Last updated: 2022-02-09

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Knit directory: mage_2020_marker-gene-benchmarking/

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File Version Author Date Message
Rmd 262f46d Jeffrey Pullin 2022-02-08 Update simulation-based TPR analysis
Rmd aca9ad2 Jeffrey Pullin 2021-11-29 Various changes made in the last days before thesis submission
Rmd 98c856a Jeffrey Pullin 2021-09-28 Update analyses
Rmd e3d9f9e Jeffrey Pullin 2021-09-22 Polish tpr analysis
Rmd 27e8a89 Jeffrey Pullin 2021-09-21 Extend tpr analysis
Rmd 17f2a0f Jeffrey Pullin 2021-08-07 Add new plots and analysis for lab meeting 5/8/2021
Rmd 33c015d Jeffrey Pullin 2021-08-04 Fix off by error in rankcorr and run higher lambda values
Rmd 3fa1beb Jeffrey Pullin 2021-08-04 Update analysis code to new marker gene format
Rmd 92d3bf0 Jeffrey Pullin 2021-08-02 Add code to create plots for ECSSC talk
Rmd 15c9978 Jeffrey Pullin 2021-07-25 Update analysis for new simulations
Rmd e4bd7a9 Jeffrey Pullin 2021-07-22 Misc WIP changes to simulations and code
Rmd 74443b4 Jeffrey Pullin 2021-07-13 Update endothelial data processing and simulation outputs
Rmd acc6dd9 Jeffrey Pullin 2021-05-31 Large update
html 61ee246 Jeffrey Pullin 2021-04-13 Build site.
Rmd b5b2a88 Jeffrey Pullin 2021-04-13 Add new results
Rmd 07b49fa Jeffrey Pullin 2021-04-08 Finish rewriting TPR plots to use new framework
Rmd cd9837a Jeffrey Pullin 2021-04-08 Refactor how marker genes are extracted from methods
Rmd be29ac9 Jeffrey Pullin 2021-04-06 Rename tpr-fdr to tpr only

library(tibble)
library(dplyr)
library(ggplot2)
library(tidyr)
library(SingleCellExperiment)
library(scater)
library(forcats)
library(purrr)
library(patchwork)
source(here::here("code", "top-genes.R"))
source(here::here("code", "analysis-utils.R"))
source(here::here("code", "plot-utils.R"))

Aim

To investigate the TPR performance of the different methods on simualted datasets.

Data loading

metrics_data <- retrive_simulation_parameters() %>% 
  filter(sim_label == "standard") %>% 
  rowwise() %>% 
  mutate(
    mgs_raw = list(readRDS(full_filename)$result), 
    mgs = list(split(mgs_raw, mgs_raw$cluster))
  ) %>% 
  ungroup() %>% 
  unnest_longer(
    col = mgs, 
    values_to = "mgs", 
    indices_to = "cluster"
  ) %>% 
  select(-mgs_raw) %>% 
  mutate(umg_path = here::here(
    "data", "sim_mgs", paste0("mg-", sim_name, "-", data_id, ".rds")) 
  ) %>% 
  rowwise() %>% 
  mutate(true_mgs = list(readRDS(umg_path))) %>% 
  mutate(cluster_2 = paste0("group_", substr(cluster, 6, 6))) %>% 
  mutate(true_mgs = list(true_mgs[[cluster_2]])) %>% 
  dplyr::rename(sel_mgs = mgs) %>% 
  ungroup()
plot_tpr <- function(data, 
                     data_id, 
                     n_true = 20, 
                     n_sel = 40, 
                     direction = "up") {
  
  plot_dataset <- dataset_lookup[data_id]
  
  data %>%
    filter(data_id == !!data_id) %>% 
    filter(sim_label == "standard") %>% 
    expand_grid(n_true = n_true, n_sel = n_sel) %>% 
    rowwise() %>% 
    dplyr::filter(!is.null(sel_mgs)) %>% 
    mutate(
      true_mgs = list(get_top_true_mgs(
        true_mgs, 
        n = n_true, 
        direction = direction,
        sort_by_score = "mean_score")
      ),
      sel_mgs = list(get_top_sel_mgs(
        sel_mgs, 
        n = n_sel, 
        direction = direction)
      ), 
      tpr = calculate_tpr(sel_mgs$gene, true_mgs$gene)
    ) %>%  
    ungroup() %>% 
    mutate(plot_method = method_lookup[method]) %>% 
    mutate(plot_pars = pars_lookup[pars]) %>% 
    mutate(plot_pars = fct_reorder(
      factor(plot_pars), 
      tpr, 
      .fun = function(x) median(x) + min(x))
    ) %>% 
    ggplot(aes(x = plot_pars, y = tpr, colour = plot_method)) + 
    geom_boxplot() + 
    coord_flip(ylim = c(0, 1)) + 
    scale_y_continuous(breaks = seq(0, 1, by = 0.2)) +
    labs(
      y = "Proportion of true genes recovered", 
      x = "Method", 
      colour = "Method",
      title = paste0(plot_dataset, " dataset"),
    ) + 
    theme_bw()
}
plot_tpr(metrics_data, "pbmc3k", n_true = 20, n_sel = 20)

plot_tpr(metrics_data, "pbmc3k", n_true = 5, n_sel = 5)

plot_tpr(metrics_data, "pbmc3k", n_true = 40, n_sel = 40)

plot_tpr(metrics_data, "pbmc3k", n_true = 20, n_sel = 40)

plot_tpr(metrics_data, "pbmc3k", n_true = 20, n_sel = 40, direction = "both")

wrap_plots(
  plot_tpr(metrics_data, "pbmc3k"),
  plot_tpr(metrics_data, "pbmc3k", n_true = 5, n_sel = 10) + labs(x = ""),
  guides = "collect"
)

wrap_plots(
  plot_tpr(metrics_data, "pbmc3k", n_true = 20, n_sel = 20),
  plot_tpr(metrics_data, "pbmc3k", n_true = 5, n_sel = 5) + labs(x = ""),
  guides = "collect"
)

wrap_plots(
  plot_tpr(metrics_data, "lawlor"),
  plot_tpr(metrics_data, "lawlor", n_true = 5, n_sel = 10) + labs(x = ""),
  guides = "collect"
)

plot_tpr(metrics_data, "lawlor", n_true = 10, n_sel = 10)

wrap_plots(
  plot_tpr(metrics_data, "lawlor", n_true = 20, n_sel = 20),
  plot_tpr(metrics_data, "lawlor", n_true = 5, n_sel = 5) + labs(x = ""),
  guides = "collect"
)

plot_tpr(metrics_data, "lawlor", n_true = 10, n_sel = 10)

wrap_plots(
  plot_tpr(metrics_data, "zeisel"),
  plot_tpr(metrics_data, "zeisel", n_true = 5, n_sel = 10) + labs(x = ""),
  guides = "collect"
)

plot_tpr(metrics_data, "zeisel")

plot_tpr(metrics_data, "lawlor")

plot_tpr(metrics_data, "pbmc3k", direction = "down", n_sel = 20, n_true = 10)

plot_tpr(metrics_data, "zeisel", direction = "down")

plot_tpr(metrics_data, "lawlor", direction = "down")

plot_tpr(metrics_data, "pbmc3k", direction = "both")

plot_tpr(metrics_data, "zeisel", direction = "both")

plot_tpr(metrics_data, "lawlor", direction = "both")


devtools::session_info()
─ Session info ───────────────────────────────────────────────────────────────
 setting  value                       
 version  R version 4.1.0 (2021-05-18)
 os       Red Hat Enterprise Linux    
 system   x86_64, linux-gnu           
 ui       X11                         
 language (EN)                        
 collate  en_AU.UTF-8                 
 ctype    en_AU.UTF-8                 
 tz       Australia/Melbourne         
 date     2022-02-09                  

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[2] /usr/local/easybuild-2019/easybuild/software/mpi/gcc/10.2.0/openmpi/4.0.5/r/4.1.0/lib64/R/library