In steinbaugh/pointillism: Single-cell RNA-seq toolkit

## nolint start
suppressPackageStartupMessages({
    library(goalie)
    library(basejump)
    library(Seurat)
    library(pointillism)
})
prepareTemplate(package = "pointillism")
source("_setup.R")
initDir(params[["results_dir"]])
## nolint end

Load objects

file <- params[["seurat_file"]]
object <- import(file)
name <- basenameSansExt(file)
rm(file)
assert(
    is(object, "Seurat"),
    is.character(name)
)
invisible(validObject(object))
file <- params[["all_markers_file"]]
markers <- import(file)
rm(file)
assert(is(markers, "SeuratMarkersPerCluster"))
invisible(validObject(markers))
file <- params[["known_markers_file"]]
knownMarkers <- import(file)
rm(file)
assert(is(knownMarkers, "KnownMarkers"))
invisible(validObject(knownMarkers))
## Check that object has organism and gene-to-symbol mappings defined.
assert(
    is.character(organism(object)),
    is(GeneToSymbol(object), "GeneToSymbol")
)
print(object)

Top markers per cluster {.tabset}

topMarkers(markers)

plotTopMarkers(
    object = object,
    markers = markers,
    headerLevel = 2L,
    dark = params[["dark"]]
)

Known cell type markers {.tabset}

plotKnownMarkers(
    object = object,
    markers = knownMarkers,
    headerLevel = 2L,
    dark = params[["dark"]]
)

Cell types per cluster {.tabset}

plotCellTypesPerCluster(
    object = object,
    markers = knownMarkers,
    headerLevel = 2L,
    dark = params[["dark"]]
)

ctpc <- cellTypesPerCluster(knownMarkers)
assignAndSaveData(
    name = paste(name, "cell_types_per_cluster", sep = "_"),
    object = ctpc,
    dir = params[["data_dir"]]
)
print(ctpc)