report.Rmd

---
title: "Prime Hits Report"
date: "`r Sys.Date()`"
output:
  word_document:
   reference_docx: report_style.docx
#  pdf_document:
#    latex_engine: pdflatex # Or lualatex (both have excellent Unicode support)
#    keep_tex: TRUE # Useful for debugging if issues arise
#    fig_crop: FALSE
#geometry: "margin=0.1in"  # Adjust margins if needed
# Other font options: Arial Unicode MS, FreeSerif, etc.
# You might also need to specify sansfont, monofont if used
#classoption: landscape
params:
  target: NA
  stage: NA
  run: NA
  Ch1_norm: NA
  Ch2_norm: NA
  scale_scope: NA
  col_to_penalise: NA
  equation: NA
  zero_limit: NA
  channel_flip: NA
  hit_threshold: NA
  norm_plots: NA
  run_summary: NA
  d_dens_plot: NA
  combined_plot: NA
  df_normw_plot: NA
  df_export_plot_ratio: NA
  df_export_plot_penalised: NA
  zoom_Ch1_raw: NA
  zoom_Ch2_raw: NA
  hit_tbl_tags: NA
  hit_tbl: NA
  plates_wide: NA
  
  
  
header-includes:
  - \usepackage{booktabs}
#  - \usepackage{longtable}
#  - \usepackage{array}
#  - \usepackage{multirow}
#  - \usepackage{wrapfig}
  - \usepackage{float}
  - \usepackage{colortbl}
#  - \usepackage{pdflscape}
#  - \usepackage{tabu}
#  - \usepackage{threeparttable}
#  - \usepackage[normalem]{ulem}
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
library(ggplot2)
library(patchwork)
library(tidyverse)
library(kableExtra)

library(knitr)
# Define formatting function
# Custom function to format numbers based on conditions
format_number <- function(x) {
  sapply(x, function(val) {
    if (abs(val) > 1000 || abs(val) < 0.01) {
      return(formatC(val, format = "e", digits = 2)) # Scientific notation
    } else {
      return(as.character(round(val, 2))) # Round to two decimal places
    }
  })
}

```



## Parameters used:

  
* Target: `r params$target`

* Stage: `r params$stage`

* Run: `r params$run`

* Ch1 (X-axis) normalisation: `r params$Ch1_norm`

* Ch2 (Y-axis) normalisation: `r params$Ch2_norm`

* Normalisation scope: `r params$scale_scope`

* Column to penalise: `r params$col_to_penalise`

* Hit threshold: `r params$hit_threshold`

* Equation: `r params$equation`

* Limit penalized number to max of zero: `r params$zero_limit`

* Acceptor First: `r params$channel_flip`


## Run summary 

### Normalisation center and scale and Density of d 

```{r norm_plots, echo=FALSE, fig.width=12, fig.height=4}
params$norm_plots 
```

### Run Summary Table

```{r run_summary,fig.width=12, fig.height=4, echo=FALSE}

formatted_run_summary <- select(params$run_summary,feature,median_Compound:`median_Positive Control`,mad_Compound:`mad_Positive Control`,rCV_Compound:`rCV_Positive Control`) %>%
  mutate(across(
    where(is.numeric),
    ~ format_number(.x)
  ))

# Output kable with scaling
kable(formatted_run_summary, booktabs = TRUE, caption="Run summary")# %>%
  #kable_styling(latex_options = c("striped", "scale_down", position = "H"))

# # Create a flextable from your data frame
# ft <- flextable(formatted_run_summary)
# 
# # Optional: Configure the theme to be somewhat similar to a stripped effect
# ft <- theme_vanilla(ft) 
# 
# # Autofit to adjust to the content
# ft <- autofit(ft)
# 
# # Optional: You can add features similar to striped rows using color shading
# ft <- bg(ft, i = seq(from = 1, to = nrow(formatted_run_summary), by = 2), bg = "#F0F0F0")
# 
# # (Flextable doesn't directly support caption in PDF, adjust document format accordingly)
# ft
```

### Density of d  

```{r d_dens_plot, echo=FALSE, fig.width=12, fig.height=4}
params$d_dens_plot 
```

\newpage

## Penaltry strength plots

`r params$equation`

```{r combined_plot, echo=FALSE, fig.width=12, fig.height=8.1}

params$combined_plot
```

## Heatplot of penalised values in normalised space 

```{r df_normw_plot, echo=FALSE, fig.width=12, fig.height=5}
params$df_normw_plot
```

## Heatplot of penalised and non-penalised values in raw space 

```{r plots_both_penalty, echo=FALSE, fig.width=12, fig.height=8}
df_export_plot_ratio_zoom<- params$df_export_plot_ratio+coord_cartesian(xlim=params$zoom_Ch1_raw,ylim=params$zoom_Ch2_raw)
df_export_plot_penalised_zoom <- params$df_export_plot_penalised+coord_cartesian(xlim=params$zoom_Ch1_raw,ylim=params$zoom_Ch2_raw)
df_export_plot_ratio_zoom / df_export_plot_penalised_zoom
```


##  Actives by Well Type

```{r Actives by Well Type, echo=FALSE}
# kable(params$hit_tbl, format = "latex", booktabs = TRUE, caption="Actives by Well Type") %>%
#   kable_styling(latex_options = c("striped", "scale_down", position = "H"))

kable(params$hit_tbl, caption="Actives by Well Type")                
```

##  Actives by tag

```{r Actives by Well Tag,echo=FALSE}
# kable(params$hit_tbl_tags, format = "latex", booktabs = TRUE, caption="Actives by Well Tag") %>%
#   kable_styling(latex_options = c("striped", "scale_down", position = "H"))
kable(params$hit_tbl_tags, caption="Actives by Well Tag")                           
```


## Plate Summary Table

```{r all_plates, echo=FALSE}



plates_wide <- select(params$plates_wide,feature,`Plate ID`,median_Compound:`median_Positive Control`,mad_Compound:`mad_Positive Control`,rCV_Compound:`rCV_Positive Control`,rSB,rZf)

# Create a copy of plates_wide with formatted results as character columns
formatted_plates_wide <- plates_wide %>% na.omit %>%
  mutate(`Plate ID`=as.character(`Plate ID`)) %>%
  mutate(across(
    where(is.numeric),
    ~ format_number(.x)
  ))

names(formatted_plates_wide) <- str_remove(names(formatted_plates_wide),"Control")
names(formatted_plates_wide) <- str_replace(names(formatted_plates_wide),"Compound","Cpd")
# # Output kable with scaling
# kable(formatted_plates_wide, format = "latex", booktabs = TRUE, caption="Plate Stats") %>%
#   kable_styling(latex_options = c("striped", "scale_down", position = "H"))

kable(formatted_plates_wide, caption="Plate Stats")
```