Plot within and between correlations for a continuous property

plot_within_btw_continuous.R

# Plot within and between correlations for a continuous property
plot_within_btw = function( data, info){

	library(tidyverse)
	library(corrr)

	if( ! all(c("ID", "Property") %in% colnames(info)) ){
		stop("info must have column names ID and Property")
	}

	if( ! identical(info$ID, colnames(data)) ){
		stop("info$ID and colnames(data) must be identical")
	}

	# compute correlations
	df_cor = correlate( data, quiet=TRUE ) %>%
		 		stretch() %>%
				filter(!is.na(r))

    # merge with info
	df = df_cor %>%
			inner_join(info %>% 
						rename(x = ID, Property.x = Property), 
						by='x') %>%
			inner_join(info %>% 
						rename(y = ID, Property.y = Property), 
						by='y') 

	# Plot
	fig = df %>%
		mutate(Status = Property.x & Property.y) %>%
		ggplot(aes(Status, r, fill=Status)) +
			geom_violin() + 
			geom_boxplot(width = 0.07, fill = "grey", outlier.color = "black") + 
		    theme_bw(15) + 
		    scale_fill_manual(values = c("grey90", "steelblue1")) + 
		    theme(legend.position = "none") + 
		    xlab("Property") + 
		    ylab("Correlation")

	list(fig = fig, df = df)	    
}

library(dreamlet)
library(tidyverse)

file = "/sc/arion/projects/psychAD/NPS-AD/freeze2_rc/processAssays/final/AGING_2024-02-01_22_23_processAssays_SubID_class.RDS"
res.proc2 = readRDS(file)

# form = ~ Source + Sex + scale(PMI) + log(n_genes) + percent_mito + mito_genes + mito_ribo + ribo_genes

form = ~ Sex
fit = dreamlet(res.proc2, form, assays="EN")


data = residuals(fit)[['EN']]

info = colData(res.proc2)
info$SubID = rownames(info)
info = info %>% 
		as_tibble %>% 
		select(SubID, Age) %>%
		mutate(Property = Age < 5) %>% # define within/btw
		rename(ID = SubID) %>%
		filter(ID %in% colnames(data))

res = plot_within_btw( data, info)

res$fig

> res$df
# A tibble: 79,242 × 7
   x     y            r Age.x Property.x Age.y Property.y
   <chr> <chr>    <dbl> <dbl> <lgl>      <dbl> <lgl>     
 1 H822  H823   0.0844     26 FALSE       50   FALSE     
 2 H822  H831   0.223      26 FALSE       85   FALSE     
 3 H822  H836   0.0989     26 FALSE       20   FALSE     
 4 H822  H845  -0.151      26 FALSE       24   FALSE     
 5 H822  H846  -0.193      26 FALSE       58   FALSE     
 6 H822  H847  -0.0703     26 FALSE        0.4 TRUE      
 7 H822  H848  -0.0925     26 FALSE       22   FALSE     
 8 H822  H863  -0.00587    26 FALSE       43   FALSE