#' Cell-cycle markers
#'
#' Data provenence information, including the organism and Ensembl release are
#' defined in `metadata()`.
#'
#' @export
#' @note Updated 2022-04-25.
#'
#' @return `CellTypeMarkers`
setClass(
Class = "CellCycleMarkers",
contains = "CompressedSplitDFrameList"
)
setValidity(
Class = "CellCycleMarkers",
method = function(object) {
validate(
areSetEqual(
x = colnames(object[[1L]]),
y = c("geneId", "geneName", "phase")
)
## > isSubset(
## > x = c("date", "organism", "provider", "release"),
## > y = names(metadata(object))
## > )
)
}
)
#' Cell-type markers
#'
#' Data provenence information, including the organism and Ensembl release are
#' defined in `metadata()`.
#'
#' @export
#' @note Updated 2022-04-25.
#'
#' @return `CellTypeMarkers`
setClass(
Class = "CellTypeMarkers",
contains = "CompressedSplitDFrameList"
)
setValidity(
Class = "CellTypeMarkers",
method = function(object) {
validate(
areSetEqual(
x = colnames(object[[1L]]),
y = c("cellType", "geneId", "geneName")
)
## > isSubset(
## > x = c("date", "organism", "provider", "release"),
## > y = names(metadata(object))
## > )
)
}
)
#' Known markers
#'
#' Class containing known markers detected.
#'
#' Results are grouped by `cellType` column and arranged by adjusted *P* value
#' (`padj`).
#'
#' @export
#' @note Updated 2022-04-25.
#'
#' @return `KnownMarkers`.
setClass(
Class = "KnownMarkers",
contains = "DFrame"
)
setValidity(
Class = "KnownMarkers",
method = function(object) {
validate(
## Consider requiring "avgLog2Fc" column here.
isSubset(
x = c(
"cellType",
"cluster",
"geneId",
"geneName",
"name",
"padj",
"pvalue"
),
y = colnames(object)
),
isSubset(
x = c("alphaThreshold", "date", "packageVersion"),
y = names(metadata(object))
)
)
}
)
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