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"))
To investigate the TPR performance of the different methods on simualted datasets.
<- retrive_simulation_parameters() %>%
metrics_data 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]])) %>%
::rename(sel_mgs = mgs) %>%
dplyrungroup()
<- function(data,
plot_tpr
data_id, n_true = 20,
n_sel = 40,
direction = "up") {
<- dataset_lookup[data_id]
plot_dataset
%>%
data filter(data_id == !!data_id) %>%
filter(sim_label == "standard") %>%
expand_grid(n_true = n_true, n_sel = n_sel) %>%
rowwise() %>%
::filter(!is.null(sel_mgs)) %>%
dplyrmutate(
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")
::session_info() devtools
─ 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
─ Packages ───────────────────────────────────────────────────────────────────
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