super_meta_plot.Rmd

---
title: "Untitled"
author: "JR"
date: "4/28/2023"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```

```{R}
# filter to super binders
peak_occurrence_df <- peak_occurrence_df %>%
  mutate(superbinders = peak_occurrence_df$number_of_dbp > 200)


# setting col of superbinders
peak_occurrence_df <- peak_occurrence_df %>%
  mutate(superbinder2 = ifelse(peak_occurrence_df$superbinders ==T, "Superbinder", "notsuperbinder"))

# superbinder promoters
super_proms <- subset(peak_occurrence_df, superbinder2 == "Superbinder")
super_proms <- dplyr::select(super_proms, "gene_id")


# non super binder proms
non_super_proms <- subset(peak_occurrence_df, superbinder2 == "notsuperbinder")
non_super_proms  <- dplyr::select(non_super_proms, "gene_id")


# subet mRNA and lncRNA promoters by super binders
super_gr <- lncrna_mrna_promoters[lncrna_mrna_promoters$gene_id %in% super_proms$gene_id]
non_super_gr <- lncrna_mrna_promoters[lncrna_mrna_promoters$gene_id %in% non_super_proms$gene_id]



# setting up superbinders metaplot_Df

superbinder_metaplot_df <- data.frame(x = integer(), dens = numeric(), dbp = character())

i=1
# for loop to populate super binder _metaplot
for(i in 1:length(filtered_consensus_list)) {
 print(names(filtered_consensus_list)[[i]])
  tmp_df <- profile_tss(filtered_consensus_list[[i]], lncrna_mrna_promoters = super_gr)
  tmp_df$dbp <- names(filtered_consensus_list)[[i]]
  superbinder_metaplot_df <- bind_rows(superbinder_metaplot_df, tmp_df)
  
}

# non super binder meta_df

non_superbinder_metaplot_df <- data.frame(x = integer(), dens = numeric(), dbp = character())

i= 1
# for loop to populate mRNA_metaplot
for(i in 1:length(filtered_consensus_list)) {
 print(names(filtered_consensus_list)[[i]])
  tmp_df <- profile_tss(filtered_consensus_list[[i]], lncrna_mrna_promoters = non_super_gr)
  tmp_df$dbp <- names(filtered_consensus_list)[[i]]
  non_superbinder_metaplot_df <- bind_rows(non_superbinder_metaplot_df, tmp_df)
}





# now adding the information of gene type
non_superbinder_metaplot_df$gene_type <- "non_super_binder"
superbinder_metaplot_df$gene_type <- "superbinder"
combined_super_binder_metaplot_profile <- bind_rows(non_superbinder_metaplot_df, superbinder_metaplot_df)

ggplot(combined_super_binder_metaplot_profile, 
       aes(x = x, y = dens, color = gene_type )) +
  geom_vline(xintercept = 0, lty = 2) + 
  geom_line(size = 1.5) + 
  facet_wrap(dbp ~ ., scales = "free_y") +
  ggtitle("Promoter Metaplot") + 
  scale_x_continuous(breaks = c(-1000, 0, 1000),
                     labels = c("-1kb", "TSS", "+1kb"),
                     name = "") + 
  ylab("Peak frequency") +
 scale_color_manual(values = c("#424242","#a8404c"))




```