R/data.R

In thomazbastiaanssen/anansi: Annotation-Based Analysis of Specific Interactions

#' Simplified snippet of the Krebs cycle
#' @name krebs
#' @description
#' Enzymes and metabolites that make up the Krebs cycle. Features share a row
#' when they play a role in the same reaction.
#' Used in vignettes, exported to facilitate user exploration.
#' @format A `data.frame` of two factors, named `"Enzyme"` and `"Metabolite"`,
#'     which contain these respective components of the krebs cycle.
#' @source Generated by hand based on the krebs cycle.
#' @importFrom utils data
#' @usage data("krebs", package = "anansi")
#'
"krebs"

#' @rdname kegg_link
#' @format `ec2ko`: a `data.frame` of two columns, named `"ec"`
#'     and `"ko"`. The IDs refer to KEGG orthologues. Enzyme commission numbers,
#'     ecs, typically describe reactions captured by them.
#'
#' @source `ec2ko`: Adapted from <https://www.genome.jp/kegg/>, using
#'     `KEGGREST`. Script to generate available in example.
#' @usage data("ec2ko", package = "anansi")
"ec2ko"

#' @rdname kegg_link
#' @format `ec2cpd`: a `data.frame` of two columns, named `"ec"` and `"cpd"`.
#'     The IDs refer to compounds in the KEGG database. Enzyme commission
#'     numbers, ecs, typically describe reactions either producing or requiring
#'     them.
#' @source `ec2cpd`: Adapted from <https://www.genome.jp/kegg/> using
#'     `KEGGREST`. Script to generate available in example.
#' @usage data("ec2cpd", package = "anansi")
#'
"ec2cpd"

#' Use linking data from the KEGG database.
#' @description
#' `kegg_link()` is a convenience function to return a list containing two
#' `data.frame`s; `ec2cpd` and `ec2ko`. This will be their most likely use.
#' `ec2cpd` and `ec2ko` are two `data.frame`s, used to link ko, ecs and cpd
#' identifiers in the KEGG database.
#'
#' @returns `kegg_link()` returns a list containing the two aforementioned
#'     data.frames, `ec2cpd` and `ec2ko`.
#' @examples
#' kegg_link()
#'
#' # Generate ec2ko and ec2cpd:
#' # Don't download during tests. set to `TRUE` to download.
#' dry_run <- TRUE
#'
#' if (!dry_run) {
#'     ec2ko <- KEGGREST::keggLink("ec", "ko")
#'     ec2ko <- data.frame(
#'         ec = gsub("ec:", "", x = ec2ko, fixed = TRUE),
#'         ko = gsub("ko:", "", x = names(ec2ko), fixed = TRUE),
#'         row.names = NULL
#'     )
#'
#'     ec2cpd <- KEGGREST::keggLink("ec", "cpd")
#'     ec2cpd <- data.frame(
#'         ec = gsub("ec:", "", x = ec2cpd, fixed = TRUE),
#'         cpd = gsub("cpd:", "", x = names(ec2cpd), fixed = TRUE),
#'         row.names = NULL
#'     )
#' }
#'
#' @export
#'
kegg_link <- function() {
    local({
        data("ec2ko", package = "anansi", envir = environment())
        data("ec2cpd", package = "anansi", envir = environment())
        return(list(ec2ko = get("ec2ko"), ec2cpd = get("ec2cpd")))
    })
}

#' Snippet of the CLR-transformed hippocampal metabolomics data from the FMT
#'     Aging study.
#'
#' @format A matrix object with three rows, compounds, and 36 columns, samples.
#' @source \doi{10.1038/s43587-021-00093-9}
#' @usage data("FMT_data", package = "anansi")
#'
"FMT_metab"

#' Snippet of the CLR-transformed inferred functional data from the FMT Aging
#'     study.
#'
#' @description Piphillin was used to infer functions from the 16S sequencing
#'     data in terms of KOs. Unfortunately, the Piphillin algorithm is
#'     proprietary and has since been taken down.
#'
#' @format A marix object with 6468 rows, KOs, and 36 columns, samples.
#' @source \doi{10.1038/s43587-021-00093-9}
#' @usage data("FMT_data", package = "anansi")
#'
"FMT_KOs"

#' Snippet of the metadata from the FMT Aging study.
#'
#' @description There were three treatment groups in the study that all received
#'     faecal microbiota transplantation (FMT). Young mice that received FMT
#'     from young mice (Young yFMT), aged mice that received FMT from aged mice
#'     (Aged oFMT) and aged mice that received FMT from young mice (Aged yFMT).
#' @format A data.frame object with 36 rows, samples, and two columns, denoting
#'     sample ID and treatment group, respectively.
#' @source \doi{10.1038/s43587-021-00093-9}
#' @usage data("FMT_data", package = "anansi")
#'
"FMT_metadata"