Last updated: 2021-04-13

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Knit directory: mage_2020_marker-gene-benchmarking/

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Rmd b5b2a88 Jeffrey Pullin 2021-04-13 Add new results
Rmd 3a4cb2e Jeffrey Pullin 2021-03-15 Update 16/3/2021
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library(tibble)
library(dplyr)
library(ggplot2)
library(tidyr)
library(purrr)
library(pals)

source(here::here("code", "analysis-utils.R"))

Aim

Measure the time the different methods take to run.

Data loading

results_folder <- here::here("results")
file_names <- list.files(results_folder, full.names = TRUE)

times <- numeric(length(file_names))
for (i in seq_along(file_names)) {
  if (!isTRUE(getOption("knitr.in.progress"))) {
    print(i)
  }
  res <- readRDS(file_names[[i]])
  times[[i]] <- res$time
  rm(res)
}

times <- tibble(time = times, file_name = basename(file_names))
pars <- retrive_simulation_parameters()

time_data <- left_join(pars, times, by = "file_name")

time_data <- time_data %>% 
  rowwise() %>% 
  mutate(num_clusters = if_else(is.na(n_clus), length(group.prob), n_clus)) %>% 
  ungroup()

Plots

All methods

Total number of cells

Linear time scale

time_data %>% 
  mutate(pars = method_name) %>% 
  filter(sim_label == "num_cells") %>%
  ggplot(aes(x = batchCells, y = time, colour = pars)) +
  geom_point() + 
  geom_smooth(method = "lm", se = FALSE, formula = y ~ x) + 
  scale_x_continuous(breaks = c(100, 500, 1000, 2000, 3000)) + 
  # FIXME: Improve colours.
  scale_colour_manual(values = unname(polychrome(20))) + 
  labs(
    title = "Runtime vs total number of cells - all methods",
    x = "Number of cells", 
    y = "Time (s)", 
    colour = "Method"
  ) + 
  theme_bw()

log time scale

time_data %>% 
  mutate(pars = method_name) %>% 
  filter(sim_label == "num_cells") %>%
  ggplot(aes(x = batchCells, y = time, colour = pars)) +
  geom_point() + 
  geom_smooth(method = "lm", se = FALSE, formula = y ~ x) + 
  scale_x_continuous(breaks = c(100, 500, 1000, 2000, 3000)) +
  scale_y_log10() + 
  scale_colour_manual(values = unname(polychrome(20))) + 
  labs(
    title = "log(runtime) vs total number of cells - all methods",
    x = "Number of cells", 
    y = "Time (s)", 
    colour = "Method"
  ) + 
  theme_bw()

Number of clusters

Linear time scale

time_data %>% 
  rowwise() %>% 
  mutate(num_clusters = if_else(is.na(n_clus), length(group.prob), n_clus)) %>% 
  filter(sim_label == "num_clusters") %>%
  ggplot(aes(x = num_clusters, y = time, col = pars)) +
  geom_point() + 
  geom_smooth(method = "lm", se = FALSE, formula = y ~ x) +
  scale_colour_manual(values = unname(polychrome(20))) + 
  labs(
    title = "Runtime vs number of clusters - all methods",
    x = "Number of clusters", 
    y = "Time (s)", 
    colour = "Method") + 
  theme_bw()

time_data %>% 
  rowwise() %>% 
  mutate(num_clusters = if_else(is.na(n_clus), length(group.prob), n_clus)) %>% 
  filter(sim_label == "num_clusters") %>%
  ggplot(aes(x = num_clusters, y = time, col = pars)) +
  geom_point() + 
  geom_smooth(method = "lm", se = FALSE, formula = y ~ x) + 
  scale_y_log10() + 
  scale_colour_manual(values = unname(polychrome(20))) + 
  labs(
    title = "Runtime vs number of clusters - all methods",
    x = "Number of clusters", 
    y = "Time (s)", 
    colour = "Method") + 
  theme_bw()

scran

Total number of cells

time_data %>% 
  filter(sim_label == "num_cells") %>% 
  filter(method == "scran") %>%
  mutate(scran_pars = paste0(test.type, "_", pval.type)) %>% 
  ggplot(aes(x = batchCells, y = time, colour = scran_pars)) +
  geom_point() + 
  geom_smooth(method = "lm", se = FALSE, formula = y ~ x) + 
  scale_x_continuous(breaks = c(100, 500, 1000, 2000, 3000)) + 
  labs(
    title = "Runtime vs total number of cells - scran", 
    x = "Total number of cells", 
    y = "Time (s)", 
    colour = "scran options") + 
  theme_bw()

Version Author Date
ca82ce0 Jeffrey Pullin 2021-02-16
2863555 Jeffrey Pullin 2021-02-10

Number of clusters

time_data %>% 
  rowwise() %>% 
  mutate(num_clusters = if_else(is.na(n_clus), length(group.prob), n_clus)) %>% 
  filter(sim_label == "num_clusters") %>%
  filter(method == "scran") %>%
  ggplot(aes(x = num_clusters, y = time, col = pars)) +
  geom_point() + 
  geom_smooth(method = "lm", se = FALSE, formula = y ~ x) + 
  labs(
    title = "Runtime vs number of clusters - scran", 
    x = "Number of clusters", 
    y = "Time (s)",
    colour = "scran options"
  ) + 
  theme_bw()

Seurat

Total number of cells

time_data %>% 
  filter(sim_label == "num_cells") %>% 
  filter(method == "seurat") %>%
  ggplot(aes(x = batchCells, y = time, col = test.use)) +
  geom_point() + 
  geom_smooth(method = "lm", se = FALSE, formula = y ~ x) + 
  labs(
    y = "Time (s)",
    x = "Test method", 
    col = "Test used"
  ) + 
  theme_bw() + 
  theme(axis.text.x = element_text(angle = 45, hjust = 1))

Version Author Date
ca82ce0 Jeffrey Pullin 2021-02-16
2863555 Jeffrey Pullin 2021-02-10

Number of clusters

time_data %>% 
  filter(sim_label == "num_clusters") %>%
  filter(method == "seurat") %>%
  ggplot(aes(x = num_clusters, y = time, col = test.use)) +
  geom_point() + 
  geom_smooth(method = "lm", se = FALSE, formula = y ~ x) + 
  labs(
    y = "Time (s)", 
    x = "Number of clusters",
    col = "Test used"
  ) + 
  theme_bw()

All times

For slurm optimization

time_data %>% 
  ggplot(aes(x = time)) + 
  geom_histogram(binwidth = 200) +
  geom_vline(xintercept = 60 * 20, col = "blue") + 
  geom_vline(xintercept = 60 * 30, col = "red") + 
  geom_vline(xintercept = 60 * 60, col = "green") + 
  geom_vline(xintercept = 120 * 60, col = "yellow") + 
  labs(x = "Time (s)", y = "Count") + 
  theme_bw()

Version Author Date
ca82ce0 Jeffrey Pullin 2021-02-16
2863555 Jeffrey Pullin 2021-02-10

devtools::session_info()
─ Session info ───────────────────────────────────────────────────────────────
 setting  value                       
 version  R version 4.0.3 (2020-10-10)
 os       CentOS Linux 7 (Core)       
 system   x86_64, linux-gnu           
 ui       X11                         
 language (EN)                        
 collate  en_AU.UTF-8                 
 ctype    en_AU.UTF-8                 
 tz       UTC                         
 date     2021-04-13                  

─ Packages ───────────────────────────────────────────────────────────────────
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[1] /home/jpullin/R_libs
[2] /opt/R/4.0.3/lib/R/library