stemangiola

# PREMISE
# these implementation of HPCL is highly experimental. 
# Therefore the interface, function names, arguments names, types of input 
# are subject to change and to be extended.
# At this stage, the input is a named list of Seurat objects. 
# In another branch (soon to be integrated), we accept SCE, H5 SCE, and anndata

BiocManager::install("MangiolaLaboratory/HPCell@grammar-hpc", upgrade_dependencies=FALSE)
BiocManager::install("crew", upgrade_dependencies=FALSE)
BiocManager::install("crew.cluster", upgrade_dependencies=FALSE)

stemangiola

git remote set-url origin [email protected]:USERNAME/REPOSITORY.git

stemangiola

  
 get_cell_type_color = function(cell_type_vector){
  
  cell_type_vector |> 
    enframe(value = "harmonised_cell_type") |> 
    left_join(
      tribble(
        ~harmonised_cell_type, ~palette,
        

stemangiola

# Theme
friendly_cols <- dittoSeq::dittoColors()

#   scale_fill_manual(values = friendly_cols)
#   scale_color_manual(values = friendly_cols)

theme_multipanel =
  theme_bw() +
  theme(
    panel.border = element_blank(),

stemangiola

#' Convert array of quosure (e.g. c(col_a, col_b)) into character vector
#' 
#' @keywords internal
#'
#' @importFrom rlang quo_name
#' @importFrom rlang quo_squash
#' @importFrom purrr when
#' @importFrom magrittr equals
#'
#' @param v A array of quosures (e.g. c(col_a, col_b))

stemangiola

ToDataFrameTypeColFull = function(tree, ...){
	tree %>%
	Clone() %>%
	{
		t = (.)
		foreach(l=1:(t %$% Get("level") %>% max), .combine = bind_rows) %do% {
			data.tree::Clone(t) %>%
			{ data.tree::Prune(., function(x) x$level <= l + 1); . } %>%
				data.tree::ToDataFrameTypeCol(...) %>%
				as_tibble

stemangiola

get_bimodality = function(fit) {
fit %>%
    tidybayes::gather_draws(exposure_rate[S]) %>% summarise(
        bimodal = diptest::dip.test(`.value`) %$% `p.value`
       ) 
}

stemangiola

####################################################################
# From within R
####################################################################

####################################################################
# Initialisation of makefiles
####################################################################

dotR <- file.path(Sys.getenv("HOME"), ".R")
if (!file.exists(dotR)) dir.create(dotR)

stemangiola

generate_gamma_sum <- function(N, k, theta) {
	n_means = length(k)
  sums = numeric(N)
  for(n in 1:N) sums[n] = sum(rgamma(n_means, shape = k, scale = theta))
  list(sums = sums, shape = k, scale = theta)
}

k=c(3,4,5)
theta=c(1, 2, 1)
	generate_gamma_sum(10000, c(3,4,5), c(1, 2, 1)) %$% 

stemangiola

approximated_modified_bessel_second_kind_log = function(z, v, s = max(0,v-10)){

# s = 0 not approximated

  0.5 * ( log(pi) - log(2) ) + (-z - 0.5 * log(z)) +


  foreach(j = s:floor(v-0.5), .combine = c) %do% {

    lgamma(j + abs(v) - 0.5 + 1) -