use 'instrumented' do_SingleR(i)

testi

source("inst.R", echo=TRUE)
library(Rcollectl)
library(AnVILBestPractices)
library(SingleR)
library(BiocParallel)
   clid = cl_start()
   Rcollectl::cl_timestamp(clid, "pre-data")
   p3k = TENxPBMCData::TENxPBMCData("pbmc3k")
   Rcollectl::cl_timestamp(clid, "3k loaded")
   rownames(p3k) = make.names(rowData(p3k)$Symbol, unique=TRUE)
   pred3k = do_SingleRi(p3k, clprocid=clid, BPPARAM=MulticoreParam(12))
   table(pred3k$preds$pruned.labels)
   head(pred3k$preds)
   cl_stop(clid)
Sys.sleep(2)
   path = Rcollectl::cl_result_path(clid)
   Rcollectl::plot_usage(Rcollectl::cl_parse(path)) +
       Rcollectl::cl_timestamp_layer(path) +
       Rcollectl::cl_timestamp_label(path) +
       ggplot2::theme(axis.text.x = ggplot2::element_text(angle = 90, vjust = 0.5, hjust=1))