scat_report.Rmd

---
title: "Olink Scatter Plots"
output: html_document

params:
  rp_upload_data: NA
  rp_bridging_str: NA
  rp_combined_data: NA
  rp_combined_meta: NA
  rp_choice_a1: NA #x var
  rp_choice_a2: NA # color 
  rp_batch_plot_scatter: NA
---

```{r eval = FALSE, echo = FALSE}
# For PDF output, change the header to have "output: pdf_document".
#
# Note that due to an issue in rmarkdown, the default value of a parameter in
# the header cannot be `NULL`, so I used a default of `NA` for the default value
# of `n`.
library(dplyr)
library(DT)
```


## Summary of plate level information.


```{r, echo=F, message=F, warning=F}
DT::datatable(
      data.frame(software_version = sapply(params$rp_upload_data, function(x) x@metadata$software_version) %>% unlist(),
                 filename = sapply(params$rp_upload_data, function(x) x$file_name[1]) %>% unlist(),
                 panel = sapply(params$rp_upload_data, function(x) x@metadata$panel)%>% unlist(),
                 total_samples = sapply(params$rp_upload_data, function(x) ncol(x)) %>% unlist(),
                 total_analyte = sapply(params$rp_upload_data, function(x) nrow(x)) %>% unlist()),
      rownames = NULL,
      options = list(scrollX = TRUE))
```
 
### Reference sample identifier: `r paste(strsplit(params$rp_bridging_str, split = ","), collapse = ",")`

```{r, echo=F, message=F, warning=F}
# needs sample_id, Plate.ID, in metafile and "lot" only appear once in column names

lapply(strsplit(params$rp_bridging_str, split = ",")%>%unlist(), function(x){
      bdg_ls <- pull_bdg(params$rp_upload_data, pattern = x)
      data.frame(filename = names(bdg_ls),
                 identifier = x,
                 total_samples = sapply(bdg_ls, function(x) ncol(x)) %>% unlist(),
                 total_analyte = sapply(bdg_ls, function(x) paste(x$Assay, collapse = ",")) %>% unlist())
    })%>%
      do.call(what = "rbind")%>%
      DT::datatable(rownames = NULL,
      options = list(scrollX = TRUE))

```

### Plots

**Yellow dots indicate LOD**    


```{r, echo=F, message=F, warning=F, out.width= "100%"}
lod_df <- data.frame(params$rp_combined_data@elementMetadata@listData)

if(sum(grep("(LOD_)", colnames(lod_df))) == 0){
      lod_df <- cbind.data.frame(Analyt = lod_df[, 1],
                      LOD = lod_df[ ,grep("(LOD)", colnames(lod_df))]%>%as.numeric())
    }else{
      lod_df <- cbind.data.frame(Analyt = lod_df[, 1], 
                      lapply(grep("(LOD_)", colnames(lod_df)), function(x){
                        lod_df[ ,x]%>%as.numeric()
                      })%>% do.call(what = "cbind")%>%
                        data.frame()%>%
                        set_colnames(value = colnames(lod_df)[grep("(LOD_)", colnames(lod_df))]))%>%
        gather(-Analyt, key = "Plate.ID", value = "LOD")%>%
        mutate(Plate.ID = gsub("LOD_", "", Plate.ID))
    }


if(is.null(params$rp_batch_plot_scatter) | (length(params$rp_batch_plot_scatter) == 0)){
  query <- rownames(params$rp_combined_data)
}else if(params$rp_batch_plot_scatter == ""){
  query <- rownames(params$rp_combined_data)
}else{
  query <- params$rp_batch_plot_scatter
}

plot.ls <- lapply(query, function(x){
  p <- data.frame(params$rp_combined_meta,
             NPX = params$rp_combined_data@assays@data$npx[rownames(params$rp_combined_data) == x , ]
             )%>%
    left_join(
      data.frame(Plate.ID = unique(params$rp_combined_meta$Plate.ID))%>%
          merge.data.frame(lod_df)%>%
          filter(Analyt == x)%>%
          dplyr::select(-Analyt),
          by = "Plate.ID"
    )%>%
    mutate(Plate.ID = trim_string_bycommon(Plate.ID, split = "_"),
           Plate.ID = substr(Plate.ID, start = 1, stop = 10))%>%
    filter(!grepl("^(NC|IPC)", sample_id))%>%
  ggplot()+
  #geom_boxplot(aes_string(params$rp_choice_a1, "NPX",fill = params$rp_choice_a2), 
  #            alpha = 0.7)+
  geom_point(position = position_jitterdodge(jitter.width = 0.1), shape = 21, 
             aes_string(params$rp_choice_a1, "NPX", color = params$rp_choice_a2))+
  geom_point(data = .%>%
               dplyr::select(LOD, params$rp_choice_a1)%>%
               distinct()%>%
               data.frame(),
             aes_string(params$rp_choice_a1, "LOD"), 
             shape = 13, color = "yellow")+
  labs(title = x)+
  theme_bw(base_size = 8)
  if(length(unique(params$rp_combined_meta[ ,params$rp_choice_a2])) > 15){
    p+theme(axis.text.x = element_text(angle = 90, hjust = 1),
            legend.position="none")
  }else{
    p+theme(axis.text.x = element_text(angle = 90, hjust = 1),
            legend.position="bottom", legend.box="vertical", legend.margin=margin())
  }
})

per_panel <- 6
n_panel <- ceiling(length(plot.ls)/per_panel)

for (i in 1 : n_panel) {
  print(
    wrap_plots(plot.ls[(1 + (i-1) * per_panel) : min(length(plot.ls), (per_panel + (i-1) * per_panel))],
               ncol = 3, nrow = 2, byrow = T, guides = "collect")& theme(legend.position = 'bottom')
  )
}
```