#' Updates shinycell config to recognize a metadata as a discrete one
#'
#' Updates shinycell config to recognize a metadata as a discrete one. This
#' function is useful when a discrete metadata only contains integers, e.g.
#' unspervised cluster labels starting from 0 to (n-1) clusters. If these
#' metadata are not factored, then ShinyCell is unable to recognise these
#' as discrete metadata automatically. This is especially important when
#' working with loom files as they do not support factors/levels by default.
#'
#' @param scConf shinycell config data.table
#' @param meta.to.input metadata from the single-cell metadata to be made
#' discrete. Must match one of the following:
#' \itemize{
#' \item{Seurat objects}: column names in \code{seu@meta.data}
#' i.e. \code{colnames(seu@meta.data)}
#' \item{SCE objects}: column names in \code{sce@colData}
#' i.e. \code{colnames(sce@colData)}
#' \item{h5ad files}: column names in \code{h5ad.obs}
#' i.e. \code{h5ad.obs.columns.values}
#' \item{loom files}: column names in \code{loom/col_attrs}
#' i.e. \code{loom/col_attrs.names}
#' }
#' @param obj input single-cell object for Seurat (v3+) / SingleCellExperiment
#' data or input file path for h5ad / loom files
#' @param maxLevels maximum number of levels allowed for categorical metadata.
#' Metadata with nlevels > maxLevels will throw up an error message
#'
#' @return updated shinycell config data.table
#'
#' @author John F. Ouyang
#'
#' @import data.table reticulate hdf5r
#'
#' @examples
#' scConf = makeMetaCategorical(scConf, "clusterID", loom_obj)
#'
#' @export
makeMetaCategorical <- function(scConf, meta.to.input, obj, maxLevels = 50){
meta = meta.to.input[1] # use only the first one
# Extract corresponding metadata
if(class(obj)[1] == "Seurat"){
# Seurat Object
objMeta = obj@meta.data
} else if (class(obj)[1] == "SingleCellExperiment"){
# SCE Object
objMeta = SingleCellExperiment::colData(obj)
} else if (tolower(tools::file_ext(obj)) == "h5ad"){
# h5ad file
ad <- import("anndata", convert = FALSE)
inpH5 = ad$read_h5ad(obj)
objMeta = data.frame(py_to_r(inpH5$obs$values))
rownames(objMeta) = py_to_r(inpH5$obs_names$values)
colnames(objMeta) = py_to_r(inpH5$obs$columns$values)
for(i in colnames(objMeta)){
objMeta[[i]] = unlist(objMeta[[i]]) # unlist and refactor
if(as.character(inpH5$obs[i]$dtype) == "category"){
objMeta[[i]] = factor(objMeta[[i]], levels =
py_to_r(inpH5$obs[i]$cat$categories$values))
}
}
} else if (tolower(tools::file_ext(obj)) == "loom"){
# loom file
inpLM = H5File$new(obj, mode = "r+")
cellIdx = which(inpLM[["col_attrs"]]$names == "CellID")
if(length(cellIdx) != 1){
stop("CellID attribute not found in col_attrs in loom file!")
}
objMeta = data.frame(row.names = inpLM[["col_attrs"]][["CellID"]]$read())
for(i in inpLM[["col_attrs"]]$names[-cellIdx]){
tmp = inpLM[["col_attrs"]][[i]]$read()
if(length(tmp) == nrow(objMeta)){objMeta[[i]] = tmp}
}
inpLM$close_all()
} else {
stop("Only Seurat/SCE objects or h5ad/loom file paths are accepted!")
}
# Check if meta exist in obj metadata
if(!all(meta %in% colnames(objMeta))){
stop("meta.to.input not found in single-cell data object!")
}
if(!all(meta %in% scConf$ID)){
stop("meta.to.input not found in shinycell config!")
}
# Start discretizing meta.data
objMeta[[meta]] = factor(objMeta[[meta]])
nLevels = nlevels(objMeta[[meta]])
if(nLevels > maxLevels){
stop(paste0(meta,
" has exceeded the maximum number of levels allowed!"))
}
if(nLevels >= 2){
scConf[ID == meta]$fID = paste0(levels(objMeta[[meta]]), collapse = "|")
scConf[ID == meta]$fUI = scConf[ID == meta]$fID
scConf[ID == meta]$fCL = paste0(colorRampPalette(brewer.pal(12, "Paired"))(nLevels),
collapse = "|")
scConf[ID == meta]$fRow = ceiling(nLevels / 4)
scConf[ID == meta]$grp = TRUE
} else if(nLevels == 1){
scConf[ID == meta]$fID = levels(objMeta[[meta]])
scConf[ID == meta]$fUI = scConf[ID == meta]$fID
scConf[ID == meta]$fCL = "black"
scConf[ID == meta]$fRow = 1
}
return(scConf)
}
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