plan %>% drake::vis_drake_graph(targets_only = T)
loadd(abundance_heatmap_plot)
abundance_heatmap_plot
loadd(intra_feature_type_coabundances)
intra_feature_type_coabundances %>%
mutate(
n_nodes = coabundance %>% map_int(~ {
.x %>% igraph::gorder()
}),
n_edges = coabundance %>% map_int(~ {
.x %>%
igraph::gsize() %>%
as.integer()
})
) %>%
select(-coabundance) %>%
filter(n_nodes > 0 | n_edges > 0) %>%
arrange(-n_nodes, -n_edges) %>%
knitr::kable()
| disease | feature_type | method | n_nodes | n_edges |
|---|---|---|---|---|
| healthy | pathway | spearman | 19 | 38 |
| healthy | pathway | banocc | 19 | 23 |
| CRC | pathway | spearman | 18 | 50 |
| healthy | taxon | spearman | 18 | 29 |
| CRC | pathway | banocc | 18 | 22 |
| healthy | taxon | banocc | 18 | 18 |
| CRC | taxon | banocc | 12 | 9 |
| CRC | taxon | spearman | 10 | 11 |
| CRC | taxon | sparcc | 5 | 3 |
| healthy | taxon | sparcc | 4 | 2 |
loadd(intra_feature_type_network_plots)
intra_feature_type_network_plots %<>%
mutate(plot = list(plot, feature_type, disease) %>%
pmap(~ ..1 + labs(title = paste0(..2, "-", ..3)))) %>%
group_by(method) %>%
do(plots = .$plot %>% wrap_plots() + plot_layout(guides = "collect")) %>%
deframe()
content above tabbed region.