R/5_BIGG.R
In tidymass/massdatabase: Play with databases about mass spectrometry
Defines functions
request_bigg_version
Documented in
request_bigg_version
#' Request BiGG Database Version
#'
#' This function retrieves the current version of the BiGG database from the BiGG API.
#'
#' @param url A string specifying the URL of the BiGG database version endpoint.
#' Defaults to `"http://bigg.ucsd.edu/api/v2/database_version"`.
#'
#' @details
#' The function makes an HTTP request to the BiGG database version endpoint using `curl`.
#' It parses the response to extract the version information, returning it as a data frame
#' with two columns: `name` and `value`. If the request fails, the function returns `NULL`.
#'
#' @return A data frame containing the version information of the BiGG database with two columns:
#' - `name`: The type of version information (e.g., "bigg_models_version").
#' - `value`: The corresponding value of the version information.
#'
#' @examples
#' \dontrun{
#' # Retrieve the current version of the BiGG database
#' version_info <- request_bigg_version()
#'
#' # Use a custom API URL
#' version_info <- request_bigg_version(url = "http://bigg.ucsd.edu/api/v2/custom_endpoint")
#' }
#'
#' @importFrom curl curl
#' @importFrom stringr str_replace_all str_split str_trim
#' @export
request_bigg_version <-
function(url = "http://bigg.ucsd.edu/api/v2/database_version") {
options(warn = -1)
x <-
tryCatch(
curl::curl(url = url),
error = function(e)
NULL
)
open(x)
out <- readLines(x, warn = FALSE)
close(x)
# cat(out, sep = "\n")
out <-
out %>%
stringr::str_replace_all("\"", "") %>%
stringr::str_replace_all("\\{|\\}", "") %>%
stringr::str_split(pattern = "\\,") %>%
`[[`(1) %>%
stringr::str_trim() %>%
stringr::str_split("\\: ") %>%
do.call(rbind, .) %>%
as.data.frame()
colnames(out) <- c("name", "value")
return(out)
}
#' @title Download BIGG model data
#' @description Download BIGG model data
#' @author Xiaotao Shen
#' \email{shenxt1990@@outlook.com}
#' @param model_id model_id, for example, iND750
#' @param path Default is .
#' @return version.
#' @export
download_bigg_model <-
function(model_id = "iND750", path = ".") {
dir.create(path, showWarnings = FALSE, recursive = TRUE)
url <-
paste0('http://bigg.ucsd.edu/static/models/', model_id, '.json')
system(command = paste('curl -O', url))
if (!paste0(model_id, '.json') %in% dir(path)) {
file.copy(
from = file.path(".", paste0(model_id, '.json')),
to = file.path(path, paste0(model_id, '.json')),
overwrite = TRUE,
recursive = TRUE
)
unlink(x = file.path(".", paste0(model_id, '.json')),
recursive = TRUE,
force = TRUE)
}
}
#' @title Request BIGG model information
#' @description Request BIGG model information
#' @author Xiaotao Shen
#' \email{shenxt1990@@outlook.com}
#' @param url url http://bigg.ucsd.edu/api/v2/models
#' @return model information
#' @importFrom curl curl
#' @importFrom stringr str_replace_all str_extract str_replace str_split
#' @importFrom stringr str_trim
#' @export
#' @examples
#' x <- request_bigg_model_info()
#' head(x)
request_bigg_model_info <-
function(url = "http://bigg.ucsd.edu/api/v2/models") {
x <-
curl::curl(url = url)
open(x)
out <- readLines(x, warn = FALSE)
close(x)
# cat(out, sep = "\n")
out <-
out %>%
stringr::str_replace_all("\"", "") %>%
stringr::str_replace_all("\\{results\\: ", "")
model_count <-
stringr::str_extract(out, "results_count\\: [0-9]{2,3}") %>%
stringr::str_replace("results_count\\: ", "") %>%
as.numeric()
out <-
out %>%
stringr::str_replace_all("\\, results_count\\: [0-9]{2,3}\\}", "") %>%
stringr::str_replace(pattern = "^\\[", "") %>%
stringr::str_replace(pattern = "\\]$", "")
out <-
out %>%
stringr::str_split(pattern = "\\}, \\{") %>%
`[[`(1) %>%
stringr::str_replace_all("^\\{", "") %>%
stringr::str_replace_all("\\}$", "") %>%
lapply(function(x) {
x <-
stringr::str_split(x, "\\,")[[1]] %>%
stringr::str_trim() %>%
lapply(function(y) {
stringr::str_split(y, "\\: ")[[1]]
}) %>%
do.call(rbind, .) %>%
as.data.frame()
x1 <- matrix(data = x[, 2], nrow = 1) %>%
as.data.frame()
colnames(x1) <- x$V1
x1
}) %>%
do.call(rbind, .) %>%
as.data.frame()
out$gene_count <- as.numeric(out$gene_count)
out$reaction_count <- as.numeric(out$reaction_count)
out$metabolite_count <- as.numeric(out$metabolite_count)
invisible(out)
}
#' @title Request BIGG universal metabolite information
#' @description Request BIGG universal metabolite information
#' @author Xiaotao Shen
#' \email{shenxt1990@@outlook.com}
#' @param url url http://bigg.ucsd.edu/api/v2/universal/metabolites
#' @return universal metabolite information
#' @importFrom curl curl
#' @importFrom stringr str_replace_all str_extract str_replace str_split
#' @importFrom stringr str_trim
#' @export
#' @examples
#' x <- request_bigg_universal_metabolite_info()
#' dim(x)
#' head(x)
request_bigg_universal_metabolite_info <-
function(url = "http://bigg.ucsd.edu/api/v2/universal/metabolites") {
x <-
curl::curl(url = url)
open(x)
out <- readLines(x, warn = FALSE)
close(x)
out <-
out %>%
stringr::str_replace_all("\"", "") %>%
stringr::str_replace_all("\\{results\\: ", "")
metabolite_count <-
stringr::str_extract(out, "results_count\\: [0-9]{2,5}") %>%
stringr::str_replace("results_count\\: ", "") %>%
as.numeric()
out <-
out %>%
stringr::str_replace_all("\\, results_count\\: [0-9]{2,5}\\}", "") %>%
stringr::str_replace(pattern = "^\\[", "") %>%
stringr::str_replace(pattern = "\\]$", "")
out <-
out %>%
stringr::str_split(pattern = "\\}, \\{") %>%
`[[`(1) %>%
stringr::str_replace_all("^\\{", "") %>%
stringr::str_replace_all("\\}$", "") %>%
lapply(function(x) {
x <-
x %>%
stringr::str_split(", name\\: ") %>%
`[[`(1) %>%
stringr::str_split(", model_bigg_id\\: ") %>%
unlist() %>%
stringr::str_replace_all("bigg_id: ", "")
}) %>%
do.call(rbind, .) %>%
as.data.frame()
colnames(out) <- c("bigg_id", "name", "model_bigg_id")
invisible(out)
}
#' @title Request BIGG metabolite
#' @description Request BIGG metabolite
#' @author Xiaotao Shen
#' \email{shenxt1990@@outlook.com}
#' @param url url http://bigg.ucsd.edu/api/v2/universal/metabolites
#' @param metabolite_id metabolite_id, for example, g3p
#' @param return_form data.frame or list.
#' @return universal metabolite information
#' @importFrom curl curl
#' @importFrom stringr str_replace_all str_extract str_replace str_split
#' @importFrom stringr str_trim
#' @export
#' @examples
#' x <- request_bigg_universal_metabolite(metabolite_id = "g3p", return_form = "list")
#' x
#' y <- request_bigg_universal_metabolite(metabolite_id = "g3p", return_form = "data.frame")
#' y
request_bigg_universal_metabolite <-
function(url = "http://bigg.ucsd.edu/api/v2/universal/metabolites",
metabolite_id = "g3p",
return_form = c("list", "data.frame")) {
return_form <- match.arg(return_form)
url <- paste0(url, "/", metabolite_id)
x <-
curl::curl(url = url)
open(x)
out <- readLines(x, warn = FALSE)
close(x)
out <-
out %>%
stringr::str_replace_all("\"", "") %>%
stringr::str_replace_all("\\{results\\: ", "")
out <-
out %>%
stringr::str_replace(pattern = "^\\{", "") %>%
stringr::str_replace(pattern = "\\}$", "")
database_link <-
stringr::str_extract(string = out, pattern = "database_links: .+\\}, bigg_id:") %>%
stringr::str_replace("database_links: \\{", "") %>%
stringr::str_replace("\\}, bigg_id:", "")
database_link <-
database_link %>%
stringr::str_split("\\],") %>%
`[[`(1) %>%
stringr::str_trim() %>%
stringr::str_replace("\\]", "") %>%
lapply(function(x) {
id <-
x %>%
stringr::str_extract_all("id: .{1,50}\\}") %>%
`[[`(1) %>%
stringr::str_replace("id: ", "") %>%
stringr::str_replace("\\}", "") %>%
paste(collapse = "{}") %>%
stringr::str_replace_all("CHEBI:", "")
database <-
x %>%
stringr::str_split("\\: \\[") %>%
`[[`(1) %>%
`[`(1)
data.frame(database = database, id = id)
}) %>%
do.call(rbind, .) %>%
as.data.frame()
bigg_id <-
stringr::str_extract(string = out, pattern = "\\}, bigg_id: [a-zA-Z0-9_-]{1,100}, formulae:") %>%
stringr::str_replace(", formulae:", "") %>%
stringr::str_replace("\\}, bigg_id: ", "")
formula <-
stringr::str_extract(string = out, pattern = "formulae: .{1,100}, old_identifiers") %>%
stringr::str_replace("formulae: ", "") %>%
stringr::str_replace(", old_identifiers", "") %>%
stringr::str_replace("\\[", "") %>%
stringr::str_replace("\\]", "") %>%
stringr::str_replace_all(", ", "{}")
old_identifiers <-
stringr::str_extract(string = out, pattern = "old_identifiers: .{1,100}, charges:") %>%
stringr::str_replace("old_identifiers: ", "") %>%
stringr::str_replace(", charges:", "") %>%
stringr::str_replace("\\[", "") %>%
stringr::str_replace("\\]", "") %>%
stringr::str_replace_all(", ", "{}")
charges <-
stringr::str_extract(string = out, pattern = "charges: .{1,100}, name:") %>%
stringr::str_replace("charges: ", "") %>%
stringr::str_replace(", name:", "") %>%
stringr::str_replace("\\[", "") %>%
stringr::str_replace("\\]", "") %>%
stringr::str_replace_all(", ", "{}")
name <-
stringr::str_extract(string = out, pattern = "name: .{1,300}, compartments_in_models:") %>%
stringr::str_replace("name: ", "") %>%
stringr::str_replace(", compartments_in_models:", "")
compartments_in_models <-
stringr::str_extract(string = out, pattern = "compartments_in_models: .+\\}\\]") %>%
stringr::str_replace("compartments_in_models: ", "") %>%
stringr::str_replace("\\[", "") %>%
stringr::str_replace("\\]", "")
compartments_in_models <-
compartments_in_models %>%
stringr::str_split("\\}, \\{") %>%
`[[`(1) %>%
stringr::str_replace("^\\{", "") %>%
stringr::str_replace("\\}\\]$", "") %>%
stringr::str_replace("bigg_id: ", "") %>%
stringr::str_split(", organism: |, model_bigg_id: ") %>%
do.call(rbind, .) %>%
as.data.frame()
colnames(compartments_in_models) <-
c("bigg_id", "organism", "model_bigg_id")
if (return_form == "list") {
return_result <-
list(
bigg_id = bigg_id,
name = name,
formula = formula,
old_identifiers = old_identifiers,
charges = charges,
database_link = database_link,
compartments_in_models = compartments_in_models
)
} else{
organism <-
compartments_in_models$organism %>%
paste(collapse = "{}")
model_bigg_id <-
compartments_in_models$model_bigg_id %>%
paste(collapse = "{}")
return_result <-
data.frame(
bigg_id = bigg_id,
name = name,
formula = formula,
old_identifiers = old_identifiers,
charges = charges,
organism = organism,
model_bigg_id = model_bigg_id
)
database_link <-
database_link %>%
dplyr::mutate(
database = case_when(
database == "InChI Key" ~ "InChI_Key",
database == "Reactome Compound" ~ "Reactome",
database == "SEED Compound" ~ "SEED",
database == "Human Metabolome Database" ~ "HMDB",
database == "MetaNetX (MNX) Chemical" ~ "MetaNetX",
database == "KEGG Compound" ~ "KEGG",
database == "KEGG Drug" ~ "KEGG_Drug",
database == "KEGG Glycan" ~ "KEGG_Glycan",
TRUE ~ database
)
)
missing_id <-
setdiff(
c(
"InChI_Key",
"Reactome",
"SEED",
"CHEBI",
"HMDB",
"MetaNetX",
"KEGG",
"KEGG_Drug",
"KEGG_Glycan",
"LipidMaps",
"BioCyc"
),
database_link$database
)
if (length(missing_id) > 0) {
new_database_link <-
data.frame(database = missing_id, id = NA)
database_link <-
rbind(database_link, new_database_link) %>%
dplyr::filter(database != "")
}
database_link <-
database_link %>%
dplyr::arrange(database)
id <-
as.data.frame(matrix(database_link$id, nrow = 1))
colnames(id) <- database_link$database
return_result <-
cbind(return_result, id)
}
invisible(return_result)
}
#' Download BiGG Universal Metabolite Data
#'
#' This function downloads the BiGG universal metabolite database, saving it to a specified directory.
#' It provides the option to store intermediate files and control the download rate by introducing a delay.
#'
#' @param path A string specifying the directory to save the downloaded data. Defaults to the current directory (`"."`).
#' @param sleep A numeric value indicating the number of seconds to pause between downloads. Defaults to 1 second.
#' @param delete_intermediate A logical value indicating whether to delete intermediate files after the download completes. Defaults to `TRUE`.
#'
#' @details
#' The function first retrieves a list of all available metabolites from the BiGG database using
#' `request_bigg_universal_metabolite_info()`. It saves this information in an intermediate directory.
#' For each metabolite, the function checks if the data already exists locally; if not, it downloads the data using
#' `request_bigg_universal_metabolite()`.
#'
#' A progress bar is shown during the download process. The final data is saved as `bigg_universal_metabolit_database`
#' in the specified path. If `delete_intermediate = TRUE`, intermediate files are deleted after the download completes.
#'
#' @return None. The function saves the downloaded data to the specified directory.
#'
#' @examples
#' \dontrun{
#' # Download BiGG universal metabolite data to the current directory
#' download_bigg_universal_metabolite()
#'
#' # Download data to a custom path with 2 seconds of sleep between downloads
#' download_bigg_universal_metabolite(path = "data", sleep = 2)
#'
#' # Keep intermediate files
#' download_bigg_universal_metabolite(delete_intermediate = FALSE)
#' }
#'
#' @importFrom progress progress_bar
#' @export
download_bigg_universal_metabolite <-
function(path = ".",
sleep = 1,
delete_intermediate = TRUE) {
dir.create(path, recursive = TRUE, showWarnings = FALSE)
dir.create(file.path(path, "intermediate"),
recursive = TRUE,
showWarnings = FALSE)
metabolite_info <-
request_bigg_universal_metabolite_info()
message(nrow(metabolite_info), " metabolites in total")
save(metabolite_info,
file = file.path(path, "intermediate/metabolite_info"))
pb <- progress::progress_bar$new(total = nrow(metabolite_info))
###download metabolite
bigg_universal_metabolit_database <-
vector(mode = "list", length = nrow(metabolite_info))
names(bigg_universal_metabolit_database) <- metabolite_info$bigg_id
for (i in seq_len(nrow(metabolite_info))) {
pb$tick()
id <- metabolite_info$bigg_id[i]
if (file.exists(file.path(path, "intermediate", paste0(id)))) {
load(file = file.path(path, "intermediate", paste0(id)))
bigg_universal_metabolit_database[[i]] <- metabolite
} else{
Sys.sleep(time = sleep)
metabolite <-
request_bigg_universal_metabolite(metabolite_id = metabolite_info$bigg_id[i],
return_form = "data.frame")
save(metabolite, file = file.path(path, "intermediate", id))
bigg_universal_metabolit_database[[i]] <- metabolite
}
}
save(
bigg_universal_metabolit_database,
file = file.path(path, "bigg_universal_metabolit_database")
)
if (delete_intermediate) {
unlink(file.path(path, "intermediate"), recursive = TRUE)
}
}
#' Read BiGG Universal Metabolite Data
#'
#' This function reads the saved BiGG universal metabolite database from the specified directory
#' and returns it as a combined data frame.
#'
#' @param path A string specifying the directory where the BiGG database is located. Defaults to the current directory (`"."`).
#'
#' @details
#' The function loads the previously saved `bigg_universal_metabolit_database` file from the provided directory.
#' It uses a progress bar to indicate the loading progress and combines individual metabolite data into a
#' single data frame using `dplyr::bind_rows()`. The final data frame is returned to the user.
#'
#' @return A data frame containing all the metabolites from the BiGG universal database.
#'
#' @examples
#' \dontrun{
#' # Read the BiGG database from the current directory
#' metabolites <- read_bigg_universal_metabolite()
#'
#' # Read the BiGG database from a custom directory
#' metabolites <- read_bigg_universal_metabolite(path = "data")
#' }
#'
#' @importFrom progress progress_bar
#' @importFrom dplyr bind_rows
#' @export
read_bigg_universal_metabolite <-
function(path = ".") {
load(file.path(path, "bigg_universal_metabolit_database"))
pb <-
progress::progress_bar$new(total =
length(bigg_universal_metabolit_database))
bigg_universal_metabolit_database <-
bigg_universal_metabolit_database %>%
dplyr::bind_rows() %>%
as.data.frame()
return(bigg_universal_metabolit_database)
}
#' Convert BiGG Universal Metabolite Data to MetID Format
#'
#' This function converts the BiGG universal metabolite database into a format compatible with the `metid` package.
#' It processes the metabolite formulas, calculates mass-to-charge ratios (m/z), and maps various IDs for downstream use.
#'
#' @param data A data frame containing BiGG metabolite information, including formulas and IDs.
#' @param path A string specifying the directory where the output data will be saved. Defaults to the current directory (`"."`).
#' @param threads An integer specifying the number of threads to use for parallel processing. Defaults to 5.
#'
#' @details
#' The function processes the provided metabolite data by:
#' - Handling missing formulas and modifying them based on charge.
#' - Calculating the mass-to-charge ratio (m/z) for each metabolite using `Rdisop`.
#' - Renaming and reformatting columns for compatibility with the `metid` package.
#' - Writing the processed data to a temporary CSV file and creating a `metid`-compatible database.
#'
#' The final processed database is saved as `bigg_ms1` in the specified path, and intermediate files are cleaned up.
#'
#' @return An invisible object containing the converted database.
#'
#' @examples
#' \dontrun{
#' # Convert BiGG metabolite data to MetID format and save to the current directory
#' convert_bigg_universal2metid(data = bigg_data)
#'
#' # Save the converted data to a custom directory using multiple threads
#' convert_bigg_universal2metid(data = bigg_data, path = "metid_data", threads = 10)
#' }
#'
#' @importFrom dplyr filter rename mutate select bind_rows
#' @importFrom purrr map
#' @importFrom stringr str_split str_replace str_replace_all
#' @importFrom Rdisop getMass getMolecule
#' @importFrom progress progress_bar
#' @importFrom readr write_csv
#' @export
convert_bigg_universal2metid <-
function(data,
path = ".",
threads = 5) {
dir.create(path, showWarnings = FALSE, recursive = TRUE)
####Formula and mz
data[which(data == "", arr.ind = TRUE)] <- NA
data <-
data %>%
dplyr::filter(!is.na(formula))
####add formula to H or remove H based on charge
message("Extract formula...")
pb <-
progress::progress_bar$new(total = nrow(data))
formula <-
seq_len(nrow(data)) %>%
purrr::map(function(idx) {
# cat(idx, " ")
pb$tick()
charge = data$charges[idx]
formula <- data$formula[idx]
if (is.na(charge)) {
return(data$formula[idx])
}
if (charge == "0") {
return(data$formula[idx])
}
if (length(grep("\\{\\}", charge)) == 0) {
charge <- as.numeric(charge)
adduct = paste0(ifelse(charge > 0, "M-", "M+"), abs(charge), "H")
formula <-
masstools::sum_formula(formula = formula, adduct = adduct)
return(formula)
}
if (length(grep("\\{\\}", charge)) > 0) {
charge <- as.numeric(stringr::str_split(charge, "\\{\\}")[[1]])
formula <- stringr::str_split(formula, "\\{\\}")[[1]]
if (length(charge) != length(formula)) {
return(NA)
}
if (any(charge) == 0) {
return(formula[which(charge == 0)])
}
adduct = paste0(ifelse(charge[1] > 0, "M-", "M+"), abs(charge[1]), "H")
formula <-
masstools::sum_formula(formula = formula[1], adduct = adduct)
return(formula)
}
}) %>%
unlist()
data$formula <- formula
data$HMDB <-
data$HMDB %>%
purrr::map(function(x) {
if (is.na(x)) {
return(x)
}
x <- stringr::str_split(x, "\\{\\}")[[1]]
x <- stringr::str_replace(x, "HMDB", "HMDB00")
x <- paste(x, collapse = "{}")
x
}) %>%
unlist()
data <-
data %>%
dplyr::filter(!is.na(formula))
###add mz
message("Calculating mz...")
pb <-
progress::progress_bar$new(total = nrow(data))
mz <-
seq_len(nrow(data)) %>%
purrr::map(function(i) {
pb$tick()
temp <-
tryCatch(
Rdisop::getMass(Rdisop::getMolecule(data$formula[i])),
error = function(e)
NA
)
}) %>%
unlist()
data$mz <- mz
data <-
data %>%
dplyr::filter(!is.na(mz))
data <-
data %>%
dplyr::rename(
BIGG.ID = bigg_id,
Compound.name = name,
Formula = formula,
BIOCYC.ID = BioCyc,
CHEBI.ID = CHEBI,
HMDB.ID = HMDB,
INCHIKEY.ID = InChI_Key,
KEGG.ID = KEGG,
METANETX.ID = MetaNetX,
REACTOME.ID = Reactome,
SEED.ID = SEED,
KEGG_DRUG.ID = KEGG_Drug,
KEGG_GLYCAN.ID = KEGG_Glycan,
LIPIDMAPS.ID = LipidMaps
) %>%
dplyr::mutate(
Lab.ID = BIGG.ID,
CAS.ID = NA,
RT = NA,
mz.pos = NA,
mz.neg = NA,
Submitter = "BIGG"
) %>%
dplyr::select(
Lab.ID,
Compound.name,
mz,
RT,
CAS.ID,
HMDB.ID,
KEGG.ID,
Formula,
mz.pos,
mz.neg,
Submitter,
everything()
)
data$Synonyms <-
data$Compound.name %>%
stringr::str_replace_all("; ", "\\{\\}")
data$Compound.name <-
data$Synonyms %>%
stringr::str_split("\\{\\}") %>%
lapply(function(x) {
x[1]
}) %>%
unlist()
temp_file <- tempfile()
dir.create(temp_file, showWarnings = FALSE)
readr::write_csv(x = data, file = file.path(temp_file, "data.csv"))
bigg_ms1 =
metid::construct_database(
path = temp_file,
version = as.character(Sys.Date()),
metabolite.info.name = "data.csv",
source = "BIGG",
link = "http://bigg.ucsd.edu/",
creater = "Xiaotao Shen",
email = "shenxt@stanford.edu",
rt = FALSE,
threads = threads
)
unlink(file.path(temp_file, "data.csv"))
unlink(temp_file)
save(bigg_ms1, file = file.path(path, "bigg_ms1"))
invisible(bigg_ms1)
}
#' @title Request BIGG universal reaction information
#' @description Request BIGG universal reaction information
#' @author Xiaotao Shen
#' \email{shenxt1990@@outlook.com}
#' @param url url http://bigg.ucsd.edu/api/v2/universal/reactions
#' @return universal metabolite information
#' @importFrom curl curl
#' @importFrom stringr str_replace_all str_extract str_replace str_split
#' @importFrom stringr str_trim
#' @export
#' @examples
#' x <- request_bigg_universal_reaction_info()
#' dim(x)
#' head(x)
request_bigg_universal_reaction_info <-
function(url = "http://bigg.ucsd.edu/api/v2/universal/reactions") {
x <-
curl::curl(url = url)
open(x)
out <- readLines(x, warn = FALSE)
close(x)
out <-
out %>%
stringr::str_replace_all("\"", "") %>%
stringr::str_replace_all("\\{results\\: ", "")
reaction_count <-
stringr::str_extract(out, "results_count\\: [0-9]{2,5}") %>%
stringr::str_replace("results_count\\: ", "") %>%
as.numeric()
out <-
out %>%
stringr::str_replace_all("\\, results_count\\: [0-9]{2,5}\\}", "") %>%
stringr::str_replace(pattern = "^\\[", "") %>%
stringr::str_replace(pattern = "\\]$", "")
out <-
out %>%
stringr::str_split(pattern = "\\}, \\{") %>%
`[[`(1) %>%
stringr::str_replace_all("^\\{", "") %>%
stringr::str_replace_all("\\}$", "") %>%
lapply(function(x) {
x <-
x %>%
stringr::str_split(", name\\: ") %>%
`[[`(1) %>%
stringr::str_split(", model_bigg_id\\: ") %>%
unlist() %>%
stringr::str_replace_all("bigg_id: ", "")
}) %>%
do.call(rbind, .) %>%
as.data.frame()
colnames(out) <- c("bigg_id", "name", "model_bigg_id")
invisible(out)
}
#' @title Request BIGG reaction information for specific species (model)
#' @description Request BIGG reaction information for specific species
#' @author Xiaotao Shen
#' \email{shenxt1990@@outlook.com}
#' @param model_bigg_id please use the model bigg id using the
#' request_bigg_model_info function. Default is iAB_RBC_283 (human)
#' @return reaction information
#' @importFrom curl curl
#' @importFrom stringr str_replace_all str_extract str_replace str_split
#' @importFrom stringr str_trim
#' @export
#' @examples
#' x <- request_bigg_universal_reaction_info()
#' dim(x)
#' head(x)
request_bigg_reaction_info <-
function(model_bigg_id = "iAB_RBC_283") {
url <-
paste0("http://bigg.ucsd.edu/api/v2/models/",
model_bigg_id,
"/reactions")
x <-
curl::curl(url = url)
open(x)
out <- readLines(x, warn = FALSE)
close(x)
out <-
out %>%
stringr::str_replace_all("\"", "") %>%
stringr::str_replace_all("\\{results\\: ", "")
reaction_count <-
stringr::str_extract(out, "results_count\\: [0-9]{2,5}") %>%
stringr::str_replace("results_count\\: ", "") %>%
as.numeric()
out <-
out %>%
stringr::str_replace_all("\\, results_count\\: [0-9]{2,5}\\}", "") %>%
stringr::str_replace(pattern = "^\\[", "") %>%
stringr::str_replace(pattern = "\\]$", "")
out <-
out %>%
stringr::str_split(pattern = "\\}, \\{") %>%
`[[`(1) %>%
stringr::str_replace_all("^\\{", "") %>%
stringr::str_replace_all("\\}$", "") %>%
lapply(function(x) {
x <-
x %>%
stringr::str_split(", name\\: ") %>%
`[[`(1) %>%
stringr::str_split(", model_bigg_id\\: ") %>%
unlist() %>%
stringr::str_replace_all("bigg_id: ", "")
}) %>%
do.call(rbind, .) %>%
as.data.frame()
colnames(out) <- c("bigg_id", "name", "model_bigg_id")
invisible(out)
}
#' @title Request BIGG reaction
#' @description Request BIGG reaction
#' @author Xiaotao Shen
#' \email{shenxt1990@@outlook.com}
#' @param url url http://bigg.ucsd.edu/api/v2/universal/reactions
#' @param reaction_id reaction_id, for example, ADA
#' @param return_form data.frame or list.
#' @return universal metabolite information
#' @importFrom curl curl
#' @importFrom stringr str_replace_all str_extract str_replace str_split
#' @importFrom stringr str_trim
#' @export
#' @examples
#' x <- request_bigg_universal_reaction(reaction_id = "ADA", return_form = "list")
#' x
#' y <- request_bigg_universal_reaction(reaction_id = "ADA", return_form = "data.frame")
#' y
request_bigg_universal_reaction <-
function(url = "http://bigg.ucsd.edu/api/v2/universal/reactions",
reaction_id = "ADA",
return_form = c("list", "data.frame")) {
return_form <- match.arg(return_form)
url <- paste0(url, "/", reaction_id)
x <-
curl::curl(url = url)
open(x)
out <- readLines(x, warn = FALSE)
close(x)
out <-
out %>%
stringr::str_replace_all("\"", "") %>%
stringr::str_replace_all("\\{results\\: ", "")
out <-
out %>%
stringr::str_replace(pattern = "^\\{", "") %>%
stringr::str_replace(pattern = "\\}$", "")
models_containing_reaction <-
stringr::str_extract(string = out, pattern = "models_containing_reaction: \\[.+\\}\\], reaction_string: ") %>%
stringr::str_replace("models_containing_reaction: \\[", "") %>%
stringr::str_replace("\\], reaction_string: ", "")
models_containing_reaction <-
models_containing_reaction %>%
stringr::str_split("\\}, \\{") %>%
`[[`(1) %>%
stringr::str_trim() %>%
stringr::str_replace("\\{|\\}", "") %>%
stringr::str_split(", organism: ") %>%
lapply(function(x) {
x <-
stringr::str_replace(x, "bigg_id: ", "")
x
}) %>%
do.call(rbind, .) %>%
as.data.frame()
colnames(models_containing_reaction) <-
c("bigg_id", "organism")
bigg_id <-
stringr::str_extract(string = out, pattern = "\\]\\}\\, bigg_id\\: .{1,20}, old_identifiers\\: ") %>%
stringr::str_replace("\\]\\}, bigg_id\\: ", "") %>%
stringr::str_replace("\\, old_identifiers\\: ", "")
old_identifiers <-
stringr::str_extract(string = out, pattern = "old_identifiers: .{1,50}, name: ") %>%
stringr::str_replace("old_identifiers: ", "") %>%
stringr::str_replace(", name: ", "") %>%
stringr::str_replace("\\[", "") %>%
stringr::str_replace("\\]", "") %>%
stringr::str_replace_all(", ", "{}")
pseudoreaction <-
stringr::str_extract(string = out, pattern = "pseudoreaction: .{1,20}") %>%
stringr::str_replace("pseudoreaction: ", "")
name <-
stringr::str_extract(string = out, pattern = "name: .{1,100}, pseudoreaction:") %>%
stringr::str_replace("name: ", "") %>%
stringr::str_replace(", pseudoreaction:", "")
reaction_string <-
stringr::str_extract(string = out, pattern = "reaction_string: .{1,100}, metabolites: ") %>%
stringr::str_replace("reaction_string: ", "") %>%
stringr::str_replace(", metabolites: ", "")
metabolites <-
stringr::str_extract(string = out, pattern = "metabolites: \\[.+, database_links: ") %>%
stringr::str_replace("metabolites: \\[\\{", "") %>%
stringr::str_replace("\\}\\], database_links: ", "")
metabolites <-
metabolites %>%
stringr::str_split("\\}, \\{") %>%
`[[`(1) %>%
stringr::str_trim() %>%
stringr::str_split(", name: |, compartment_bigg_id: |, stoichiometry: ") %>%
lapply(function(x) {
x <-
stringr::str_replace_all(x, "bigg_id: ", "")
x
}) %>%
do.call(rbind, .) %>%
as.data.frame()
colnames(metabolites) <-
c("bigg_id", "name", "compartment_bigg_id", "stoichiometry")
database_link <-
stringr::str_extract(string = out, pattern = "database_links:.+\\}, bigg_id: ") %>%
stringr::str_replace("database_links: \\{", "") %>%
stringr::str_replace("\\]\\}, bigg_id:", "") %>%
stringr::str_trim()
database_link <-
database_link %>%
stringr::str_split("\\],") %>%
`[[`(1) %>%
stringr::str_trim() %>%
stringr::str_replace("\\]", "") %>%
lapply(function(x) {
id <-
x %>%
stringr::str_extract_all("id: .{1,50}\\}") %>%
`[[`(1) %>%
stringr::str_replace("id: ", "") %>%
stringr::str_replace("\\}", "") %>%
paste(collapse = "{}") %>%
stringr::str_replace_all("CHEBI:", "")
database <-
x %>%
stringr::str_split("\\: \\[") %>%
`[[`(1) %>%
`[`(1)
data.frame(database = database, id = id)
}) %>%
do.call(rbind, .) %>%
as.data.frame()
if (return_form == "list") {
return_result <-
list(
models_containing_reaction = models_containing_reaction,
bigg_id = bigg_id,
old_identifiers = old_identifiers,
pseudoreaction = pseudoreaction,
name = name,
reaction_string = reaction_string,
metabolites = metabolites,
database_link = database_link
)
} else{
models_bigg_id <-
models_containing_reaction$bigg_id %>%
paste(collapse = "{}")
models_bigg_organism <-
models_containing_reaction$organism %>%
paste(collapse = "{}")
metabolite_bigg_id <-
metabolites$bigg_id %>%
paste(collapse = "{}")
metabolite_name <-
metabolites$name %>%
paste(collapse = "{}")
metabolites_compartment_bigg_id <-
metabolites$compartment_bigg_id %>%
paste(collapse = "{}")
metabolites_stoichiometry <-
metabolites$stoichiometry %>%
paste(collapse = "{}")
return_result <-
data.frame(
bigg_id = bigg_id,
old_identifiers = old_identifiers,
pseudoreaction = pseudoreaction,
name = name,
reaction_string = reaction_string,
models_bigg_id = models_bigg_id,
models_bigg_organism = models_bigg_organism,
metabolite_bigg_id = metabolite_bigg_id,
metabolite_name = metabolite_name,
metabolites_compartment_bigg_id = metabolites_compartment_bigg_id,
metabolites_stoichiometry = metabolites_stoichiometry
)
database_link <-
database_link %>%
dplyr::mutate(
database = case_when(
database == "EC Number" ~ "EC_Number",
database == "Reactome Reaction" ~ "Reactome",
database == "SEED Reaction" ~ "SEED",
database == "Human Metabolome Database" ~ "HMDB",
database == "MetaNetX (MNX) Equation" ~ "MetaNetX",
database == "KEGG Reaction" ~ "KEGG",
TRUE ~ database
)
)
missing_id <-
setdiff(
c(
"RHEA",
"KEGG",
"BioCyc",
"Reactome",
"Reactome",
"SEED",
"MetaNetX"
),
database_link$database
)
if (length(missing_id) > 0) {
new_database_link <-
data.frame(database = missing_id, id = NA)
database_link <-
rbind(database_link, new_database_link)
}
database_link <-
database_link %>%
dplyr::arrange(database)
id <-
as.data.frame(matrix(database_link$id, nrow = 1))
colnames(id) <- database_link$database
return_result <-
cbind(return_result, id)
}
invisible(return_result)
}
#' @title Read the BIGG model from download_bigg_model function
#' @description Read the BIGG model from download_bigg_model function
#' @author Xiaotao Shen
#' \email{shenxt1990@@outlook.com}
#' @param path Default is .. Should be same with
#' download_bigg_model function.
#' @param model model
#' @return A data frame
#' @importFrom magrittr %>%
#' @importFrom plyr dlply .
#' @importFrom readr read_delim
#' @importFrom dplyr mutate bind_rows select distinct rename full_join filter
#' @importFrom tidyr pivot_wider
#' @importFrom purrr map
#' @export
read_bigg_model <-
function(path = ".", model = "iND750") {
if (requireNamespace("rjson", quietly = TRUE)) {
result <-
rjson::fromJSON(file = file.path(path, paste0(model, ".json")))
} else{
stop("Please install rjson package first.")
}
return(result)
}
tidymass/massdatabase documentation built on Oct. 18, 2024, 3:56 p.m.
R Package Documentation
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Defines functions request_bigg_version
Documented in request_bigg_version
#' Request BiGG Database Version
#'
#' This function retrieves the current version of the BiGG database from the BiGG API.
#'
#' @param url A string specifying the URL of the BiGG database version endpoint.
#' Defaults to `"http://bigg.ucsd.edu/api/v2/database_version"`.
#'
#' @details
#' The function makes an HTTP request to the BiGG database version endpoint using `curl`.
#' It parses the response to extract the version information, returning it as a data frame
#' with two columns: `name` and `value`. If the request fails, the function returns `NULL`.
#'
#' @return A data frame containing the version information of the BiGG database with two columns:
#' - `name`: The type of version information (e.g., "bigg_models_version").
#' - `value`: The corresponding value of the version information.
#'
#' @examples
#' \dontrun{
#' # Retrieve the current version of the BiGG database
#' version_info <- request_bigg_version()
#'
#' # Use a custom API URL
#' version_info <- request_bigg_version(url = "http://bigg.ucsd.edu/api/v2/custom_endpoint")
#' }
#'
#' @importFrom curl curl
#' @importFrom stringr str_replace_all str_split str_trim
#' @export
request_bigg_version <-
function(url = "http://bigg.ucsd.edu/api/v2/database_version") {
options(warn = -1)
x <-
tryCatch(
curl::curl(url = url),
error = function(e)
NULL
)
open(x)
out <- readLines(x, warn = FALSE)
close(x)
# cat(out, sep = "\n")
out <-
out %>%
stringr::str_replace_all("\"", "") %>%
stringr::str_replace_all("\\{|\\}", "") %>%
stringr::str_split(pattern = "\\,") %>%
`[[`(1) %>%
stringr::str_trim() %>%
stringr::str_split("\\: ") %>%
do.call(rbind, .) %>%
as.data.frame()
colnames(out) <- c("name", "value")
return(out)
}
#' @title Download BIGG model data
#' @description Download BIGG model data
#' @author Xiaotao Shen
#' \email{shenxt1990@@outlook.com}
#' @param model_id model_id, for example, iND750
#' @param path Default is .
#' @return version.
#' @export
download_bigg_model <-
function(model_id = "iND750", path = ".") {
dir.create(path, showWarnings = FALSE, recursive = TRUE)
url <-
paste0('http://bigg.ucsd.edu/static/models/', model_id, '.json')
system(command = paste('curl -O', url))
if (!paste0(model_id, '.json') %in% dir(path)) {
file.copy(
from = file.path(".", paste0(model_id, '.json')),
to = file.path(path, paste0(model_id, '.json')),
overwrite = TRUE,
recursive = TRUE
)
unlink(x = file.path(".", paste0(model_id, '.json')),
recursive = TRUE,
force = TRUE)
}
}
#' @title Request BIGG model information
#' @description Request BIGG model information
#' @author Xiaotao Shen
#' \email{shenxt1990@@outlook.com}
#' @param url url http://bigg.ucsd.edu/api/v2/models
#' @return model information
#' @importFrom curl curl
#' @importFrom stringr str_replace_all str_extract str_replace str_split
#' @importFrom stringr str_trim
#' @export
#' @examples
#' x <- request_bigg_model_info()
#' head(x)
request_bigg_model_info <-
function(url = "http://bigg.ucsd.edu/api/v2/models") {
x <-
curl::curl(url = url)
open(x)
out <- readLines(x, warn = FALSE)
close(x)
# cat(out, sep = "\n")
out <-
out %>%
stringr::str_replace_all("\"", "") %>%
stringr::str_replace_all("\\{results\\: ", "")
model_count <-
stringr::str_extract(out, "results_count\\: [0-9]{2,3}") %>%
stringr::str_replace("results_count\\: ", "") %>%
as.numeric()
out <-
out %>%
stringr::str_replace_all("\\, results_count\\: [0-9]{2,3}\\}", "") %>%
stringr::str_replace(pattern = "^\\[", "") %>%
stringr::str_replace(pattern = "\\]$", "")
out <-
out %>%
stringr::str_split(pattern = "\\}, \\{") %>%
`[[`(1) %>%
stringr::str_replace_all("^\\{", "") %>%
stringr::str_replace_all("\\}$", "") %>%
lapply(function(x) {
x <-
stringr::str_split(x, "\\,")[[1]] %>%
stringr::str_trim() %>%
lapply(function(y) {
stringr::str_split(y, "\\: ")[[1]]
}) %>%
do.call(rbind, .) %>%
as.data.frame()
x1 <- matrix(data = x[, 2], nrow = 1) %>%
as.data.frame()
colnames(x1) <- x$V1
x1
}) %>%
do.call(rbind, .) %>%
as.data.frame()
out$gene_count <- as.numeric(out$gene_count)
out$reaction_count <- as.numeric(out$reaction_count)
out$metabolite_count <- as.numeric(out$metabolite_count)
invisible(out)
}
#' @title Request BIGG universal metabolite information
#' @description Request BIGG universal metabolite information
#' @author Xiaotao Shen
#' \email{shenxt1990@@outlook.com}
#' @param url url http://bigg.ucsd.edu/api/v2/universal/metabolites
#' @return universal metabolite information
#' @importFrom curl curl
#' @importFrom stringr str_replace_all str_extract str_replace str_split
#' @importFrom stringr str_trim
#' @export
#' @examples
#' x <- request_bigg_universal_metabolite_info()
#' dim(x)
#' head(x)
request_bigg_universal_metabolite_info <-
function(url = "http://bigg.ucsd.edu/api/v2/universal/metabolites") {
x <-
curl::curl(url = url)
open(x)
out <- readLines(x, warn = FALSE)
close(x)
out <-
out %>%
stringr::str_replace_all("\"", "") %>%
stringr::str_replace_all("\\{results\\: ", "")
metabolite_count <-
stringr::str_extract(out, "results_count\\: [0-9]{2,5}") %>%
stringr::str_replace("results_count\\: ", "") %>%
as.numeric()
out <-
out %>%
stringr::str_replace_all("\\, results_count\\: [0-9]{2,5}\\}", "") %>%
stringr::str_replace(pattern = "^\\[", "") %>%
stringr::str_replace(pattern = "\\]$", "")
out <-
out %>%
stringr::str_split(pattern = "\\}, \\{") %>%
`[[`(1) %>%
stringr::str_replace_all("^\\{", "") %>%
stringr::str_replace_all("\\}$", "") %>%
lapply(function(x) {
x <-
x %>%
stringr::str_split(", name\\: ") %>%
`[[`(1) %>%
stringr::str_split(", model_bigg_id\\: ") %>%
unlist() %>%
stringr::str_replace_all("bigg_id: ", "")
}) %>%
do.call(rbind, .) %>%
as.data.frame()
colnames(out) <- c("bigg_id", "name", "model_bigg_id")
invisible(out)
}
#' @title Request BIGG metabolite
#' @description Request BIGG metabolite
#' @author Xiaotao Shen
#' \email{shenxt1990@@outlook.com}
#' @param url url http://bigg.ucsd.edu/api/v2/universal/metabolites
#' @param metabolite_id metabolite_id, for example, g3p
#' @param return_form data.frame or list.
#' @return universal metabolite information
#' @importFrom curl curl
#' @importFrom stringr str_replace_all str_extract str_replace str_split
#' @importFrom stringr str_trim
#' @export
#' @examples
#' x <- request_bigg_universal_metabolite(metabolite_id = "g3p", return_form = "list")
#' x
#' y <- request_bigg_universal_metabolite(metabolite_id = "g3p", return_form = "data.frame")
#' y
request_bigg_universal_metabolite <-
function(url = "http://bigg.ucsd.edu/api/v2/universal/metabolites",
metabolite_id = "g3p",
return_form = c("list", "data.frame")) {
return_form <- match.arg(return_form)
url <- paste0(url, "/", metabolite_id)
x <-
curl::curl(url = url)
open(x)
out <- readLines(x, warn = FALSE)
close(x)
out <-
out %>%
stringr::str_replace_all("\"", "") %>%
stringr::str_replace_all("\\{results\\: ", "")
out <-
out %>%
stringr::str_replace(pattern = "^\\{", "") %>%
stringr::str_replace(pattern = "\\}$", "")
database_link <-
stringr::str_extract(string = out, pattern = "database_links: .+\\}, bigg_id:") %>%
stringr::str_replace("database_links: \\{", "") %>%
stringr::str_replace("\\}, bigg_id:", "")
database_link <-
database_link %>%
stringr::str_split("\\],") %>%
`[[`(1) %>%
stringr::str_trim() %>%
stringr::str_replace("\\]", "") %>%
lapply(function(x) {
id <-
x %>%
stringr::str_extract_all("id: .{1,50}\\}") %>%
`[[`(1) %>%
stringr::str_replace("id: ", "") %>%
stringr::str_replace("\\}", "") %>%
paste(collapse = "{}") %>%
stringr::str_replace_all("CHEBI:", "")
database <-
x %>%
stringr::str_split("\\: \\[") %>%
`[[`(1) %>%
`[`(1)
data.frame(database = database, id = id)
}) %>%
do.call(rbind, .) %>%
as.data.frame()
bigg_id <-
stringr::str_extract(string = out, pattern = "\\}, bigg_id: [a-zA-Z0-9_-]{1,100}, formulae:") %>%
stringr::str_replace(", formulae:", "") %>%
stringr::str_replace("\\}, bigg_id: ", "")
formula <-
stringr::str_extract(string = out, pattern = "formulae: .{1,100}, old_identifiers") %>%
stringr::str_replace("formulae: ", "") %>%
stringr::str_replace(", old_identifiers", "") %>%
stringr::str_replace("\\[", "") %>%
stringr::str_replace("\\]", "") %>%
stringr::str_replace_all(", ", "{}")
old_identifiers <-
stringr::str_extract(string = out, pattern = "old_identifiers: .{1,100}, charges:") %>%
stringr::str_replace("old_identifiers: ", "") %>%
stringr::str_replace(", charges:", "") %>%
stringr::str_replace("\\[", "") %>%
stringr::str_replace("\\]", "") %>%
stringr::str_replace_all(", ", "{}")
charges <-
stringr::str_extract(string = out, pattern = "charges: .{1,100}, name:") %>%
stringr::str_replace("charges: ", "") %>%
stringr::str_replace(", name:", "") %>%
stringr::str_replace("\\[", "") %>%
stringr::str_replace("\\]", "") %>%
stringr::str_replace_all(", ", "{}")
name <-
stringr::str_extract(string = out, pattern = "name: .{1,300}, compartments_in_models:") %>%
stringr::str_replace("name: ", "") %>%
stringr::str_replace(", compartments_in_models:", "")
compartments_in_models <-
stringr::str_extract(string = out, pattern = "compartments_in_models: .+\\}\\]") %>%
stringr::str_replace("compartments_in_models: ", "") %>%
stringr::str_replace("\\[", "") %>%
stringr::str_replace("\\]", "")
compartments_in_models <-
compartments_in_models %>%
stringr::str_split("\\}, \\{") %>%
`[[`(1) %>%
stringr::str_replace("^\\{", "") %>%
stringr::str_replace("\\}\\]$", "") %>%
stringr::str_replace("bigg_id: ", "") %>%
stringr::str_split(", organism: |, model_bigg_id: ") %>%
do.call(rbind, .) %>%
as.data.frame()
colnames(compartments_in_models) <-
c("bigg_id", "organism", "model_bigg_id")
if (return_form == "list") {
return_result <-
list(
bigg_id = bigg_id,
name = name,
formula = formula,
old_identifiers = old_identifiers,
charges = charges,
database_link = database_link,
compartments_in_models = compartments_in_models
)
} else{
organism <-
compartments_in_models$organism %>%
paste(collapse = "{}")
model_bigg_id <-
compartments_in_models$model_bigg_id %>%
paste(collapse = "{}")
return_result <-
data.frame(
bigg_id = bigg_id,
name = name,
formula = formula,
old_identifiers = old_identifiers,
charges = charges,
organism = organism,
model_bigg_id = model_bigg_id
)
database_link <-
database_link %>%
dplyr::mutate(
database = case_when(
database == "InChI Key" ~ "InChI_Key",
database == "Reactome Compound" ~ "Reactome",
database == "SEED Compound" ~ "SEED",
database == "Human Metabolome Database" ~ "HMDB",
database == "MetaNetX (MNX) Chemical" ~ "MetaNetX",
database == "KEGG Compound" ~ "KEGG",
database == "KEGG Drug" ~ "KEGG_Drug",
database == "KEGG Glycan" ~ "KEGG_Glycan",
TRUE ~ database
)
)
missing_id <-
setdiff(
c(
"InChI_Key",
"Reactome",
"SEED",
"CHEBI",
"HMDB",
"MetaNetX",
"KEGG",
"KEGG_Drug",
"KEGG_Glycan",
"LipidMaps",
"BioCyc"
),
database_link$database
)
if (length(missing_id) > 0) {
new_database_link <-
data.frame(database = missing_id, id = NA)
database_link <-
rbind(database_link, new_database_link) %>%
dplyr::filter(database != "")
}
database_link <-
database_link %>%
dplyr::arrange(database)
id <-
as.data.frame(matrix(database_link$id, nrow = 1))
colnames(id) <- database_link$database
return_result <-
cbind(return_result, id)
}
invisible(return_result)
}
#' Download BiGG Universal Metabolite Data
#'
#' This function downloads the BiGG universal metabolite database, saving it to a specified directory.
#' It provides the option to store intermediate files and control the download rate by introducing a delay.
#'
#' @param path A string specifying the directory to save the downloaded data. Defaults to the current directory (`"."`).
#' @param sleep A numeric value indicating the number of seconds to pause between downloads. Defaults to 1 second.
#' @param delete_intermediate A logical value indicating whether to delete intermediate files after the download completes. Defaults to `TRUE`.
#'
#' @details
#' The function first retrieves a list of all available metabolites from the BiGG database using
#' `request_bigg_universal_metabolite_info()`. It saves this information in an intermediate directory.
#' For each metabolite, the function checks if the data already exists locally; if not, it downloads the data using
#' `request_bigg_universal_metabolite()`.
#'
#' A progress bar is shown during the download process. The final data is saved as `bigg_universal_metabolit_database`
#' in the specified path. If `delete_intermediate = TRUE`, intermediate files are deleted after the download completes.
#'
#' @return None. The function saves the downloaded data to the specified directory.
#'
#' @examples
#' \dontrun{
#' # Download BiGG universal metabolite data to the current directory
#' download_bigg_universal_metabolite()
#'
#' # Download data to a custom path with 2 seconds of sleep between downloads
#' download_bigg_universal_metabolite(path = "data", sleep = 2)
#'
#' # Keep intermediate files
#' download_bigg_universal_metabolite(delete_intermediate = FALSE)
#' }
#'
#' @importFrom progress progress_bar
#' @export
download_bigg_universal_metabolite <-
function(path = ".",
sleep = 1,
delete_intermediate = TRUE) {
dir.create(path, recursive = TRUE, showWarnings = FALSE)
dir.create(file.path(path, "intermediate"),
recursive = TRUE,
showWarnings = FALSE)
metabolite_info <-
request_bigg_universal_metabolite_info()
message(nrow(metabolite_info), " metabolites in total")
save(metabolite_info,
file = file.path(path, "intermediate/metabolite_info"))
pb <- progress::progress_bar$new(total = nrow(metabolite_info))
###download metabolite
bigg_universal_metabolit_database <-
vector(mode = "list", length = nrow(metabolite_info))
names(bigg_universal_metabolit_database) <- metabolite_info$bigg_id
for (i in seq_len(nrow(metabolite_info))) {
pb$tick()
id <- metabolite_info$bigg_id[i]
if (file.exists(file.path(path, "intermediate", paste0(id)))) {
load(file = file.path(path, "intermediate", paste0(id)))
bigg_universal_metabolit_database[[i]] <- metabolite
} else{
Sys.sleep(time = sleep)
metabolite <-
request_bigg_universal_metabolite(metabolite_id = metabolite_info$bigg_id[i],
return_form = "data.frame")
save(metabolite, file = file.path(path, "intermediate", id))
bigg_universal_metabolit_database[[i]] <- metabolite
}
}
save(
bigg_universal_metabolit_database,
file = file.path(path, "bigg_universal_metabolit_database")
)
if (delete_intermediate) {
unlink(file.path(path, "intermediate"), recursive = TRUE)
}
}
#' Read BiGG Universal Metabolite Data
#'
#' This function reads the saved BiGG universal metabolite database from the specified directory
#' and returns it as a combined data frame.
#'
#' @param path A string specifying the directory where the BiGG database is located. Defaults to the current directory (`"."`).
#'
#' @details
#' The function loads the previously saved `bigg_universal_metabolit_database` file from the provided directory.
#' It uses a progress bar to indicate the loading progress and combines individual metabolite data into a
#' single data frame using `dplyr::bind_rows()`. The final data frame is returned to the user.
#'
#' @return A data frame containing all the metabolites from the BiGG universal database.
#'
#' @examples
#' \dontrun{
#' # Read the BiGG database from the current directory
#' metabolites <- read_bigg_universal_metabolite()
#'
#' # Read the BiGG database from a custom directory
#' metabolites <- read_bigg_universal_metabolite(path = "data")
#' }
#'
#' @importFrom progress progress_bar
#' @importFrom dplyr bind_rows
#' @export
read_bigg_universal_metabolite <-
function(path = ".") {
load(file.path(path, "bigg_universal_metabolit_database"))
pb <-
progress::progress_bar$new(total =
length(bigg_universal_metabolit_database))
bigg_universal_metabolit_database <-
bigg_universal_metabolit_database %>%
dplyr::bind_rows() %>%
as.data.frame()
return(bigg_universal_metabolit_database)
}
#' Convert BiGG Universal Metabolite Data to MetID Format
#'
#' This function converts the BiGG universal metabolite database into a format compatible with the `metid` package.
#' It processes the metabolite formulas, calculates mass-to-charge ratios (m/z), and maps various IDs for downstream use.
#'
#' @param data A data frame containing BiGG metabolite information, including formulas and IDs.
#' @param path A string specifying the directory where the output data will be saved. Defaults to the current directory (`"."`).
#' @param threads An integer specifying the number of threads to use for parallel processing. Defaults to 5.
#'
#' @details
#' The function processes the provided metabolite data by:
#' - Handling missing formulas and modifying them based on charge.
#' - Calculating the mass-to-charge ratio (m/z) for each metabolite using `Rdisop`.
#' - Renaming and reformatting columns for compatibility with the `metid` package.
#' - Writing the processed data to a temporary CSV file and creating a `metid`-compatible database.
#'
#' The final processed database is saved as `bigg_ms1` in the specified path, and intermediate files are cleaned up.
#'
#' @return An invisible object containing the converted database.
#'
#' @examples
#' \dontrun{
#' # Convert BiGG metabolite data to MetID format and save to the current directory
#' convert_bigg_universal2metid(data = bigg_data)
#'
#' # Save the converted data to a custom directory using multiple threads
#' convert_bigg_universal2metid(data = bigg_data, path = "metid_data", threads = 10)
#' }
#'
#' @importFrom dplyr filter rename mutate select bind_rows
#' @importFrom purrr map
#' @importFrom stringr str_split str_replace str_replace_all
#' @importFrom Rdisop getMass getMolecule
#' @importFrom progress progress_bar
#' @importFrom readr write_csv
#' @export
convert_bigg_universal2metid <-
function(data,
path = ".",
threads = 5) {
dir.create(path, showWarnings = FALSE, recursive = TRUE)
####Formula and mz
data[which(data == "", arr.ind = TRUE)] <- NA
data <-
data %>%
dplyr::filter(!is.na(formula))
####add formula to H or remove H based on charge
message("Extract formula...")
pb <-
progress::progress_bar$new(total = nrow(data))
formula <-
seq_len(nrow(data)) %>%
purrr::map(function(idx) {
# cat(idx, " ")
pb$tick()
charge = data$charges[idx]
formula <- data$formula[idx]
if (is.na(charge)) {
return(data$formula[idx])
}
if (charge == "0") {
return(data$formula[idx])
}
if (length(grep("\\{\\}", charge)) == 0) {
charge <- as.numeric(charge)
adduct = paste0(ifelse(charge > 0, "M-", "M+"), abs(charge), "H")
formula <-
masstools::sum_formula(formula = formula, adduct = adduct)
return(formula)
}
if (length(grep("\\{\\}", charge)) > 0) {
charge <- as.numeric(stringr::str_split(charge, "\\{\\}")[[1]])
formula <- stringr::str_split(formula, "\\{\\}")[[1]]
if (length(charge) != length(formula)) {
return(NA)
}
if (any(charge) == 0) {
return(formula[which(charge == 0)])
}
adduct = paste0(ifelse(charge[1] > 0, "M-", "M+"), abs(charge[1]), "H")
formula <-
masstools::sum_formula(formula = formula[1], adduct = adduct)
return(formula)
}
}) %>%
unlist()
data$formula <- formula
data$HMDB <-
data$HMDB %>%
purrr::map(function(x) {
if (is.na(x)) {
return(x)
}
x <- stringr::str_split(x, "\\{\\}")[[1]]
x <- stringr::str_replace(x, "HMDB", "HMDB00")
x <- paste(x, collapse = "{}")
x
}) %>%
unlist()
data <-
data %>%
dplyr::filter(!is.na(formula))
###add mz
message("Calculating mz...")
pb <-
progress::progress_bar$new(total = nrow(data))
mz <-
seq_len(nrow(data)) %>%
purrr::map(function(i) {
pb$tick()
temp <-
tryCatch(
Rdisop::getMass(Rdisop::getMolecule(data$formula[i])),
error = function(e)
NA
)
}) %>%
unlist()
data$mz <- mz
data <-
data %>%
dplyr::filter(!is.na(mz))
data <-
data %>%
dplyr::rename(
BIGG.ID = bigg_id,
Compound.name = name,
Formula = formula,
BIOCYC.ID = BioCyc,
CHEBI.ID = CHEBI,
HMDB.ID = HMDB,
INCHIKEY.ID = InChI_Key,
KEGG.ID = KEGG,
METANETX.ID = MetaNetX,
REACTOME.ID = Reactome,
SEED.ID = SEED,
KEGG_DRUG.ID = KEGG_Drug,
KEGG_GLYCAN.ID = KEGG_Glycan,
LIPIDMAPS.ID = LipidMaps
) %>%
dplyr::mutate(
Lab.ID = BIGG.ID,
CAS.ID = NA,
RT = NA,
mz.pos = NA,
mz.neg = NA,
Submitter = "BIGG"
) %>%
dplyr::select(
Lab.ID,
Compound.name,
mz,
RT,
CAS.ID,
HMDB.ID,
KEGG.ID,
Formula,
mz.pos,
mz.neg,
Submitter,
everything()
)
data$Synonyms <-
data$Compound.name %>%
stringr::str_replace_all("; ", "\\{\\}")
data$Compound.name <-
data$Synonyms %>%
stringr::str_split("\\{\\}") %>%
lapply(function(x) {
x[1]
}) %>%
unlist()
temp_file <- tempfile()
dir.create(temp_file, showWarnings = FALSE)
readr::write_csv(x = data, file = file.path(temp_file, "data.csv"))
bigg_ms1 =
metid::construct_database(
path = temp_file,
version = as.character(Sys.Date()),
metabolite.info.name = "data.csv",
source = "BIGG",
link = "http://bigg.ucsd.edu/",
creater = "Xiaotao Shen",
email = "shenxt@stanford.edu",
rt = FALSE,
threads = threads
)
unlink(file.path(temp_file, "data.csv"))
unlink(temp_file)
save(bigg_ms1, file = file.path(path, "bigg_ms1"))
invisible(bigg_ms1)
}
#' @title Request BIGG universal reaction information
#' @description Request BIGG universal reaction information
#' @author Xiaotao Shen
#' \email{shenxt1990@@outlook.com}
#' @param url url http://bigg.ucsd.edu/api/v2/universal/reactions
#' @return universal metabolite information
#' @importFrom curl curl
#' @importFrom stringr str_replace_all str_extract str_replace str_split
#' @importFrom stringr str_trim
#' @export
#' @examples
#' x <- request_bigg_universal_reaction_info()
#' dim(x)
#' head(x)
request_bigg_universal_reaction_info <-
function(url = "http://bigg.ucsd.edu/api/v2/universal/reactions") {
x <-
curl::curl(url = url)
open(x)
out <- readLines(x, warn = FALSE)
close(x)
out <-
out %>%
stringr::str_replace_all("\"", "") %>%
stringr::str_replace_all("\\{results\\: ", "")
reaction_count <-
stringr::str_extract(out, "results_count\\: [0-9]{2,5}") %>%
stringr::str_replace("results_count\\: ", "") %>%
as.numeric()
out <-
out %>%
stringr::str_replace_all("\\, results_count\\: [0-9]{2,5}\\}", "") %>%
stringr::str_replace(pattern = "^\\[", "") %>%
stringr::str_replace(pattern = "\\]$", "")
out <-
out %>%
stringr::str_split(pattern = "\\}, \\{") %>%
`[[`(1) %>%
stringr::str_replace_all("^\\{", "") %>%
stringr::str_replace_all("\\}$", "") %>%
lapply(function(x) {
x <-
x %>%
stringr::str_split(", name\\: ") %>%
`[[`(1) %>%
stringr::str_split(", model_bigg_id\\: ") %>%
unlist() %>%
stringr::str_replace_all("bigg_id: ", "")
}) %>%
do.call(rbind, .) %>%
as.data.frame()
colnames(out) <- c("bigg_id", "name", "model_bigg_id")
invisible(out)
}
#' @title Request BIGG reaction information for specific species (model)
#' @description Request BIGG reaction information for specific species
#' @author Xiaotao Shen
#' \email{shenxt1990@@outlook.com}
#' @param model_bigg_id please use the model bigg id using the
#' request_bigg_model_info function. Default is iAB_RBC_283 (human)
#' @return reaction information
#' @importFrom curl curl
#' @importFrom stringr str_replace_all str_extract str_replace str_split
#' @importFrom stringr str_trim
#' @export
#' @examples
#' x <- request_bigg_universal_reaction_info()
#' dim(x)
#' head(x)
request_bigg_reaction_info <-
function(model_bigg_id = "iAB_RBC_283") {
url <-
paste0("http://bigg.ucsd.edu/api/v2/models/",
model_bigg_id,
"/reactions")
x <-
curl::curl(url = url)
open(x)
out <- readLines(x, warn = FALSE)
close(x)
out <-
out %>%
stringr::str_replace_all("\"", "") %>%
stringr::str_replace_all("\\{results\\: ", "")
reaction_count <-
stringr::str_extract(out, "results_count\\: [0-9]{2,5}") %>%
stringr::str_replace("results_count\\: ", "") %>%
as.numeric()
out <-
out %>%
stringr::str_replace_all("\\, results_count\\: [0-9]{2,5}\\}", "") %>%
stringr::str_replace(pattern = "^\\[", "") %>%
stringr::str_replace(pattern = "\\]$", "")
out <-
out %>%
stringr::str_split(pattern = "\\}, \\{") %>%
`[[`(1) %>%
stringr::str_replace_all("^\\{", "") %>%
stringr::str_replace_all("\\}$", "") %>%
lapply(function(x) {
x <-
x %>%
stringr::str_split(", name\\: ") %>%
`[[`(1) %>%
stringr::str_split(", model_bigg_id\\: ") %>%
unlist() %>%
stringr::str_replace_all("bigg_id: ", "")
}) %>%
do.call(rbind, .) %>%
as.data.frame()
colnames(out) <- c("bigg_id", "name", "model_bigg_id")
invisible(out)
}
#' @title Request BIGG reaction
#' @description Request BIGG reaction
#' @author Xiaotao Shen
#' \email{shenxt1990@@outlook.com}
#' @param url url http://bigg.ucsd.edu/api/v2/universal/reactions
#' @param reaction_id reaction_id, for example, ADA
#' @param return_form data.frame or list.
#' @return universal metabolite information
#' @importFrom curl curl
#' @importFrom stringr str_replace_all str_extract str_replace str_split
#' @importFrom stringr str_trim
#' @export
#' @examples
#' x <- request_bigg_universal_reaction(reaction_id = "ADA", return_form = "list")
#' x
#' y <- request_bigg_universal_reaction(reaction_id = "ADA", return_form = "data.frame")
#' y
request_bigg_universal_reaction <-
function(url = "http://bigg.ucsd.edu/api/v2/universal/reactions",
reaction_id = "ADA",
return_form = c("list", "data.frame")) {
return_form <- match.arg(return_form)
url <- paste0(url, "/", reaction_id)
x <-
curl::curl(url = url)
open(x)
out <- readLines(x, warn = FALSE)
close(x)
out <-
out %>%
stringr::str_replace_all("\"", "") %>%
stringr::str_replace_all("\\{results\\: ", "")
out <-
out %>%
stringr::str_replace(pattern = "^\\{", "") %>%
stringr::str_replace(pattern = "\\}$", "")
models_containing_reaction <-
stringr::str_extract(string = out, pattern = "models_containing_reaction: \\[.+\\}\\], reaction_string: ") %>%
stringr::str_replace("models_containing_reaction: \\[", "") %>%
stringr::str_replace("\\], reaction_string: ", "")
models_containing_reaction <-
models_containing_reaction %>%
stringr::str_split("\\}, \\{") %>%
`[[`(1) %>%
stringr::str_trim() %>%
stringr::str_replace("\\{|\\}", "") %>%
stringr::str_split(", organism: ") %>%
lapply(function(x) {
x <-
stringr::str_replace(x, "bigg_id: ", "")
x
}) %>%
do.call(rbind, .) %>%
as.data.frame()
colnames(models_containing_reaction) <-
c("bigg_id", "organism")
bigg_id <-
stringr::str_extract(string = out, pattern = "\\]\\}\\, bigg_id\\: .{1,20}, old_identifiers\\: ") %>%
stringr::str_replace("\\]\\}, bigg_id\\: ", "") %>%
stringr::str_replace("\\, old_identifiers\\: ", "")
old_identifiers <-
stringr::str_extract(string = out, pattern = "old_identifiers: .{1,50}, name: ") %>%
stringr::str_replace("old_identifiers: ", "") %>%
stringr::str_replace(", name: ", "") %>%
stringr::str_replace("\\[", "") %>%
stringr::str_replace("\\]", "") %>%
stringr::str_replace_all(", ", "{}")
pseudoreaction <-
stringr::str_extract(string = out, pattern = "pseudoreaction: .{1,20}") %>%
stringr::str_replace("pseudoreaction: ", "")
name <-
stringr::str_extract(string = out, pattern = "name: .{1,100}, pseudoreaction:") %>%
stringr::str_replace("name: ", "") %>%
stringr::str_replace(", pseudoreaction:", "")
reaction_string <-
stringr::str_extract(string = out, pattern = "reaction_string: .{1,100}, metabolites: ") %>%
stringr::str_replace("reaction_string: ", "") %>%
stringr::str_replace(", metabolites: ", "")
metabolites <-
stringr::str_extract(string = out, pattern = "metabolites: \\[.+, database_links: ") %>%
stringr::str_replace("metabolites: \\[\\{", "") %>%
stringr::str_replace("\\}\\], database_links: ", "")
metabolites <-
metabolites %>%
stringr::str_split("\\}, \\{") %>%
`[[`(1) %>%
stringr::str_trim() %>%
stringr::str_split(", name: |, compartment_bigg_id: |, stoichiometry: ") %>%
lapply(function(x) {
x <-
stringr::str_replace_all(x, "bigg_id: ", "")
x
}) %>%
do.call(rbind, .) %>%
as.data.frame()
colnames(metabolites) <-
c("bigg_id", "name", "compartment_bigg_id", "stoichiometry")
database_link <-
stringr::str_extract(string = out, pattern = "database_links:.+\\}, bigg_id: ") %>%
stringr::str_replace("database_links: \\{", "") %>%
stringr::str_replace("\\]\\}, bigg_id:", "") %>%
stringr::str_trim()
database_link <-
database_link %>%
stringr::str_split("\\],") %>%
`[[`(1) %>%
stringr::str_trim() %>%
stringr::str_replace("\\]", "") %>%
lapply(function(x) {
id <-
x %>%
stringr::str_extract_all("id: .{1,50}\\}") %>%
`[[`(1) %>%
stringr::str_replace("id: ", "") %>%
stringr::str_replace("\\}", "") %>%
paste(collapse = "{}") %>%
stringr::str_replace_all("CHEBI:", "")
database <-
x %>%
stringr::str_split("\\: \\[") %>%
`[[`(1) %>%
`[`(1)
data.frame(database = database, id = id)
}) %>%
do.call(rbind, .) %>%
as.data.frame()
if (return_form == "list") {
return_result <-
list(
models_containing_reaction = models_containing_reaction,
bigg_id = bigg_id,
old_identifiers = old_identifiers,
pseudoreaction = pseudoreaction,
name = name,
reaction_string = reaction_string,
metabolites = metabolites,
database_link = database_link
)
} else{
models_bigg_id <-
models_containing_reaction$bigg_id %>%
paste(collapse = "{}")
models_bigg_organism <-
models_containing_reaction$organism %>%
paste(collapse = "{}")
metabolite_bigg_id <-
metabolites$bigg_id %>%
paste(collapse = "{}")
metabolite_name <-
metabolites$name %>%
paste(collapse = "{}")
metabolites_compartment_bigg_id <-
metabolites$compartment_bigg_id %>%
paste(collapse = "{}")
metabolites_stoichiometry <-
metabolites$stoichiometry %>%
paste(collapse = "{}")
return_result <-
data.frame(
bigg_id = bigg_id,
old_identifiers = old_identifiers,
pseudoreaction = pseudoreaction,
name = name,
reaction_string = reaction_string,
models_bigg_id = models_bigg_id,
models_bigg_organism = models_bigg_organism,
metabolite_bigg_id = metabolite_bigg_id,
metabolite_name = metabolite_name,
metabolites_compartment_bigg_id = metabolites_compartment_bigg_id,
metabolites_stoichiometry = metabolites_stoichiometry
)
database_link <-
database_link %>%
dplyr::mutate(
database = case_when(
database == "EC Number" ~ "EC_Number",
database == "Reactome Reaction" ~ "Reactome",
database == "SEED Reaction" ~ "SEED",
database == "Human Metabolome Database" ~ "HMDB",
database == "MetaNetX (MNX) Equation" ~ "MetaNetX",
database == "KEGG Reaction" ~ "KEGG",
TRUE ~ database
)
)
missing_id <-
setdiff(
c(
"RHEA",
"KEGG",
"BioCyc",
"Reactome",
"Reactome",
"SEED",
"MetaNetX"
),
database_link$database
)
if (length(missing_id) > 0) {
new_database_link <-
data.frame(database = missing_id, id = NA)
database_link <-
rbind(database_link, new_database_link)
}
database_link <-
database_link %>%
dplyr::arrange(database)
id <-
as.data.frame(matrix(database_link$id, nrow = 1))
colnames(id) <- database_link$database
return_result <-
cbind(return_result, id)
}
invisible(return_result)
}
#' @title Read the BIGG model from download_bigg_model function
#' @description Read the BIGG model from download_bigg_model function
#' @author Xiaotao Shen
#' \email{shenxt1990@@outlook.com}
#' @param path Default is .. Should be same with
#' download_bigg_model function.
#' @param model model
#' @return A data frame
#' @importFrom magrittr %>%
#' @importFrom plyr dlply .
#' @importFrom readr read_delim
#' @importFrom dplyr mutate bind_rows select distinct rename full_join filter
#' @importFrom tidyr pivot_wider
#' @importFrom purrr map
#' @export
read_bigg_model <-
function(path = ".", model = "iND750") {
if (requireNamespace("rjson", quietly = TRUE)) {
result <-
rjson::fromJSON(file = file.path(path, paste0(model, ".json")))
} else{
stop("Please install rjson package first.")
}
return(result)
}
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