mmplot to support group based labelling about mmgenome2 HOT 3 CLOSED

labelframe<-data %>% 
  select(starts_with("cov"),binID) %>%
  filter(!is.na(binID)) %>%
  group_by(binID) %>%
  replace(., is.na(.), 0) %>%
  summarise_all(funs(mean))

mmplot(...)+
geom_text_repel(
    data          = labelframe,
    aes(label=binID),
    nudge_x       = 1,
    segment.size  = 0.2,
    segment.color = "grey50",
    direction     = "y",
    hjust         = 1,
    size=5
  )

library(mmgenome2)
#> Loading required package: ggplot2
mmsubset <- mmextract(mmgenome2, 
                      data.frame(cov_C13.11.25 = c(1.253, 1.298, 2.78, 3.006, 1.772),
                                 cov_C14.01.09 = c(46.774, 26.499, 15.013, 28.049, 48.58))
                      )
#> 185 scaffolds (or 2.39% of the scaffolds in mm, weighted by length) remain after 97100 of 97285 scaffolds have been filtered.
bin1 <- mmextract(mmsubset, 
                  data.frame(cov_C13.11.25 = c(1.239, 1.273, 1.732, 2.075, 1.658),
                             cov_C14.01.09 = c(30.96, 41.872, 45.587, 40.788, 31.734))
                  )
#> 54 scaffolds (or 53.19% of the scaffolds in mm, weighted by length) remain after 131 of 185 scaffolds have been filtered.
bin2 <- mmextract(mmsubset,
                  data.frame(cov_C13.11.25 = c(2.052, 2.479, 2.874, 2.527),
                             cov_C14.01.09 = c(20.203, 29.722, 25.62, 17.494))
                  )
#> 41 scaffolds (or 43.23% of the scaffolds in mm, weighted by length) remain after 144 of 185 scaffolds have been filtered.
mmsubset$bin <- NA
mmsubset$bin[which(mmsubset$scaffold %in% bin1$scaffold)] <- "bin1"
mmsubset$bin[which(mmsubset$scaffold %in% bin2$scaffold)] <- "bin2"

mmplot(mmsubset,
            x = "cov_C13.11.25",
            y = "cov_C14.01.09",
            label_bins = "bin")