Description of your analysis
hise
: The HISE SDK package for R
purrr
: Functional programming in R
furrr
: Parallel functional programming
library(dplyr)
library(hise)
library(purrr)
library(furrr)
Attaching package: ‘dplyr’ The following objects are masked from ‘package:stats’: filter, lag The following objects are masked from ‘package:base’: intersect, setdiff, setequal, union
plan("multicore", workers = 8)
cache_uuid_path <- function(uuid) {
if(!dir.exists(paste0("cache/", uuid))) {
hise_res <- cacheFiles(list(uuid))
}
cache_path <- paste0("cache/",uuid)
cache_file <- list.files(cache_path, full.names = TRUE)
cache_file
}
search_id <- "polonium-tin-curium"
Retrieve the list of files stored in our HISE project store
ps_files <- listFilesInProjectStores(list("cohorts"))
ps_files <- map(
ps_files$files,
function(l) {
l <- l[c("id", "name")]
as.data.frame(l)
}) %>%
list_rbind()
Filter for files from the previous notebook using our search_id and the .tar extension
tar_files <- ps_files %>%
filter(grepl(search_id, name)) %>%
filter(grepl(".tar$", name))
tar_files$name
future_walk(
tar_files$id,
function(uuid) {
tar_file <- cache_uuid_path(uuid)
untar_call <- paste("tar -xf", tar_file)
system(untar_call)
}
)
sample_files <- list.files("sample_h5ad", full.names = TRUE)
head(sample_files)
out_path <- "output"
if (!dir.exists(out_path)) {
dir.create(out_path)
}
out_file <- paste0(out_path, "/analysis_result_", Sys.Date(), ".csv")
write.csv(result, out_file)
study_space_uuid <- ""
title <- paste0("CertPro Analysis Result ", Sys.Date())
search_id <- ids::proquint(n_words = 3)
search_id
in_files <- list(file_uuid)
in_files
out_files <- list(out_file)
out_files
uploadFiles(
studySpaceId = study_space_uuid,
title = title,
files = out_files,
inputFileIds = in_list,
store = "project",
destination = search_id
)
import session_info
session_info.show()