moxifloxacin", + "Ofloxacin", + "Streptomycin", + "Amikacin", + "Capreomycin", + "Kanamycin" +) # Do Stuff #### # Import all the JSON files into a list of lists format #### -if (is.null(opt$file)){ +if (is.null(opt$file)) { # opt$dir is used to get the list of files, a vector of non-duplicated files is then passed to map - files <- list.files(path = opt$dir, - pattern = "*.json", - full.names = T) -}else{ + files <- list.files( + path = opt$dir, + pattern = "*.json", + full.names = TRUE + ) +} else { files <- unlist(strsplit(opt$file, ",")) } files <- files[!duplicated(basename(files))] -list.of.json.files <- map(files, - ~ fromJSON(.x, simplifyDataFrame = F) +list.of.json.files <- map( + files, + ~ fromJSON(.x, simplifyDataFrame = FALSE) ) -# Apply that getResults function to each element in your list then bash it together into a final report +# Apply the correct getResults function to each element in your list then bash it together into a final report -temp <- map(list.of.json.files, getResults) %>% - bind_rows() +if (opt$panel == "2019") { + temp <- map(list.of.json.files, getResults2019) %>% + bind_rows() +} else if (opt$panel == "2020") { + temp <- map(list.of.json.files, getResults2020) %>% + bind_rows() + columns <- + setdiff( + columns, + c( + "Mykrobe_Ciprofloxacin_gyrA", + "Ciprofloxacin_R_mutations", + "Ciprofloxacin_Prediction" + ) + ) + report_cols <- setdiff( + report_cols, + c( + "lineage", + "lineage_per_covg", + "lineage_depth" + ) + ) +} else { + stop("Panel must be one of 2019 or 2020", call. = FALSE) +} # Predictions of resistance or susceptibility -predictions.table <- + +predictions.table <- temp %>% - select(file, drug, susceptibility) %>% - mutate(drug = paste(drug, "_Prediction", sep = "")) %>% - spread(drug, susceptibility, fill = "failed") %>% + select(file, drug, susceptibility) %>% + mutate(drug = paste(drug, "_Prediction", sep = "")) %>% + spread(drug, susceptibility, fill = "failed") %>% select(-starts_with("NA")) -if (length(predictions.table) == 1){ +if (length(predictions.table) == 1) { print(predictions.table) - stop("No susceptibility results in files specified. Did the testing fail?", call.=FALSE) + stop("No susceptibility results in files specified. Did the testing fail?", + call. = FALSE + ) } # Variants, if present -if (0 < predictions.table %>% - select(ends_with("_Prediction")) %>% - unlist(use.names = F) %>% - str_count("[R,r]") %>% - sum()){ +num.variants <- + predictions.table %>% + select(ends_with("_Prediction")) %>% + unlist(use.names = FALSE) %>% + str_count("[R,r]") %>% + sum() + +if (num.variants > 0) { + # Multiple resistance mutations and confidence per drug in the X_R_mutations column + # Actual protein changes in Mykrobe_X columns - # Multiple resistance mutations and confidence per drug in the X_R_mutations column - # Actual protein changes in Mykrobe_X columns - - variants.temp <- - temp %>% - select(file, drug, variants = `variants (gene:alt_depth:wt_depth:conf)`) %>% - mutate(variants = replace(variants, variants == "", NA)) %>% # Make missing data consistent... - filter(!is.na(variants)) %>% # ...Then get rid of it - mutate(tempcols = paste(drug, "R_mutations", sep = "_")) %>% - mutate(R_mutations = variants) %>% - mutate(variants = strsplit(variants, "__")) %>% # Split the mutations across rows (list first then split across rows) - unnest(variants) %>% - separate(variants, c("gene", "mutation"), "_") %>% - mutate(columnname = ifelse(gene %in% c("gyrA", "tlyA", "rrs", "eis", "gid"), # Check for columns that include the drug name or not and paste accordingly - paste("Mykrobe", drug, gene, sep = "_"), - paste("Mykrobe", gene, sep = "_"))) %>% - # Extract out the mutation information with a regex that covers all potential genes - # This regex looks for whatever is ahead of the first colon and after the last hyphen - mutate(mutation = str_match(mutation, "(.*)-.*:")[,2]) %>% - select(file, tempcols, R_mutations, columnname, mutation) - - # Split each kind of variants into its own temp table then merge - variants.1 <- - variants.temp %>% - select(file, tempcols, R_mutations) %>% - distinct() %>% - spread(tempcols, R_mutations) - - variants.2 <- - variants.temp %>% - select(file, columnname, mutation) %>% - group_by(file, columnname) %>% - summarise(mutation = paste(mutation, collapse = ";")) %>% - spread(columnname, mutation) - - variants.table <- full_join(variants.1, variants.2, by = "file") -}else{ - variants.table <- data.frame(file=predictions.table$file, stringsAsFactors = F) + variants.temp <- + temp %>% + select(file, drug, variants = `variants (gene:alt_depth:wt_depth:conf)`) %>% + mutate(variants = replace(variants, variants == "", NA)) %>% # Make missing data consistent... + filter(!is.na(variants)) %>% # ...Then get rid of it + mutate(tempcols = paste(drug, "R_mutations", sep = "_")) %>% + mutate(R_mutations = variants) %>% + mutate(variants = strsplit(variants, "__")) %>% # Split the mutations across rows (list first then split across rows) + unnest(variants) %>% + separate(variants, c("gene", "mutation"), "_") %>% + mutate(columnname = ifelse( + gene %in% c("gyrA", "rrs", "eis", "gid"), + # Check for columns that include the drug name or not and paste accordingly + paste("Mykrobe", drug, gene, sep = "_"), + paste("Mykrobe", gene, sep = "_") + )) %>% + # Extract out the mutation information with a regex that covers all potential genes + # This regex looks for whatever is ahead of the first colon and after the last hyphen + mutate(mutation = str_match(mutation, "(.*)-.*:")[, 2]) %>% + select(file, tempcols, R_mutations, columnname, mutation) + + # Split each kind of variants into its own temp table then merge + variants.1 <- + variants.temp %>% + select(file, tempcols, R_mutations) %>% + distinct() %>% + spread(tempcols, R_mutations) + + variants.2 <- + variants.temp %>% + select(file, columnname, mutation) %>% + group_by(file, columnname) %>% + summarise(mutation = paste(mutation, collapse = ";")) %>% + spread(columnname, mutation) + + variants.table <- + full_join(variants.1, variants.2, by = "file") +} else { + variants.table <- + data.frame(file = predictions.table$file, stringsAsFactors = FALSE) } # Make a report #### -report <- - temp %>% +report <- + temp %>% select(file, mykrobe_version, Mykrobe_Resistance_probe_set) %>% # Get important info from initial table distinct() %>% # Drop duped rows and combine all the tables together - full_join(variants.table) %>% - full_join(predictions.table) %>% - bind_rows(report) %>% # Use bind_rows to add columns (eg. unteseted drugs) to the final output + full_join(variants.table) %>% + full_join(predictions.table) %>% + bind_rows(report) %>% # Use bind_rows to add columns (eg. unteseted drugs) to the final output filter(file != "") # Only add the 'no mutation' replacement to the columns that actually have a result -report <- +report <- report %>% - filter_at(vars(ends_with("_Prediction")), any_vars(. != "failed")) %>% - mutate_at(vars(starts_with("Mykrobe_")), funs(replace(., is.na(.), "No Mutation"))) %>% - full_join(anti_join(report, ., by = "file")) %>% - select(columns) - + filter_at(vars(ends_with("_Prediction")), any_vars(. != "failed")) %>% + mutate_at(vars(starts_with("Mykrobe_")), funs(replace(., is.na(.), "No Mutation"))) %>% + full_join(anti_join(report, ., by = "file")) %>% + select(columns) + # Add in the parameters fed from Galaxy using named character vector -report <- - report %>% +report <- + report %>% mutate( Lims_Comment = params["Lims_Comment"], Lims_INTComment = params["Lims_INTComment"], @@ -351,30 +578,22 @@ LIMS_file = params["LIMS_file"], Mutation_set_version = params["Mutation_set_version"] ) - - -#View(report) # Write some output # Report as is -write.csv(report, "output-report.csv", row.names = F) +write.csv(report, "output-report.csv", row.names = FALSE) print("Writing Susceptibility report to CSV as output-report.csv") # Select specific columns from temp and output them -temp %>% - select(file, - phylo_group, - species, - lineage, - phylo_group_per_covg, - species_per_covg, - lineage_per_covg, - phylo_group_depth, - species_depth, - lineage_depth) %>% +# Addition of any_of accounts for both 2019 and 2020 panels + +temp %>% + select_at( # This is a dplyr 0.8.3 function, superceded in newer versions but this tool is built around a number of specific deps + report_cols + ) %>% distinct() %>% - write.csv("output-jsondata.csv", row.names = F) + write.csv(file = "output-jsondata.csv", row.names = FALSE) print("Writing JSON data to CSV as output-jsondata.csv") -sink(NULL, type="message") # close the sink +sink(NULL, type = "message") # close the sink quit()
--- a/mykrobe_parser.xml Thu May 09 14:16:34 2019 -0400 +++ b/mykrobe_parser.xml Fri Sep 22 17:24:02 2023 +0000 @@ -1,4 +1,7 @@ -<tool id="mykrobe_parseR" name="mykrobe_parseR" version="0.1.4.1"> +<tool id="mykrobe_parseR" name="mykrobe_parseR" version="@VERSION@+galaxy1" profile="16.04"> + <macros> + <token name="@VERSION@">0.1.4.1</token> + </macros> <requirements> <requirement type="package" version="3.4.1">r-base</requirement> <requirement type="package" version="1.5.0">r-jsonlite</requirement> @@ -30,6 +33,9 @@ #if $confidence -c "$confidence" #end if + #if $panel + -p "$panel" + #end if #if $run_name -n "$run_name" #end if @@ -42,9 +48,13 @@ multiple="true" label="JSON File(s) (.JSON or .TXT)"/> <param name="version" type="text" - argument="-v" + argument="-v" optional="true" label="Mykrobe Workflow Version"/> + <param name="panel" type="select" label="Mykrobe Panel Version" multiple="false"> + <option value="2019">2019</option> + <option value="2020">2020</option> + </param> <param name="depth" type="integer" argument="-D" optional="true" @@ -61,14 +71,33 @@ label="Name of Run"/> </inputs> <outputs> - <data name="output-jsondata" from_work_dir="output-jsondata.csv" format="csv" label="jsondata"/> - <data name="output-report" from_work_dir="output-report.csv" format="csv" label="report"/> + <data name="output_jsondata" from_work_dir="output-jsondata.csv" format="csv" label="jsondata"/> + <data name="output_report" from_work_dir="output-report.csv" format="csv" label="report"/> </outputs> <tests> <test> - <param name="input" value="test-data.json"/> - <output name="output-jsondata" ftype="csv" value="output-jsondata.csv" compare="sim_size"/> - <output name="output-report" ftype="csv" value="output-report.csv" compare="sim_size"/> + <param name="input" value="prediction_2019/data/ERR031480_L6.json,prediction_2019/data/ERR125628_MBOV.json,prediction_2019/data/ERR181314_L9.json,prediction_2019/data/ERR234162_L3.json,prediction_2019/data/ERR2659153.json,prediction_2019/data/ERR266106_MCAN.json,prediction_2019/data/ERR2704812_L5.json,prediction_2019/data/ERR3335753_L1.json,prediction_2019/data/ERR4143897_MPIN.json,prediction_2019/data/ERR756348_L7.json,prediction_2019/data/ERR841495_L5.json,prediction_2019/data/SRR17089001.json,prediction_2019/data/SRR1710097_L2.json,prediction_2019/data/SRR3500411_MMUN.json,prediction_2019/data/SRR9157804.json"/> + <param name="panel" value="2019"/> + <output name="output_jsondata" ftype="csv" value="prediction_2019/output-jsondata.csv"/> + <output name="output_report" ftype="csv" value="prediction_2019/output-report.csv"/> + </test> + <test> + <param name="input" value="prediction_2020/data/ERR031480_L6.json,prediction_2020/data/ERR125628_MBOV.json,prediction_2020/data/ERR181314_L9.json,prediction_2020/data/ERR234162_L3.json,prediction_2020/data/ERR2659153.json,prediction_2020/data/ERR266106_MCAN.json,prediction_2020/data/ERR2704812_L5.json,prediction_2020/data/ERR3335753_L1.json,prediction_2020/data/ERR4143897_MPIN.json,prediction_2020/data/ERR756348_L7.json,prediction_2020/data/ERR841495_L5.json,prediction_2020/data/SRR17089001.json,prediction_2020/data/SRR1710097_L2.json,prediction_2020/data/SRR3500411_MMUN.json,prediction_2020/data/SRR9157804.json"/> + <param name="panel" value="2020"/> + <output name="output_jsondata" ftype="csv" value="prediction_2020/output-jsondata.csv"/> + <output name="output_report" ftype="csv" value="prediction_2020/output-report.csv"/> + </test> + <test> + <param name="input" value="single_2019/single2019.json"/> + <param name="panel" value="2019"/> + <output name="output_jsondata" ftype="csv" value="single_2019/output-jsondata.csv"/> + <output name="output_report" ftype="csv" value="single_2019/output-report.csv"/> + </test> + <test> + <param name="input" value="single_2020/single2020.json"/> + <param name="panel" value="2020"/> + <output name="output_jsondata" ftype="csv" value="single_2020/output-jsondata.csv"/> + <output name="output_report" ftype="csv" value="single_2020/output-report.csv"/> </test> </tests> <help><![CDATA[
--- a/test-data/output-report.csv Thu May 09 14:16:34 2019 -0400 +++ b/test-data/output-report.csv Fri Sep 22 17:24:02 2023 +0000 @@ -1,2 +1,2 @@ -"file","Mykrobe_fabG1","Mykrobe_katG","Mykrobe_ahpC","Mykrobe_inhA","Mykrobe_ndh","Isoniazid_R_mutations","Isoniazid_Prediction","Mykrobe_rpoB","Rifampicin_R_mutations","Rifampicin_Prediction","Mykrobe_embB","Mykrobe_embA","Ethambutol_R_mutations","Ethambutol_Prediction","Mykrobe_pncA","Mykrobe_rpsA","Pyrazinamide_R_mutations","Pyrazinamide_Prediction","Mykrobe_gyrA","Moxifloxacin_Ofloxacin_R_mutations","Moxifloxacin_Ofloxacin_Prediction","Mykrobe_rpsL","Mykrobe_Streptomycin_rrs","Mykrobe_Streptomycin_gid","Streptomycin_R_mutations","Streptomycin_Prediction","Mykrobe_Amikacin_rrs","Amikacin_R_mutations","Amikacin_Prediction","Mykrobe_Capreomycin_rrs","Mykrobe_Capreomycin_tlyA","Capreomycin_R_mutations","Capreomycin_Prediction","Mykrobe_Kanamycin_rrs","Mykrobe_Kanamycin_eis","Kanamycin_R_mutations","Kanamycin_Prediction","Lims_Comment","Lims_INTComment","Mykrobe_Workflow_Version","mykrobe_version","Mykrobe_Resistance_probe_set","Mykrobe_min_depth_default_5","Mykrobe_min_conf_default_10","LIMS_file","LIMS_filename" -"sample","No Mutation","S315N","No Mutation","No Mutation","No Mutation","katG_S315N-S315N:15:0:99999996","R","S450L","rpoB_S450L-S450L:14:0:99999996","R","No Mutation","No Mutation",NA,"S","Q141P","No Mutation","pncA_Q141P-Q141P:14:0:99999996","R","No Mutation",NA,"S","K43R","No Mutation","No Mutation","rpsL_K43R-K43R:24:0:99999995","R","A1401G","rrs_A1401G-A1401G:17:0:99999996","R","A1401G","No Mutation","rrs_A1401G-A1401G:17:0:99999996","R","A1401G","No Mutation","rrs_A1401G-A1401G:17:0:99999996","R","","","","v0.5.6-0-gbd7923a-dirty","tb-walker-probe-set-feb-09-2017.fasta.gz","5","10","","" +"file","Mykrobe_fabG1","Mykrobe_katG","Mykrobe_ahpC","Mykrobe_inhA","Mykrobe_ndh","Isoniazid_R_mutations","Isoniazid_Prediction","Mykrobe_rpoB","Rifampicin_R_mutations","Rifampicin_Prediction","Mykrobe_embB","Mykrobe_embA","Ethambutol_R_mutations","Ethambutol_Prediction","Mykrobe_pncA","Mykrobe_rpsA","Pyrazinamide_R_mutations","Pyrazinamide_Prediction","Mykrobe_Ofloxacin_gyrA","Ofloxacin_R_mutations","Ofloxacin_Prediction","Mykrobe_Moxifloxacin_gyrA","Moxifloxacin_R_mutations","Moxifloxacin_Prediction","Mykrobe_Ciprofloxacin_gyrA","Ciprofloxacin_R_mutations","Ciprofloxacin_Prediction","Mykrobe_rpsL","Mykrobe_Streptomycin_rrs","Mykrobe_Streptomycin_gid","Streptomycin_R_mutations","Streptomycin_Prediction","Mykrobe_Amikacin_rrs","Amikacin_R_mutations","Amikacin_Prediction","Mykrobe_Capreomycin_rrs","Mykrobe_Capreomycin_tlyA","Capreomycin_R_mutations","Capreomycin_Prediction","Mykrobe_Kanamycin_rrs","Mykrobe_Kanamycin_eis","Kanamycin_R_mutations","Kanamycin_Prediction","Lims_Comment","Lims_INTComment","Mykrobe_Workflow_Version","mykrobe_version","Mykrobe_Resistance_probe_set","Mykrobe_min_depth_default_5","Mykrobe_min_conf_default_10","LIMS_file","Mutation_set_version" +"sample","No Mutation","S315N","No Mutation","No Mutation","No Mutation","katG_S315N-S315N:15:0:99999996","R","S450L","rpoB_S450L-S450L:14:0:99999996","R","No Mutation","No Mutation",NA,"S","Q141P","No Mutation","pncA_Q141P-Q141P:14:0:99999996","R","No Mutation",NA,NA,"No Mutation",NA,NA,"No Mutation",NA,NA,"K43R","No Mutation","No Mutation","rpsL_K43R-K43R:24:0:99999995","R","A1401G","rrs_A1401G-A1401G:17:0:99999996","R","A1401G","No Mutation","rrs_A1401G-A1401G:17:0:99999996","R","A1401G","No Mutation","rrs_A1401G-A1401G:17:0:99999996","R","","","","v0.5.6-0-gbd7923a-dirty","tb-walker-probe-set-feb-09-2017.fasta.gz","5","10","",""
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/prediction_2019/data/ERR031480_L6.json Fri Sep 22 17:24:02 2023 +0000 @@ -0,0 +1,79 @@ +{ + "ERR031480_L6": { + "susceptibility": { + "Ofloxacin": { + "predict": "S" + }, + "Moxifloxacin": { + "predict": "S" + }, + "Isoniazid": { + "predict": "S" + }, + "Kanamycin": { + "predict": "S" + }, + "Ethambutol": { + "predict": "S" + }, + "Streptomycin": { + "predict": "S" + }, + "Ciprofloxacin": { + "predict": "S" + }, + "Pyrazinamide": { + "predict": "S" + }, + "Rifampicin": { + "predict": "S" + }, + "Amikacin": { + "predict": "S" + }, + "Capreomycin": { + "predict": "S" + } + }, + "phylogenetics": { + "phylo_group": { + "Mycobacterium_tuberculosis_complex": { + "percent_coverage": 99.776, + "median_depth": 136.0 + } + }, + "sub_complex": { + "Unknown": { + "percent_coverage": -1, + "median_depth": -1 + } + }, + "species": { + "Mycobacterium_africanum": { + "percent_coverage": 89.738, + "median_depth": 167 + } + }, + "lineage": { + "West_Africa": { + "percent_coverage": 100.0, + "median_depth": 110 + } + } + }, + "kmer": 21, + "probe_sets": [ + "tb-species-170421.fasta.gz", + "tb-hunt-probe-set-jan-03-2019.fasta.gz" + ], + "files": [ + "ERR031480_1.fastq", + "ERR031480_2.fastq" + ], + "version": { + "mykrobe-predictor": "v0.10.0", + "mykrobe-atlas": "v0.10.0" + }, + "genotype_model": "kmer_count" + } +}
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/prediction_2019/data/ERR125628_MBOV.json Fri Sep 22 17:24:02 2023 +0000 @@ -0,0 +1,118 @@ +{ + "ERR125628_MBOV": { + "susceptibility": { + "Ofloxacin": { + "predict": "S" + }, + "Moxifloxacin": { + "predict": "S" + }, + "Isoniazid": { + "predict": "S" + }, + "Kanamycin": { + "predict": "S" + }, + "Ethambutol": { + "predict": "S" + }, + "Streptomycin": { + "predict": "S" + }, + "Ciprofloxacin": { + "predict": "S" + }, + "Pyrazinamide": { + "predict": "R", + "called_by": { + "pncA_H57D-GTG2289071GTC": { + "variant": null, + "genotype": [ + 1, + 1 + ], + "genotype_likelihoods": [ + -5562.061052007205, + -99999999, + -89.506424216315 + ], + "info": { + "coverage": { + "reference": { + "percent_coverage": 5.0, + "median_depth": 0, + "min_non_zero_depth": 44, + "kmer_count": 44, + "klen": 21 + }, + "alternate": { + "percent_coverage": 100.0, + "median_depth": 46, + "min_non_zero_depth": 44, + "kmer_count": 837, + "klen": 19 + } + }, + "expected_depths": [ + 56.0 + ], + "contamination_depths": [], + "filter": [], + "conf": 5473 + }, + "_cls": "Call.VariantCall" + } + } + }, + "Rifampicin": { + "predict": "S" + }, + "Amikacin": { + "predict": "S" + }, + "Capreomycin": { + "predict": "S" + } + }, + "phylogenetics": { + "phylo_group": { + "Mycobacterium_tuberculosis_complex": { + "percent_coverage": 99.425, + "median_depth": 56.0 + } + }, + "sub_complex": { + "Unknown": { + "percent_coverage": -1, + "median_depth": -1 + } + }, + "species": { + "Mycobacterium_bovis": { + "percent_coverage": 65.402, + "median_depth": 48.0 + } + }, + "lineage": { + "Unknown": { + "percent_coverage": -1, + "median_depth": -1 + } + } + }, + "kmer": 21, + "probe_sets": [ + "tb-species-170421.fasta.gz", + "tb-hunt-probe-set-jan-03-2019.fasta.gz" + ], + "files": [ + "ERR125628_1.fastq", + "ERR125628_2.fastq" + ], + "version": { + "mykrobe-predictor": "v0.10.0", + "mykrobe-atlas": "v0.10.0" + }, + "genotype_model": "kmer_count" + } +}
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/prediction_2019/data/ERR181314_L9.json Fri Sep 22 17:24:02 2023 +0000 @@ -0,0 +1,79 @@ +{ + "ERR181314_L9": { + "susceptibility": { + "Ofloxacin": { + "predict": "S" + }, + "Moxifloxacin": { + "predict": "S" + }, + "Isoniazid": { + "predict": "S" + }, + "Kanamycin": { + "predict": "S" + }, + "Ethambutol": { + "predict": "S" + }, + "Streptomycin": { + "predict": "S" + }, + "Ciprofloxacin": { + "predict": "S" + }, + "Pyrazinamide": { + "predict": "S" + }, + "Rifampicin": { + "predict": "S" + }, + "Amikacin": { + "predict": "S" + }, + "Capreomycin": { + "predict": "S" + } + }, + "phylogenetics": { + "phylo_group": { + "Mycobacterium_tuberculosis_complex": { + "percent_coverage": 99.672, + "median_depth": 171.0 + } + }, + "sub_complex": { + "Unknown": { + "percent_coverage": -1, + "median_depth": -1 + } + }, + "species": { + "Mycobacterium_africanum": { + "percent_coverage": 75.016, + "median_depth": 90.5 + } + }, + "lineage": { + "Unknown": { + "percent_coverage": -1, + "median_depth": -1 + } + } + }, + "kmer": 21, + "probe_sets": [ + "tb-species-170421.fasta.gz", + "tb-hunt-probe-set-jan-03-2019.fasta.gz" + ], + "files": [ + "ERR181314_1.fastq", + "ERR181314_2.fastq" + ], + "version": { + "mykrobe-predictor": "v0.10.0", + "mykrobe-atlas": "v0.10.0" + }, + "genotype_model": "kmer_count" + } +}
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/prediction_2019/data/ERR234162_L3.json Fri Sep 22 17:24:02 2023 +0000 @@ -0,0 +1,79 @@ +{ + "ERR234162_L3": { + "susceptibility": { + "Ofloxacin": { + "predict": "S" + }, + "Moxifloxacin": { + "predict": "S" + }, + "Isoniazid": { + "predict": "S" + }, + "Kanamycin": { + "predict": "S" + }, + "Ethambutol": { + "predict": "S" + }, + "Streptomycin": { + "predict": "S" + }, + "Ciprofloxacin": { + "predict": "S" + }, + "Pyrazinamide": { + "predict": "S" + }, + "Rifampicin": { + "predict": "S" + }, + "Amikacin": { + "predict": "S" + }, + "Capreomycin": { + "predict": "S" + } + }, + "phylogenetics": { + "phylo_group": { + "Mycobacterium_tuberculosis_complex": { + "percent_coverage": 99.797, + "median_depth": 157.0 + } + }, + "sub_complex": { + "Unknown": { + "percent_coverage": -1, + "median_depth": -1 + } + }, + "species": { + "Mycobacterium_tuberculosis": { + "percent_coverage": 99.33, + "median_depth": 142.0 + } + }, + "lineage": { + "Delhi_Central_Asia": { + "percent_coverage": 100.0, + "median_depth": 182 + } + } + }, + "kmer": 21, + "probe_sets": [ + "tb-species-170421.fasta.gz", + "tb-hunt-probe-set-jan-03-2019.fasta.gz" + ], + "files": [ + "ERR234162_1.fastq", + "ERR234162_2.fastq" + ], + "version": { + "mykrobe-predictor": "v0.10.0", + "mykrobe-atlas": "v0.10.0" + }, + "genotype_model": "kmer_count" + } +}
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/prediction_2019/data/ERR2659153.json Fri Sep 22 17:24:02 2023 +0000 @@ -0,0 +1,79 @@ +{ + "ERR2659153": { + "susceptibility": { + "Ofloxacin": { + "predict": "S" + }, + "Moxifloxacin": { + "predict": "S" + }, + "Isoniazid": { + "predict": "S" + }, + "Kanamycin": { + "predict": "S" + }, + "Ethambutol": { + "predict": "S" + }, + "Streptomycin": { + "predict": "S" + }, + "Ciprofloxacin": { + "predict": "S" + }, + "Pyrazinamide": { + "predict": "S" + }, + "Rifampicin": { + "predict": "S" + }, + "Amikacin": { + "predict": "S" + }, + "Capreomycin": { + "predict": "S" + } + }, + "phylogenetics": { + "phylo_group": { + "Mycobacterium_tuberculosis_complex": { + "percent_coverage": 99.492, + "median_depth": 75 + } + }, + "sub_complex": { + "Unknown": { + "percent_coverage": -1, + "median_depth": -1 + } + }, + "species": { + "Mycobacterium_africanum": { + "percent_coverage": 64.411, + "median_depth": 79.0 + } + }, + "lineage": { + "Unknown": { + "percent_coverage": -1, + "median_depth": -1 + } + } + }, + "kmer": 21, + "probe_sets": [ + "tb-species-170421.fasta.gz", + "tb-hunt-probe-set-jan-03-2019.fasta.gz" + ], + "files": [ + "ERR2659153_1.fastq", + "ERR2659153_2.fastq" + ], + "version": { + "mykrobe-predictor": "v0.10.0", + "mykrobe-atlas": "v0.10.0" + }, + "genotype_model": "kmer_count" + } +}
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/prediction_2019/data/ERR3335753_L1.json Fri Sep 22 17:24:02 2023 +0000 @@ -0,0 +1,231 @@ +{ + "ERR3335753_L1": { + "susceptibility": { + "Ofloxacin": { + "predict": "S" + }, + "Moxifloxacin": { + "predict": "S" + }, + "Isoniazid": { + "predict": "S" + }, + "Kanamycin": { + "predict": "S" + }, + "Ethambutol": { + "predict": "S" + }, + "Streptomycin": { + "predict": "S" + }, + "Ciprofloxacin": { + "predict": "S" + }, + "Pyrazinamide": { + "predict": "r", + "called_by": { + "pncA_T389TG-A2288853CA": { + "variant": null, + "genotype": [ + 0, + 1 + ], + "genotype_likelihoods": [ + -1707.2912821258215, + -685.0256738025864, + -10049.785656880731 + ], + "info": { + "coverage": { + "reference": { + "percent_coverage": 100.0, + "median_depth": 131, + "min_non_zero_depth": 128, + "kmer_count": 2768, + "klen": 21 + }, + "alternate": { + "percent_coverage": 100.0, + "median_depth": 43, + "min_non_zero_depth": 41, + "kmer_count": 779, + "klen": 19 + } + }, + "expected_depths": [ + 236.0 + ], + "contamination_depths": [], + "filter": [], + "conf": 1022 + }, + "_cls": "Call.VariantCall" + }, + "pncA_G390GG-C2288852CC": { + "variant": null, + "genotype": [ + 0, + 1 + ], + "genotype_likelihoods": [ + -1736.2599622230955, + -680.8401734761619, + -9873.233821297094 + ], + "info": { + "coverage": { + "reference": { + "percent_coverage": 100.0, + "median_depth": 130, + "min_non_zero_depth": 128, + "kmer_count": 2719, + "klen": 21 + }, + "alternate": { + "percent_coverage": 100.0, + "median_depth": 43, + "min_non_zero_depth": 41, + "kmer_count": 779, + "klen": 19 + } + }, + "expected_depths": [ + 236.0 + ], + "contamination_depths": [], + "filter": [], + "conf": 1055 + }, + "_cls": "Call.VariantCall" + }, + "pncA_G391GG-C2288851CC": { + "variant": null, + "genotype": [ + 0, + 1 + ], + "genotype_likelihoods": [ + -1738.6635171276575, + -680.5372646726655, + -9858.860191248112 + ], + "info": { + "coverage": { + "reference": { + "percent_coverage": 100.0, + "median_depth": 130, + "min_non_zero_depth": 128, + "kmer_count": 2715, + "klen": 21 + }, + "alternate": { + "percent_coverage": 100.0, + "median_depth": 43, + "min_non_zero_depth": 41, + "kmer_count": 779, + "klen": 19 + } + }, + "expected_depths": [ + 236.0 + ], + "contamination_depths": [], + "filter": [], + "conf": 1058 + }, + "_cls": "Call.VariantCall" + } + } + }, + "Rifampicin": { + "predict": "R", + "called_by": { + "rpoB_L430P-CTG761094CCG": { + "variant": null, + "genotype": [ + 1, + 1 + ], + "genotype_likelihoods": [ + -14797.71027662235, + -2370.6712704022216, + -210.1929350878079 + ], + "info": { + "coverage": { + "reference": { + "percent_coverage": 100.0, + "median_depth": 5, + "min_non_zero_depth": 3, + "kmer_count": 101, + "klen": 21 + }, + "alternate": { + "percent_coverage": 100.0, + "median_depth": 190, + "min_non_zero_depth": 188, + "kmer_count": 3622, + "klen": 20 + } + }, + "expected_depths": [ + 236.0 + ], + "contamination_depths": [], + "filter": [], + "conf": 14588 + }, + "_cls": "Call.VariantCall" + } + } + }, + "Amikacin": { + "predict": "S" + }, + "Capreomycin": { + "predict": "S" + } + }, + "phylogenetics": { + "phylo_group": { + "Mycobacterium_tuberculosis_complex": { + "percent_coverage": 99.69, + "median_depth": 236.0 + } + }, + "sub_complex": { + "Unknown": { + "percent_coverage": -1, + "median_depth": -1 + } + }, + "species": { + "Mycobacterium_tuberculosis": { + "percent_coverage": 98.335, + "median_depth": 220 + } + }, + "lineage": { + "East_Africa_Indian_ocean": { + "percent_coverage": 100.0, + "median_depth": 193 + } + } + }, + "kmer": 21, + "probe_sets": [ + "tb-species-170421.fasta.gz", + "tb-hunt-probe-set-jan-03-2019.fasta.gz" + ], + "files": [ + "ERR3335753_1.fastq", + "ERR3335753_2.fastq" + ], + "version": { + "mykrobe-predictor": "v0.10.0", + "mykrobe-atlas": "v0.10.0" + }, + "genotype_model": "kmer_count" + } +}
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/prediction_2019/data/ERR4143897_MPIN.json Fri Sep 22 17:24:02 2023 +0000 @@ -0,0 +1,79 @@ +{ + "ERR4143897_MPIN": { + "susceptibility": { + "Ofloxacin": { + "predict": "S" + }, + "Moxifloxacin": { + "predict": "S" + }, + "Isoniazid": { + "predict": "S" + }, + "Kanamycin": { + "predict": "S" + }, + "Ethambutol": { + "predict": "S" + }, + "Streptomycin": { + "predict": "S" + }, + "Ciprofloxacin": { + "predict": "S" + }, + "Pyrazinamide": { + "predict": "S" + }, + "Rifampicin": { + "predict": "S" + }, + "Amikacin": { + "predict": "S" + }, + "Capreomycin": { + "predict": "S" + } + }, + "phylogenetics": { + "phylo_group": { + "Mycobacterium_tuberculosis_complex": { + "percent_coverage": 99.162, + "median_depth": 61 + } + }, + "sub_complex": { + "Unknown": { + "percent_coverage": -1, + "median_depth": -1 + } + }, + "species": { + "Mycobacterium_microti": { + "percent_coverage": 52.314, + "median_depth": 55.0 + } + }, + "lineage": { + "Unknown": { + "percent_coverage": -1, + "median_depth": -1 + } + } + }, + "kmer": 21, + "probe_sets": [ + "tb-species-170421.fasta.gz", + "tb-hunt-probe-set-jan-03-2019.fasta.gz" + ], + "files": [ + "ERR4143897_1.fastq", + "ERR4143897_2.fastq" + ], + "version": { + "mykrobe-predictor": "v0.10.0", + "mykrobe-atlas": "v0.10.0" + }, + "genotype_model": "kmer_count" + } +}
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/prediction_2019/data/ERR756348_L7.json Fri Sep 22 17:24:02 2023 +0000 @@ -0,0 +1,79 @@ +{ + "ERR756348_L7": { + "susceptibility": { + "Ofloxacin": { + "predict": "S" + }, + "Moxifloxacin": { + "predict": "S" + }, + "Isoniazid": { + "predict": "S" + }, + "Kanamycin": { + "predict": "S" + }, + "Ethambutol": { + "predict": "S" + }, + "Streptomycin": { + "predict": "S" + }, + "Ciprofloxacin": { + "predict": "S" + }, + "Pyrazinamide": { + "predict": "S" + }, + "Rifampicin": { + "predict": "S" + }, + "Amikacin": { + "predict": "S" + }, + "Capreomycin": { + "predict": "S" + } + }, + "phylogenetics": { + "phylo_group": { + "Mycobacterium_tuberculosis_complex": { + "percent_coverage": 99.033, + "median_depth": 173 + } + }, + "sub_complex": { + "Unknown": { + "percent_coverage": -1, + "median_depth": -1 + } + }, + "species": { + "Mycobacterium_tuberculosis": { + "percent_coverage": 83.208, + "median_depth": 162 + } + }, + "lineage": { + "Unknown": { + "percent_coverage": -1, + "median_depth": -1 + } + } + }, + "kmer": 21, + "probe_sets": [ + "tb-species-170421.fasta.gz", + "tb-hunt-probe-set-jan-03-2019.fasta.gz" + ], + "files": [ + "ERR756348_1.fastq", + "ERR756348_2.fastq" + ], + "version": { + "mykrobe-predictor": "v0.10.0", + "mykrobe-atlas": "v0.10.0" + }, + "genotype_model": "kmer_count" + } +}
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/prediction_2019/data/ERR841495_L5.json Fri Sep 22 17:24:02 2023 +0000 @@ -0,0 +1,79 @@ +{ + "ERR841495_L5": { + "susceptibility": { + "Ofloxacin": { + "predict": "S" + }, + "Moxifloxacin": { + "predict": "S" + }, + "Isoniazid": { + "predict": "S" + }, + "Kanamycin": { + "predict": "S" + }, + "Ethambutol": { + "predict": "S" + }, + "Streptomycin": { + "predict": "S" + }, + "Ciprofloxacin": { + "predict": "S" + }, + "Pyrazinamide": { + "predict": "S" + }, + "Rifampicin": { + "predict": "S" + }, + "Amikacin": { + "predict": "S" + }, + "Capreomycin": { + "predict": "S" + } + }, + "phylogenetics": { + "phylo_group": { + "Mycobacterium_tuberculosis_complex": { + "percent_coverage": 99.715, + "median_depth": 137 + } + }, + "sub_complex": { + "Unknown": { + "percent_coverage": -1, + "median_depth": -1 + } + }, + "species": { + "Mycobacterium_africanum": { + "percent_coverage": 57.895, + "median_depth": 123.0 + } + }, + "lineage": { + "Unknown": { + "percent_coverage": -1, + "median_depth": -1 + } + } + }, + "kmer": 21, + "probe_sets": [ + "tb-species-170421.fasta.gz", + "tb-hunt-probe-set-jan-03-2019.fasta.gz" + ], + "files": [ + "ERR841495_1.fastq", + "ERR841495_2.fastq" + ], + "version": { + "mykrobe-predictor": "v0.10.0", + "mykrobe-atlas": "v0.10.0" + }, + "genotype_model": "kmer_count" + } +}
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/prediction_2019/data/SRR17089001.json Fri Sep 22 17:24:02 2023 +0000 @@ -0,0 +1,79 @@ +{ + "SRR17089001": { + "susceptibility": { + "Ofloxacin": { + "predict": "S" + }, + "Moxifloxacin": { + "predict": "S" + }, + "Isoniazid": { + "predict": "S" + }, + "Kanamycin": { + "predict": "S" + }, + "Ethambutol": { + "predict": "S" + }, + "Streptomycin": { + "predict": "S" + }, + "Ciprofloxacin": { + "predict": "S" + }, + "Pyrazinamide": { + "predict": "S" + }, + "Rifampicin": { + "predict": "S" + }, + "Amikacin": { + "predict": "S" + }, + "Capreomycin": { + "predict": "S" + } + }, + "phylogenetics": { + "phylo_group": { + "Mycobacterium_tuberculosis_complex": { + "percent_coverage": 99.448, + "median_depth": 240.0 + } + }, + "sub_complex": { + "Unknown": { + "percent_coverage": -1, + "median_depth": -1 + } + }, + "species": { + "Mycobacterium_africanum": { + "percent_coverage": 54.809, + "median_depth": 263 + } + }, + "lineage": { + "Unknown": { + "percent_coverage": -1, + "median_depth": -1 + } + } + }, + "kmer": 21, + "probe_sets": [ + "tb-species-170421.fasta.gz", + "tb-hunt-probe-set-jan-03-2019.fasta.gz" + ], + "files": [ + "SRR17089001_1.fastq", + "SRR17089001_2.fastq" + ], + "version": { + "mykrobe-predictor": "v0.10.0", + "mykrobe-atlas": "v0.10.0" + }, + "genotype_model": "kmer_count" + } +}
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/prediction_2019/data/SRR1710097_L2.json Fri Sep 22 17:24:02 2023 +0000 @@ -0,0 +1,79 @@ +{ + "SRR1710097_L2": { + "susceptibility": { + "Ofloxacin": { + "predict": "S" + }, + "Moxifloxacin": { + "predict": "S" + }, + "Isoniazid": { + "predict": "S" + }, + "Kanamycin": { + "predict": "S" + }, + "Ethambutol": { + "predict": "S" + }, + "Streptomycin": { + "predict": "S" + }, + "Ciprofloxacin": { + "predict": "S" + }, + "Pyrazinamide": { + "predict": "S" + }, + "Rifampicin": { + "predict": "S" + }, + "Amikacin": { + "predict": "S" + }, + "Capreomycin": { + "predict": "S" + } + }, + "phylogenetics": { + "phylo_group": { + "Mycobacterium_tuberculosis_complex": { + "percent_coverage": 99.686, + "median_depth": 420 + } + }, + "sub_complex": { + "Unknown": { + "percent_coverage": -1, + "median_depth": -1 + } + }, + "species": { + "Mycobacterium_tuberculosis": { + "percent_coverage": 98.909, + "median_depth": 403.0 + } + }, + "lineage": { + "Beijing_East_Asia": { + "percent_coverage": 100.0, + "median_depth": 391 + } + } + }, + "kmer": 21, + "probe_sets": [ + "tb-species-170421.fasta.gz", + "tb-hunt-probe-set-jan-03-2019.fasta.gz" + ], + "files": [ + "SRR1710097_1.fastq", + "SRR1710097_2.fastq" + ], + "version": { + "mykrobe-predictor": "v0.10.0", + "mykrobe-atlas": "v0.10.0" + }, + "genotype_model": "kmer_count" + } +}
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/prediction_2019/data/SRR3500411_MMUN.json Fri Sep 22 17:24:02 2023 +0000 @@ -0,0 +1,79 @@ +{ + "SRR3500411_MMUN": { + "susceptibility": { + "Ofloxacin": { + "predict": "S" + }, + "Moxifloxacin": { + "predict": "S" + }, + "Isoniazid": { + "predict": "S" + }, + "Kanamycin": { + "predict": "S" + }, + "Ethambutol": { + "predict": "S" + }, + "Streptomycin": { + "predict": "S" + }, + "Ciprofloxacin": { + "predict": "S" + }, + "Pyrazinamide": { + "predict": "S" + }, + "Rifampicin": { + "predict": "S" + }, + "Amikacin": { + "predict": "S" + }, + "Capreomycin": { + "predict": "S" + } + }, + "phylogenetics": { + "phylo_group": { + "Mycobacterium_tuberculosis_complex": { + "percent_coverage": 99.568, + "median_depth": 114.0 + } + }, + "sub_complex": { + "Unknown": { + "percent_coverage": -1, + "median_depth": -1 + } + }, + "species": { + "Mycobacterium_africanum": { + "percent_coverage": 62.167, + "median_depth": 94.0 + } + }, + "lineage": { + "Unknown": { + "percent_coverage": -1, + "median_depth": -1 + } + } + }, + "kmer": 21, + "probe_sets": [ + "tb-species-170421.fasta.gz", + "tb-hunt-probe-set-jan-03-2019.fasta.gz" + ], + "files": [ + "SRR3500411_1.fastq", + "SRR3500411_2.fastq" + ], + "version": { + "mykrobe-predictor": "v0.10.0", + "mykrobe-atlas": "v0.10.0" + }, + "genotype_model": "kmer_count" + } +}
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/prediction_2019/data/SRR9157804.json Fri Sep 22 17:24:02 2023 +0000 @@ -0,0 +1,79 @@ +{ + "SRR9157804": { + "susceptibility": { + "Ofloxacin": { + "predict": "S" + }, + "Moxifloxacin": { + "predict": "S" + }, + "Isoniazid": { + "predict": "S" + }, + "Kanamycin": { + "predict": "S" + }, + "Ethambutol": { + "predict": "S" + }, + "Streptomycin": { + "predict": "S" + }, + "Ciprofloxacin": { + "predict": "S" + }, + "Pyrazinamide": { + "predict": "S" + }, + "Rifampicin": { + "predict": "S" + }, + "Amikacin": { + "predict": "S" + }, + "Capreomycin": { + "predict": "S" + } + }, + "phylogenetics": { + "phylo_group": { + "Mycobacterium_tuberculosis_complex": { + "percent_coverage": 99.547, + "median_depth": 123 + } + }, + "sub_complex": { + "Unknown": { + "percent_coverage": -1, + "median_depth": -1 + } + }, + "species": { + "Mycobacterium_africanum": { + "percent_coverage": 55.332, + "median_depth": 111.0 + } + }, + "lineage": { + "Unknown": { + "percent_coverage": -1, + "median_depth": -1 + } + } + }, + "kmer": 21, + "probe_sets": [ + "tb-species-170421.fasta.gz", + "tb-hunt-probe-set-jan-03-2019.fasta.gz" + ], + "files": [ + "SRR9157804_1.fastq", + "SRR9157804_2.fastq" + ], + "version": { + "mykrobe-predictor": "v0.10.0", + "mykrobe-atlas": "v0.10.0" + }, + "genotype_model": "kmer_count" + } +}
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/prediction_2019/output-jsondata.csv Fri Sep 22 17:24:02 2023 +0000 @@ -0,0 +1,16 @@ +"file","phylo_group","species","lineage","phylo_group_per_covg","species_per_covg","lineage_per_covg","phylo_group_depth","species_depth","lineage_depth" +"ERR031480_L6","Mycobacterium_tuberculosis_complex","Mycobacterium_africanum","West_Africa",99.776,89.738,100,136,167,110 +"ERR125628_MBOV","Mycobacterium_tuberculosis_complex","Mycobacterium_bovis","Unknown",99.425,65.402,-1,56,48,-1 +"ERR181314_L9","Mycobacterium_tuberculosis_complex","Mycobacterium_africanum","Unknown",99.672,75.016,-1,171,90.5,-1 +"ERR234162_L3","Mycobacterium_tuberculosis_complex","Mycobacterium_tuberculosis","Delhi_Central_Asia",99.797,99.33,100,157,142,182 +"ERR2659153","Mycobacterium_tuberculosis_complex","Mycobacterium_africanum","Unknown",99.492,64.411,-1,75,79,-1 +"ERR266106_MCAN","Mycobacterium_tuberculosis_complex","Mycobacterium_tuberculosis","Mycobacterium_tuberculosis_subsp_canettii",98.352,73.899,63.718,100,92,94 +"ERR2704812_L5","Mycobacterium_tuberculosis_complex","Mycobacterium_africanum","Unknown",98.467,64.333,-1,332,326,-1 +"ERR3335753_L1","Mycobacterium_tuberculosis_complex","Mycobacterium_tuberculosis","East_Africa_Indian_ocean",99.69,98.335,100,236,220,193 +"ERR4143897_MPIN","Mycobacterium_tuberculosis_complex","Mycobacterium_microti","Unknown",99.162,52.314,-1,61,55,-1 +"ERR756348_L7","Mycobacterium_tuberculosis_complex","Mycobacterium_tuberculosis","Unknown",99.033,83.208,-1,173,162,-1 +"ERR841495_L5","Mycobacterium_tuberculosis_complex","Mycobacterium_africanum","Unknown",99.715,57.895,-1,137,123,-1 +"SRR17089001","Mycobacterium_tuberculosis_complex","Mycobacterium_africanum","Unknown",99.448,54.809,-1,240,263,-1 +"SRR1710097_L2","Mycobacterium_tuberculosis_complex","Mycobacterium_tuberculosis","Beijing_East_Asia",99.686,98.909,100,420,403,391 +"SRR3500411_MMUN","Mycobacterium_tuberculosis_complex","Mycobacterium_africanum","Unknown",99.568,62.167,-1,114,94,-1 +"SRR9157804","Mycobacterium_tuberculosis_complex","Mycobacterium_africanum","Unknown",99.547,55.332,-1,123,111,-1
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/prediction_2020/data/SRR1710097_L2.json Fri Sep 22 17:24:02 2023 +0000 @@ -0,0 +1,211 @@ +{ + "SRR1710097_L2": { + "susceptibility": { + "Ofloxacin": { + "predict": "S" + }, + "Moxifloxacin": { + "predict": "S" + }, + "Isoniazid": { + "predict": "S" + }, + "Kanamycin": { + "predict": "S" + }, + "Ethambutol": { + "predict": "S" + }, + "Streptomycin": { + "predict": "S" + }, + "Ciprofloxacin": { + "predict": "S" + }, + "Pyrazinamide": { + "predict": "S" + }, + "Rifampicin": { + "predict": "S" + }, + "Amikacin": { + "predict": "S" + }, + "Capreomycin": { + "predict": "S" + } + }, + "phylogenetics": { + "phylo_group": { + "Mycobacterium_tuberculosis_complex": { + "percent_coverage": 99.686, + "median_depth": 420 + } + }, + "sub_complex": { + "Unknown": { + "percent_coverage": -1, + "median_depth": -1 + } + }, + "species": { + "Mycobacterium_tuberculosis": { + "percent_coverage": 98.909, + "median_depth": 403.0 + } + }, + "lineage": { + "lineage": [ + "lineage2.2.4" + ], + "calls_summary": { + "lineage2.2.4": { + "good_nodes": 3, + "tree_depth": 3, + "genotypes": { + "lineage2": 1, + "lineage2.2": 1, + "lineage2.2.4": 1 + } + } + }, + "calls": { + "lineage2.2.4": { + "lineage2": { + "G497491A": { + "variant": "ref-G497491A?var_name=G497491A&num_alts=1&ref=NC_000962.3&enum=0&gene=NA&mut=G497491A", + "genotype": [ + 1, + 1 + ], + "genotype_likelihoods": [ + -53081.870411575976, + -99999999, + -401.73206510437967 + ], + "info": { + "coverage": { + "reference": { + "percent_coverage": 0.0, + "median_depth": 0, + "min_non_zero_depth": 0, + "kmer_count": 0, + "klen": 21 + }, + "alternate": { + "percent_coverage": 100.0, + "median_depth": 438, + "min_non_zero_depth": 424, + "kmer_count": 8731, + "klen": 21 + } + }, + "expected_depths": [ + 420 + ], + "contamination_depths": [], + "filter": [], + "conf": 52680 + }, + "_cls": "Call.VariantCall" + } + }, + "lineage2.2": { + "G2505085A": { + "variant": "ref-G2505085A?var_name=G2505085A&num_alts=2&ref=NC_000962.3&enum=0&gene=NA&mut=G2505085A", + "genotype": [ + 1, + 1 + ], + "genotype_likelihoods": [ + -49633.185227023845, + -99999999, + -453.6542893522951 + ], + "info": { + "coverage": { + "reference": { + "percent_coverage": 0.0, + "median_depth": 0, + "min_non_zero_depth": 0, + "kmer_count": 0, + "klen": 21 + }, + "alternate": { + "percent_coverage": 100.0, + "median_depth": 418, + "min_non_zero_depth": 262, + "kmer_count": 7876, + "klen": 21 + } + }, + "expected_depths": [ + 420 + ], + "contamination_depths": [], + "filter": [], + "conf": 49180 + }, + "_cls": "Call.VariantCall" + } + }, + "lineage2.2.4": { + "A782634G": { + "variant": "ref-A782634G?var_name=A782634G&num_alts=1&ref=NC_000962.3&enum=0&gene=NA&mut=A782634G", + "genotype": [ + 1, + 1 + ], + "genotype_likelihoods": [ + -52377.030507181364, + -99999999, + -405.20219781199785 + ], + "info": { + "coverage": { + "reference": { + "percent_coverage": 0.0, + "median_depth": 0, + "min_non_zero_depth": 0, + "kmer_count": 0, + "klen": 21 + }, + "alternate": { + "percent_coverage": 100.0, + "median_depth": 427, + "min_non_zero_depth": 414, + "kmer_count": 8558, + "klen": 21 + } + }, + "expected_depths": [ + 420 + ], + "contamination_depths": [], + "filter": [], + "conf": 51972 + }, + "_cls": "Call.VariantCall" + } + } + } + } + } + }, + "kmer": 21, + "probe_sets": [ + "tb-species-170421.fasta.gz", + "tb-hunt-probe-set-jan-03-2019.fasta.gz", + "tb.lineage.20200930.probes.fa.gz" + ], + "files": [ + "SRR1710097_1.fastq", + "SRR1710097_2.fastq" + ], + "version": { + "mykrobe-predictor": "v0.10.0", + "mykrobe-atlas": "v0.10.0" + }, + "genotype_model": "kmer_count" + } +}
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/prediction_2020/data/SRR3500411_MMUN.json Fri Sep 22 17:24:02 2023 +0000 @@ -0,0 +1,131 @@ +{ + "SRR3500411_MMUN": { + "susceptibility": { + "Ofloxacin": { + "predict": "S" + }, + "Moxifloxacin": { + "predict": "S" + }, + "Isoniazid": { + "predict": "S" + }, + "Kanamycin": { + "predict": "S" + }, + "Ethambutol": { + "predict": "S" + }, + "Streptomycin": { + "predict": "S" + }, + "Ciprofloxacin": { + "predict": "S" + }, + "Pyrazinamide": { + "predict": "S" + }, + "Rifampicin": { + "predict": "S" + }, + "Amikacin": { + "predict": "S" + }, + "Capreomycin": { + "predict": "S" + } + }, + "phylogenetics": { + "phylo_group": { + "Mycobacterium_tuberculosis_complex": { + "percent_coverage": 99.568, + "median_depth": 114.0 + } + }, + "sub_complex": { + "Unknown": { + "percent_coverage": -1, + "median_depth": -1 + } + }, + "species": { + "Mycobacterium_africanum": { + "percent_coverage": 62.167, + "median_depth": 94.0 + } + }, + "lineage": { + "lineage": [ + "clade_animal_A1" + ], + "calls_summary": { + "clade_animal_A1": { + "good_nodes": 1, + "tree_depth": 1, + "genotypes": { + "clade_animal_A1": 1 + } + } + }, + "calls": { + "clade_animal_A1": { + "clade_animal_A1": { + "G2873278T": { + "variant": "ref-G2873278T?var_name=G2873278T&num_alts=1&ref=NC_000962.3&enum=0&gene=NA&mut=G2873278T", + "genotype": [ + 1, + 1 + ], + "genotype_likelihoods": [ + -11085.68809338619, + -99999999, + -274.747110554358 + ], + "info": { + "coverage": { + "reference": { + "percent_coverage": 0.0, + "median_depth": 0, + "min_non_zero_depth": 0, + "kmer_count": 0, + "klen": 21 + }, + "alternate": { + "percent_coverage": 100.0, + "median_depth": 76, + "min_non_zero_depth": 71, + "kmer_count": 1518, + "klen": 21 + } + }, + "expected_depths": [ + 114.0 + ], + "contamination_depths": [], + "filter": [], + "conf": 10811 + }, + "_cls": "Call.VariantCall" + } + } + } + } + } + }, + "kmer": 21, + "probe_sets": [ + "tb-species-170421.fasta.gz", + "tb-hunt-probe-set-jan-03-2019.fasta.gz", + "tb.lineage.20200930.probes.fa.gz" + ], + "files": [ + "SRR3500411_1.fastq", + "SRR3500411_2.fastq" + ], + "version": { + "mykrobe-predictor": "v0.10.0", + "mykrobe-atlas": "v0.10.0" + }, + "genotype_model": "kmer_count" + } +}
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/prediction_2020/data/SRR9157804.json Fri Sep 22 17:24:02 2023 +0000 @@ -0,0 +1,131 @@ +{ + "SRR9157804": { + "susceptibility": { + "Ofloxacin": { + "predict": "S" + }, + "Moxifloxacin": { + "predict": "S" + }, + "Isoniazid": { + "predict": "S" + }, + "Kanamycin": { + "predict": "S" + }, + "Ethambutol": { + "predict": "S" + }, + "Streptomycin": { + "predict": "S" + }, + "Ciprofloxacin": { + "predict": "S" + }, + "Pyrazinamide": { + "predict": "S" + }, + "Rifampicin": { + "predict": "S" + }, + "Amikacin": { + "predict": "S" + }, + "Capreomycin": { + "predict": "S" + } + }, + "phylogenetics": { + "phylo_group": { + "Mycobacterium_tuberculosis_complex": { + "percent_coverage": 99.547, + "median_depth": 123 + } + }, + "sub_complex": { + "Unknown": { + "percent_coverage": -1, + "median_depth": -1 + } + }, + "species": { + "Mycobacterium_africanum": { + "percent_coverage": 55.332, + "median_depth": 111.0 + } + }, + "lineage": { + "lineage": [ + "clade_animal_A3" + ], + "calls_summary": { + "clade_animal_A3": { + "good_nodes": 1, + "tree_depth": 1, + "genotypes": { + "clade_animal_A3": 1 + } + } + }, + "calls": { + "clade_animal_A3": { + "clade_animal_A3": { + "T154276G": { + "variant": "ref-T154276G?var_name=T154276G&num_alts=2&ref=NC_000962.3&enum=0&gene=NA&mut=T154276G", + "genotype": [ + 1, + 1 + ], + "genotype_likelihoods": [ + -14665.93874938906, + -99999999, + -110.38044076914989 + ], + "info": { + "coverage": { + "reference": { + "percent_coverage": 0.0, + "median_depth": 0, + "min_non_zero_depth": 0, + "kmer_count": 0, + "klen": 21 + }, + "alternate": { + "percent_coverage": 100.0, + "median_depth": 117, + "min_non_zero_depth": 114, + "kmer_count": 2344, + "klen": 21 + } + }, + "expected_depths": [ + 123 + ], + "contamination_depths": [], + "filter": [], + "conf": 14556 + }, + "_cls": "Call.VariantCall" + } + } + } + } + } + }, + "kmer": 21, + "probe_sets": [ + "tb-species-170421.fasta.gz", + "tb-hunt-probe-set-jan-03-2019.fasta.gz", + "tb.lineage.20200930.probes.fa.gz" + ], + "files": [ + "SRR9157804_1.fastq", + "SRR9157804_2.fastq" + ], + "version": { + "mykrobe-predictor": "v0.10.0", + "mykrobe-atlas": "v0.10.0" + }, + "genotype_model": "kmer_count" + } +}
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/prediction_2020/output-jsondata.csv Fri Sep 22 17:24:02 2023 +0000 @@ -0,0 +1,16 @@ +"file","phylo_group","species","phylo_group_per_covg","species_per_covg","phylo_group_depth","species_depth" +"ERR031480_L6","Mycobacterium_tuberculosis_complex","Mycobacterium_africanum",99.776,89.738,136,167 +"ERR125628_MBOV","Mycobacterium_tuberculosis_complex","Mycobacterium_bovis",99.425,65.402,56,48 +"ERR181314_L9","Mycobacterium_tuberculosis_complex","Mycobacterium_africanum",99.672,75.016,171,90.5 +"ERR234162_L3","Mycobacterium_tuberculosis_complex","Mycobacterium_tuberculosis",99.797,99.33,157,142 +"ERR2659153","Mycobacterium_tuberculosis_complex","Mycobacterium_africanum",99.492,64.411,75,79 +"ERR266106_MCAN","Mycobacterium_tuberculosis_complex","Mycobacterium_tuberculosis",98.352,73.899,100,92 +"ERR2704812_L5","Mycobacterium_tuberculosis_complex","Mycobacterium_africanum",98.467,64.333,332,326 +"ERR3335753_L1","Mycobacterium_tuberculosis_complex","Mycobacterium_tuberculosis",99.69,98.335,236,220 +"ERR4143897_MPIN","Mycobacterium_tuberculosis_complex","Mycobacterium_microti",99.162,52.314,61,55 +"ERR756348_L7","Mycobacterium_tuberculosis_complex","Mycobacterium_tuberculosis",99.033,83.208,173,162 +"ERR841495_L5","Mycobacterium_tuberculosis_complex","Mycobacterium_africanum",99.715,57.895,137,123 +"SRR17089001","Mycobacterium_tuberculosis_complex","Mycobacterium_africanum",99.448,54.809,240,263 +"SRR1710097_L2","Mycobacterium_tuberculosis_complex","Mycobacterium_tuberculosis",99.686,98.909,420,403 +"SRR3500411_MMUN","Mycobacterium_tuberculosis_complex","Mycobacterium_africanum",99.568,62.167,114,94 +"SRR9157804","Mycobacterium_tuberculosis_complex","Mycobacterium_africanum",99.547,55.332,123,111
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/single_2019/output-jsondata.csv Fri Sep 22 17:24:02 2023 +0000 @@ -0,0 +1,2 @@ +"file","phylo_group","species","lineage","phylo_group_per_covg","species_per_covg","lineage_per_covg","phylo_group_depth","species_depth","lineage_depth" +"ERR3335753_L1","Mycobacterium_tuberculosis_complex","Mycobacterium_tuberculosis","East_Africa_Indian_ocean",99.69,98.335,100,236,220,193
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/single_2019/output-report.csv Fri Sep 22 17:24:02 2023 +0000 @@ -0,0 +1,2 @@ +"file","Mykrobe_fabG1","Mykrobe_katG","Mykrobe_ahpC","Mykrobe_inhA","Mykrobe_ndh","Isoniazid_R_mutations","Isoniazid_Prediction","Mykrobe_rpoB","Rifampicin_R_mutations","Rifampicin_Prediction","Mykrobe_embB","Mykrobe_embA","Ethambutol_R_mutations","Ethambutol_Prediction","Mykrobe_pncA","Mykrobe_rpsA","Pyrazinamide_R_mutations","Pyrazinamide_Prediction","Mykrobe_Ofloxacin_gyrA","Ofloxacin_R_mutations","Ofloxacin_Prediction","Mykrobe_Moxifloxacin_gyrA","Moxifloxacin_R_mutations","Moxifloxacin_Prediction","Mykrobe_Ciprofloxacin_gyrA","Ciprofloxacin_R_mutations","Ciprofloxacin_Prediction","Mykrobe_rpsL","Mykrobe_Streptomycin_rrs","Mykrobe_Streptomycin_gid","Streptomycin_R_mutations","Streptomycin_Prediction","Mykrobe_Amikacin_rrs","Amikacin_R_mutations","Amikacin_Prediction","Mykrobe_Capreomycin_rrs","Mykrobe_Capreomycin_tlyA","Capreomycin_R_mutations","Capreomycin_Prediction","Mykrobe_Kanamycin_rrs","Mykrobe_Kanamycin_eis","Kanamycin_R_mutations","Kanamycin_Prediction","Lims_Comment","Lims_INTComment","Mykrobe_Workflow_Version","mykrobe_version","Mykrobe_Resistance_probe_set","Mykrobe_min_depth_default_5","Mykrobe_min_conf_default_10","LIMS_file","Mutation_set_version" +"ERR3335753_L1","No Mutation","No Mutation","No Mutation","No Mutation","No Mutation",NA,"S","L430P","rpoB_L430P-CTG761094CCG:190:5:14588","R","No Mutation","No Mutation",NA,"S","T389TG;G390GG;G391GG","No Mutation","pncA_T389TG-A2288853CA:43:131:1022__pncA_G390GG-C2288852CC:43:130:1055__pncA_G391GG-C2288851CC:43:130:1058","r","No Mutation",NA,"S","No Mutation",NA,"S","No Mutation",NA,"S","No Mutation","No Mutation","No Mutation",NA,"S","No Mutation",NA,"S","No Mutation","No Mutation",NA,"S","No Mutation","No Mutation",NA,"S","","","","v0.10.0","tb-hunt-probe-set-jan-03-2019.fasta.gz","5","10","",""
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/single_2019/single2019.json Fri Sep 22 17:24:02 2023 +0000 @@ -0,0 +1,231 @@ +{ + "ERR3335753_L1": { + "susceptibility": { + "Ofloxacin": { + "predict": "S" + }, + "Moxifloxacin": { + "predict": "S" + }, + "Isoniazid": { + "predict": "S" + }, + "Kanamycin": { + "predict": "S" + }, + "Ethambutol": { + "predict": "S" + }, + "Streptomycin": { + "predict": "S" + }, + "Ciprofloxacin": { + "predict": "S" + }, + "Pyrazinamide": { + "predict": "r", + "called_by": { + "pncA_T389TG-A2288853CA": { + "variant": null, + "genotype": [ + 0, + 1 + ], + "genotype_likelihoods": [ + -1707.2912821258215, + -685.0256738025864, + -10049.785656880731 + ], + "info": { + "coverage": { + "reference": { + "percent_coverage": 100.0, + "median_depth": 131, + "min_non_zero_depth": 128, + "kmer_count": 2768, + "klen": 21 + }, + "alternate": { + "percent_coverage": 100.0, + "median_depth": 43, + "min_non_zero_depth": 41, + "kmer_count": 779, + "klen": 19 + } + }, + "expected_depths": [ + 236.0 + ], + "contamination_depths": [], + "filter": [], + "conf": 1022 + }, + "_cls": "Call.VariantCall" + }, + "pncA_G390GG-C2288852CC": { + "variant": null, + "genotype": [ + 0, + 1 + ], + "genotype_likelihoods": [ + -1736.2599622230955, + -680.8401734761619, + -9873.233821297094 + ], + "info": { + "coverage": { + "reference": { + "percent_coverage": 100.0, + "median_depth": 130, + "min_non_zero_depth": 128, + "kmer_count": 2719, + "klen": 21 + }, + "alternate": { + "percent_coverage": 100.0, + "median_depth": 43, + "min_non_zero_depth": 41, + "kmer_count": 779, + "klen": 19 + } + }, + "expected_depths": [ + 236.0 + ], + "contamination_depths": [], + "filter": [], + "conf": 1055 + }, + "_cls": "Call.VariantCall" + }, + "pncA_G391GG-C2288851CC": { + "variant": null, + "genotype": [ + 0, + 1 + ], + "genotype_likelihoods": [ + -1738.6635171276575, + -680.5372646726655, + -9858.860191248112 + ], + "info": { + "coverage": { + "reference": { + "percent_coverage": 100.0, + "median_depth": 130, + "min_non_zero_depth": 128, + "kmer_count": 2715, + "klen": 21 + }, + "alternate": { + "percent_coverage": 100.0, + "median_depth": 43, + "min_non_zero_depth": 41, + "kmer_count": 779, + "klen": 19 + } + }, + "expected_depths": [ + 236.0 + ], + "contamination_depths": [], + "filter": [], + "conf": 1058 + }, + "_cls": "Call.VariantCall" + } + } + }, + "Rifampicin": { + "predict": "R", + "called_by": { + "rpoB_L430P-CTG761094CCG": { + "variant": null, + "genotype": [ + 1, + 1 + ], + "genotype_likelihoods": [ + -14797.71027662235, + -2370.6712704022216, + -210.1929350878079 + ], + "info": { + "coverage": { + "reference": { + "percent_coverage": 100.0, + "median_depth": 5, + "min_non_zero_depth": 3, + "kmer_count": 101, + "klen": 21 + }, + "alternate": { + "percent_coverage": 100.0, + "median_depth": 190, + "min_non_zero_depth": 188, + "kmer_count": 3622, + "klen": 20 + } + }, + "expected_depths": [ + 236.0 + ], + "contamination_depths": [], + "filter": [], + "conf": 14588 + }, + "_cls": "Call.VariantCall" + } + } + }, + "Amikacin": { + "predict": "S" + }, + "Capreomycin": { + "predict": "S" + } + }, + "phylogenetics": { + "phylo_group": { + "Mycobacterium_tuberculosis_complex": { + "percent_coverage": 99.69, + "median_depth": 236.0 + } + }, + "sub_complex": { + "Unknown": { + "percent_coverage": -1, + "median_depth": -1 + } + }, + "species": { + "Mycobacterium_tuberculosis": { + "percent_coverage": 98.335, + "median_depth": 220 + } + }, + "lineage": { + "East_Africa_Indian_ocean": { + "percent_coverage": 100.0, + "median_depth": 193 + } + } + }, + "kmer": 21, + "probe_sets": [ + "tb-species-170421.fasta.gz", + "tb-hunt-probe-set-jan-03-2019.fasta.gz" + ], + "files": [ + "ERR3335753_1.fastq", + "ERR3335753_2.fastq" + ], + "version": { + "mykrobe-predictor": "v0.10.0", + "mykrobe-atlas": "v0.10.0" + }, + "genotype_model": "kmer_count" + } +}
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/single_2020/output-jsondata.csv Fri Sep 22 17:24:02 2023 +0000 @@ -0,0 +1,2 @@ +"file","phylo_group","species","phylo_group_per_covg","species_per_covg","phylo_group_depth","species_depth" +"ERR2704812_L5","Mycobacterium_tuberculosis_complex","Mycobacterium_africanum",98.467,64.333,332,326
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/single_2020/output-report.csv Fri Sep 22 17:24:02 2023 +0000 @@ -0,0 +1,2 @@ +"file","Mykrobe_fabG1","Mykrobe_katG","Mykrobe_ahpC","Mykrobe_inhA","Mykrobe_ndh","Isoniazid_R_mutations","Isoniazid_Prediction","Mykrobe_rpoB","Rifampicin_R_mutations","Rifampicin_Prediction","Mykrobe_embB","Mykrobe_embA","Ethambutol_R_mutations","Ethambutol_Prediction","Mykrobe_pncA","Mykrobe_rpsA","Pyrazinamide_R_mutations","Pyrazinamide_Prediction","Mykrobe_Ofloxacin_gyrA","Ofloxacin_R_mutations","Ofloxacin_Prediction","Mykrobe_Moxifloxacin_gyrA","Moxifloxacin_R_mutations","Moxifloxacin_Prediction","Mykrobe_rpsL","Mykrobe_Streptomycin_rrs","Mykrobe_Streptomycin_gid","Streptomycin_R_mutations","Streptomycin_Prediction","Mykrobe_Amikacin_rrs","Amikacin_R_mutations","Amikacin_Prediction","Mykrobe_Capreomycin_rrs","Mykrobe_Capreomycin_tlyA","Capreomycin_R_mutations","Capreomycin_Prediction","Mykrobe_Kanamycin_rrs","Mykrobe_Kanamycin_eis","Kanamycin_R_mutations","Kanamycin_Prediction","Lims_Comment","Lims_INTComment","Mykrobe_Workflow_Version","mykrobe_version","Mykrobe_Resistance_probe_set","Mykrobe_min_depth_default_5","Mykrobe_min_conf_default_10","LIMS_file","Mutation_set_version" +"ERR2704812_L5","No Mutation","No Mutation","G-48A","No Mutation","No Mutation","ahpC_G-48A-G2726145A:360:0:42983","R","D435V","rpoB_D435V-GAC761109GTC:344:0:40497","R","No Mutation","No Mutation",NA,"S","No Mutation","No Mutation",NA,"S","No Mutation",NA,"S","No Mutation",NA,"S","No Mutation","No Mutation","No Mutation",NA,"S","No Mutation",NA,"S","No Mutation","No Mutation",NA,"S","No Mutation","No Mutation",NA,"S","","","","v0.10.0","tb-hunt-probe-set-jan-03-2019.fasta.gz","5","10","",""
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/single_2020/single2020.json Fri Sep 22 17:24:02 2023 +0000 @@ -0,0 +1,209 @@ +{ + "ERR2704812_L5": { + "susceptibility": { + "Ofloxacin": { + "predict": "S" + }, + "Moxifloxacin": { + "predict": "S" + }, + "Isoniazid": { + "predict": "R", + "called_by": { + "ahpC_G-48A-G2726145A": { + "variant": null, + "genotype": [ + 1, + 1 + ], + "genotype_likelihoods": [ + -43297.59603037145, + -99999999, + -315.05757839655627 + ], + "info": { + "coverage": { + "reference": { + "percent_coverage": 0.0, + "median_depth": 0, + "min_non_zero_depth": 0, + "kmer_count": 0, + "klen": 21 + }, + "alternate": { + "percent_coverage": 100.0, + "median_depth": 360, + "min_non_zero_depth": 352, + "kmer_count": 7229, + "klen": 21 + } + }, + "expected_depths": [ + 332.0 + ], + "contamination_depths": [], + "filter": [], + "conf": 42983 + }, + "_cls": "Call.VariantCall" + } + } + }, + "Kanamycin": { + "predict": "S" + }, + "Ethambutol": { + "predict": "S" + }, + "Streptomycin": { + "predict": "S" + }, + "Ciprofloxacin": { + "predict": "S" + }, + "Pyrazinamide": { + "predict": "S" + }, + "Rifampicin": { + "predict": "R", + "called_by": { + "rpoB_D435V-GAC761109GTC": { + "variant": null, + "genotype": [ + 1, + 1 + ], + "genotype_likelihoods": [ + -40815.43149991495, + -99999999, + -318.2103823437153 + ], + "info": { + "coverage": { + "reference": { + "percent_coverage": 0.0, + "median_depth": 0, + "min_non_zero_depth": 0, + "kmer_count": 0, + "klen": 21 + }, + "alternate": { + "percent_coverage": 100.0, + "median_depth": 344, + "min_non_zero_depth": 328, + "kmer_count": 6544, + "klen": 20 + } + }, + "expected_depths": [ + 332.0 + ], + "contamination_depths": [], + "filter": [], + "conf": 40497 + }, + "_cls": "Call.VariantCall" + } + } + }, + "Amikacin": { + "predict": "S" + }, + "Capreomycin": { + "predict": "S" + } + }, + "phylogenetics": { + "phylo_group": { + "Mycobacterium_tuberculosis_complex": { + "percent_coverage": 98.467, + "median_depth": 332.0 + } + }, + "sub_complex": { + "Unknown": { + "percent_coverage": -1, + "median_depth": -1 + } + }, + "species": { + "Mycobacterium_africanum": { + "percent_coverage": 64.333, + "median_depth": 326 + } + }, + "lineage": { + "lineage": [ + "lineage5" + ], + "calls_summary": { + "lineage5": { + "good_nodes": 1, + "tree_depth": 1, + "genotypes": { + "lineage5": 1 + } + } + }, + "calls": { + "lineage5": { + "lineage5": { + "C1799921A": { + "variant": "ref-C1799921A?var_name=C1799921A&num_alts=1&ref=NC_000962.3&enum=0&gene=NA&mut=C1799921A", + "genotype": [ + 1, + 1 + ], + "genotype_likelihoods": [ + -40869.16316992115, + -99999999, + -318.61512332363264 + ], + "info": { + "coverage": { + "reference": { + "percent_coverage": 0.0, + "median_depth": 0, + "min_non_zero_depth": 0, + "kmer_count": 0, + "klen": 21 + }, + "alternate": { + "percent_coverage": 100.0, + "median_depth": 331, + "min_non_zero_depth": 327, + "kmer_count": 6635, + "klen": 21 + } + }, + "expected_depths": [ + 332.0 + ], + "contamination_depths": [], + "filter": [], + "conf": 40551 + }, + "_cls": "Call.VariantCall" + } + } + } + } + } + }, + "kmer": 21, + "probe_sets": [ + "tb-species-170421.fasta.gz", + "tb-hunt-probe-set-jan-03-2019.fasta.gz", + "tb.lineage.20200930.probes.fa.gz" + ], + "files": [ + "ERR2704812_1.fastq", + "ERR2704812_2.fastq" + ], + "version": { + "mykrobe-predictor": "v0.10.0", + "mykrobe-atlas": "v0.10.0" + }, + "genotype_model": "kmer_count" + } +}
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