Log fold-change values analysis
Last updated: 2024-01-01
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mage_2020_marker-gene-benchmarking/
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| Rmd | 11ee711 | Jeffrey Pullin | 2021-09-21 | Add analysis of Scanpy and Seurat log fold change values |
library(dplyr)
library(tibble)
library(ggplot2)
library(purrr)
library(patchwork)
library(scater)Load data
scanpy_t_pbmc3k <- readRDS(
here::here("results", "real_data", "pbmc3k-scanpy_t_rankby_abs.rds")
)
seurat_t_pbmc3k <- readRDS(
here::here("results", "real_data", "pbmc3k-seurat_t.rds")
)
pbmc3k <- readRDS(here::here("data", "real_data", "pbmc3k.rds"))scanpy_t_pbmc3k_mgs <- scanpy_t_pbmc3k %>%
pluck("result") %>%
select(gene, cluster, scanpy_log_fc = log_fc)
seurat_t_pbmc3k_mgs <- seurat_t_pbmc3k %>%
pluck("result") %>%
select(gene, cluster, seurat_log_fc = log_fc)
all_mgs <- left_join(
seurat_t_pbmc3k_mgs,
scanpy_t_pbmc3k_mgs,
by = c("gene", "cluster")
) %>%
mutate(log_fc_diff = seurat_log_fc - scanpy_log_fc) All clusters scatter plots
scatter_plot <- ggplot(all_mgs, aes(x = seurat_log_fc, y = scanpy_log_fc)) +
geom_point(colour = "forestgreen", alpha = 0.4) +
geom_abline() +
facet_wrap(~ cluster) +
labs(
x = "Seurat log fold-change value",
y = "Scanpy log fold-change value"
) +
theme_bw()
scatter_plot
saveRDS(scatter_plot, here::here("figures", "raw", "log-fc-scatter.rds"))B cluster scatter plot
log_fc_b_cluster_scatter_plot <- all_mgs %>%
filter(cluster == "B") %>%
ggplot(aes(x = seurat_log_fc, y = scanpy_log_fc)) +
geom_point(colour = "forestgreen", alpha = 0.4) +
geom_abline() +
labs(
x = "Seurat log fold-change value",
y = "Scanpy log fold-change value"
) +
theme_bw()
log_fc_b_cluster_scatter_plot
saveRDS(
log_fc_b_cluster_scatter_plot,
here::here("figures", "raw", "log-fc-b-cluster-scatter.rds")
)All clusters difference historgrams
ggplot(all_mgs, aes(x = log_fc_diff)) +
geom_histogram(bins = 50, fill = "forestgreen", colour = "black") +
facet_wrap(~ cluster) +
labs(
x = "Difference in log fold change values",
y = "Count"
) +
theme_bw()
Extreme Scanpy log fold-change values
all_mgs %>%
filter(scanpy_log_fc <= -20)# A tibble: 337 × 5
gene cluster seurat_log_fc scanpy_log_fc log_fc_diff
<chr> <chr> <dbl> <dbl> <dbl>
1 PLBD1 Memory CD4 T -0.743 -27.7 26.9
2 C19orf38 CD8 T -0.669 -27.7 27.0
3 IFI30 NK -1.17 -28.6 27.4
4 SLC7A7 NK -0.890 -28.2 27.3
5 RP11-290F20.3 NK -0.816 -27.9 27.1
6 FPR1 NK -0.803 -27.7 26.9
7 C19orf38 NK -0.639 -27.6 27.0
8 CD3G DC -1.22 -28.9 27.7
9 GZMA DC -2.00 -29.3 27.3
10 PRKCQ-AS1 DC -0.966 -28.4 27.5
# … with 327 more rowsplotExpression(pbmc3k, x = "label", features = "SLC7A7")
sum(logcounts(pbmc3k["SLC7A7", colLabels(pbmc3k) == "NK"]))[1] 0
devtools::session_info()─ Session info ──────────────────────────────────────────────────────────────
hash: flag: Afghanistan, eleven o’clock, woman: light skin tone, red hair
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date 2024-01-01
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