Visualize barcode rank plots for each sample

test <- demultiplexed_empty_joined %>%  filter(demultiplexed_empty_joined$FDR < 0.001) %>% select(FDR, empty_droplet)

## tidyseurat says: Key columns are missing. A data frame is returned for independent data analysis.

test |> select(empty_droplet) |> table()

## empty_droplet
## FALSE 
## 81090

Number of non-empty droplets, everything above knee is retained.

##    Mode   FALSE    TRUE    NA's 
## logical    8429   81090    9215

## is.cell
## FALSE  TRUE 
##  8429 81090

Check if p-values are lower-bounded by ‘niters’ (increase ‘niters’ if any Limited==TRUE and Sig==FALSE), with niters being: An integer scalar specifying the number of iterations to use for the Monte Carlo p-value calculations.

##        Limited
## Sig     FALSE  TRUE
##   FALSE  8429     0
##   TRUE  22814 58276

MA plot

(mitochondria genes in green, ribosomal genes in red)

Histogram of p-values: