#' @title \code{SeuratPipe}: Streamlining Seurat analysis
#' @description SeuratPipe contains common analysis, processing and
#' plotting functions with an attempt to streamline single-cell genomics
#' analysis using the Seurat package.
#' @docType package
#' @name SeuratPipe
#'
#' @return SeuratPipe main package documentation.
#'
#'
#' @author C.A.Kapourani \email{kapouranis.andreas@@gmail.com}
#'
#' @rawNamespace importFrom(rlang, "%||%")
#' @importFrom grDevices png pdf dev.off dev.list colorRampPalette
#' @importFrom stats filter median
#' @importFrom rlang fn_fmls
#' @importFrom utils head read.csv write.csv combn
#' @import ggplot2 BiocStyle
#'
NULL
#> NULL
# global reference to scrub (will be initialized in .onLoad)
scrub <- NULL
.onLoad <- function(libname = find.package("SeuratPipe"),
pkgname = "SeuratPipe"){
# use superassignment to update global reference to scrub
scrub <<- reticulate::import(module = "scrublet", convert = FALSE,
delay_load = TRUE)
# CRAN Note avoidance
if (getRversion() >= "2.15.1")
utils::globalVariables(
# sample file names from taxstats
c(# we use the magrittr pipe
"."
)
)
# https://stackoverflow.com/questions/9563711/r-color-palettes-for-many-data-classes
col_pal <- c(
"indianred", # red
"#6699CB",
"#FDBF6F", # lt orange
"#CAB2D6", # lt purple
"#FB9A99", # lt pink
"tan3",
"darkolivegreen4", # darkgreen
"darkgrey", # darkgrey
"skyblue2", # lightblue
"mediumpurple1",
"darkseagreen3",
"khaki2", "ivory3",
"steelblue4",
"#6A3D9A", # purple
"seagreen", "orchid1", "blue1", "deeppink1", "gold1",
"darkturquoise", "darkorange4", "#FF7F00",
"dodgerblue", "yellow3", "mediumorchid1", "firebrick4",
"wheat4", "maroon", "grey30", "red2", "burlywood2", "cyan",
"darkolivegreen2", "yellowgreen"
)
assign("discrete_col_pal", col_pal, envir = topenv())
base::invisible()
}
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