bca_assay_report.Rmd

---
title: "BCA assay report"
date: "`r format(Sys.time(), '%d/%m/%Y')`"
output: 
  html_document:
    theme: flatly
    css: style.css
params:
  data:
    label: "Upload data file (.xlsx):"
    input: file
    value: NULL
  anno:
    label: "Upload annotation file (.xlsx):"
    input: file
    value: NULL
  assay:
    label: "Type of assay:"
    input: select
    value: prot
    choices: [prot, pep]
  bc:
    label: "Position of BC:"
    input: select
    value: A1
    choices: [A1, B2, B3, H5, H6]
    multiple: TRUE
  bs:
    label: "Position of BS:"
    input: select
    value: 'B1'
    choices: [A1, B2, B3, H3, H4]
    multiple: TRUE
  dil:
    label: "Dilution:"
    input: numeric
    value: 5
---

---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = FALSE,
                      warning = FALSE,
                      message = FALSE,
                      fig.align = "center")
```

```{r}
# Load libraries
library(readxl)
library(dplyr)
library(ggplot2)
library(ggpmisc)
```

```{r}
# Load data
df <- read_excel(params$data,
                 range = "A24:M32") %>% 
  janitor::clean_names() %>% 
  rename(pos_row = x)

meta <- read_excel(params$anno) %>% 
  mutate(pos_col = paste0('x', pos_col))


# Choose concentrations depending on assay

concs <- switch(params$assay,
                "prot" = c(2, 1.5, 1, 0.75, 0.5, 0.25, 0.125, 0.025),
                "pep" = c(1, 0.5, 0.25, 0.125, 0.0625, 0.03125, 0.015625, 0))

```

```{r}
# Handle BC and BS
# BC
bc_pos <- params$bc

bc_list <- list()

for (i in 1:length(bc_pos)){
  
  foo <- unlist(strsplit(bc_pos[i], ""))
  
  foo_mod <- ifelse(grepl("[0-9]", foo), paste0('x', foo), foo)
  
  bc_list[[i]] <- df %>% 
    select(pos_row, any_of(foo_mod[2])) %>% 
    filter(pos_row %in% foo_mod[1]) %>% 
    pull(any_of(foo_mod[2]))
  
}

bc <- mean(unlist(bc_list))


# BS

bs_pos <- params$bs

bs_list <- list()

for (i in 1:length(bs_pos)){
  
  foo <- unlist(strsplit(bs_pos[i], ""))
  
  foo_mod <- ifelse(grepl("[0-9]", foo), paste0('x', foo), foo)
  
  bs_list[[i]] <- df %>% 
    select(pos_row, any_of(foo_mod[2])) %>% 
    filter(pos_row %in% foo_mod[1]) %>% 
    pull(any_of(foo_mod[2]))
  
}

bs <- mean(unlist(bs_list))
```

The following options were selected:

* Type of assay: **`r params$assay`**
* BC cells: **`r params$bc`** – with mean of `r round(bc, 3)`
* BS cells: **`r params$bs`** – with mean of `r round(bs, 3)`
* Dilution: **`r params$dil`** (note: if no dilution was performed, insert 1)

---

<br>

The standard curve dataset is the following:

```{r}
# Calculate first the dataset for standard curve
df_od <- df %>%
  rowwise() %>%
  summarise(od = mean(c(x1, x2))) %>%
  mutate(conc = concs,
         blanked_od = od - bc, 
         blanked_od = case_when(blanked_od < 0 ~ 0,
                                .default = blanked_od)) %>% 
  relocate(conc, .before = 1)

df_od %>% 
  mutate(across(where(is.numeric), ~ round(., 3))) %>% 
  kableExtra::kbl() %>%
  kableExtra::kable_paper("hover", full_width = F)
```

<br>

Which yields the following plot and equation:

<br>

```{r fig.align='center', fig.height=4, fig.width=6.5}
# Calculate standard curve
coefs <- lm(blanked_od ~ conc, data = df_od)$coefficients

# Plot
df_od %>%
  ggplot(aes(conc, blanked_od)) +
  stat_poly_line(se = F,
                 linetype = 3) +
  stat_poly_eq(use_label(c("eq", "R2"))) +
  geom_point() +
  theme_bw() +
  labs(x = "Concentration (ug/uL)",
       y = "Blanked OD")
```

<br>

Lastly, each of the steps to calculate the concentration of the samples of interest is depicted in the table below:

<br>

```{r}
# Calculate final sample concentrations
df %>%
  tidyr::pivot_longer(!pos_row,
                      names_to = "pos_col",
                      values_to = "od") %>%
  right_join(meta, by = c("pos_col", "pos_row")) %>%
  arrange(pos_col, pos_row) %>%
  select(sample, od) %>%
  mutate(blanked_od = od - bs,
         conc_dil = (blanked_od - coefs[1]) / coefs[2],
         prot_conc_stock = conc_dil * params$dil,
         in_100_ul = prot_conc_stock * 100) %>% 
  mutate(across(where(is.numeric), ~ round(., 2))) %>% 
  kableExtra::kbl() %>%
  kableExtra::kable_paper("hover", full_width = F)
```

---

<div class="autor-pie">
  Prado Lab - Patricia MB (2025)
</div>