R/check_sce.R

In LieberInstitute/spatialLIBD: spatialLIBD: an R/Bioconductor package to visualize spatially-resolved transcriptomics data

#' Check input sce
#'
#' This function checks that the `sce` object has the appropriate structure.
#' This is a legacy function and we highly encourage you to use
#' [SpatialExperiment-class][SpatialExperiment::SpatialExperiment-class]
#' objects and check them with `check_spe()`.
#'
#' @inheritParams sce_to_spe
#' @param variables A `character()` vector of variable names expected to
#' be present in `colData(sce)`.
#'
#' @return The input object if all checks are passed.
#' @export
#' @importFrom methods is
#' @importFrom SummarizedExperiment assayNames
#' @family Check input functions
#'
#' @examples
#'
#' if (enough_ram()) {
#'     ## Obtain the necessary data
#'     if (!exists("sce_example")) sce_example <- fetch_data("sce_example")
#'
#'     ## Check the object
#'     check_sce(sce_example)
#' }
check_sce <- function(sce,
    variables = c(
        "GraphBased",
        "ManualAnnotation",
        "Maynard",
        "Martinowich",
        paste0("SNN_k50_k", 4:28),
        "spatialLIBD",
        "cell_count",
        "sum_umi",
        "sum_gene",
        "expr_chrM",
        "expr_chrM_ratio",
        "SpatialDE_PCA",
        "SpatialDE_pool_PCA",
        "HVG_PCA",
        "pseudobulk_PCA",
        "markers_PCA",
        "SpatialDE_UMAP",
        "SpatialDE_pool_UMAP",
        "HVG_UMAP",
        "pseudobulk_UMAP",
        "markers_UMAP",
        "SpatialDE_PCA_spatial",
        "SpatialDE_pool_PCA_spatial",
        "HVG_PCA_spatial",
        "pseudobulk_PCA_spatial",
        "markers_PCA_spatial",
        "SpatialDE_UMAP_spatial",
        "SpatialDE_pool_UMAP_spatial",
        "HVG_UMAP_spatial",
        "pseudobulk_UMAP_spatial",
        "markers_UMAP_spatial"
    )) {
    ## Should be a SingleCellExperiment object
    stopifnot(is(sce, "SingleCellExperiment"))

    ## Images data stored under metadata(sce)$image
    stopifnot("image" %in% names(metadata(sce)))
    stopifnot(all(c("sample", "grob") %in% colnames(metadata(sce)$image)))

    ## Ensembl gene IDs are rownames with the symbol (gene_name) and Ensembl
    ## ID (gene_name) pasted into `gene_search`
    stopifnot(all(
        c("gene_id", "gene_name", "gene_search") %in% colnames(rowData(sce))
    ))
    stopifnot(identical(
        paste0(rowData(sce)$gene_name, "; ", rowData(sce)$gene_id),
        rowData(sce)$gene_search
    ))

    ## Rownames are Ensembl ids
    stopifnot(identical(rownames(sce), rowData(sce)$gene_id))

    ## Information about the image coordinates stored in imagerow and imagecol
    ## The sample names stored under sce$sample_name

    ## Some cluster variables, though you could potentially edit
    ## spatialLIBD::app_ui()
    ## or this could be made into a run_app() argument.

    ## Some continuous variables
    stopifnot(all(
        c(
            "imagerow",
            "imagecol",
            "sample_name",
            "key",
            variables
        ) %in% colnames(colData(sce))
    ))

    ## A unique spot-level ID (such as barcode) stored under sce$key
    ## The 'key' column is necessary for the plotly code to work.
    stopifnot(length(unique(sce$key)) == ncol(sce))
    # identical(sce$key, paste0(sce$sample_name, '_', sce$barcode))

    ## None of the values of rowData(sce)$gene_search should be re-used in
    ## colData(sce)
    stopifnot(!all(rowData(sce)$gene_search %in% colnames(colData(sce))))

    ## No column named COUNT as that's used by sce_image_gene_p() and related
    ## functions.
    stopifnot(!"COUNT" %in% colnames(colData(sce)))

    ## The counts and logcounts assays
    stopifnot(all(c("counts", "logcounts") %in% assayNames(sce)))

    ## Done!
    return(sce)
}