LeuEnk.Rmd

---
title: "R Notebook"
date: "`r Sys.Date()`"
output:
  html_notebook:
    code_folding: hide
    toc: true
    toc_float: true
---

```{r libraries, results='hide'}
library(here)
library(tidyverse)
library(eisaCIM)
```

```{r general_stuff}
work_dir <- here()
data_dir <- here(work_dir, "Data", "mzML", "sir")
```

# Read all files

Get the list of mzML files.

```{r}
mzml_files <- list.files(path = data_dir,
                         pattern = ".*conv.*\\.mzML",
                         full.names = TRUE)
```

Read the raw files.

```{r}
all_raw_data <- read_files(files = mzml_files)
```

Extract all the data.

```{r}
all_data <- list()

for(a in 1:length(mzml_files)) {
  all_data[[a]] <- extract_sim_data(data = all_raw_data[, a],
                                    sim_names = c("120", "136"),
                                    sim_ids = c(1, 2))
}
```

```{r}
# create names for the data frames
df_names <- str_extract(string = mzml_files,
                        pattern = "[0-9]{1,3}[un]M_[1-3]")

names(all_data) <- df_names
```

```{r}
all_data_df <- do.call(rbind, all_data) %>% 
  rownames_to_column() %>% 
  rename(file = rowname) %>% 
  mutate(replicate = str_replace(string = file,
                                 pattern = "([0-9]{1,3}[un]M)_([1-3])\\.[0-9]*",
                                 replacement = "\\2"),
         replicate = factor(replicate, 
                            levels = c(1, 2, 3)),
         conc = str_extract(string = file,
                            pattern = "[0-9]{1,3}[un]M"),
         conc = factor(conc, 
                       levels = c("1nM", "2nM", "5nM", "10nM", "25nM", "50nM", "100nM", "250nM", "500nM", "1uM", "5uM", "10uM", "25uM", "50uM", "75uM", "100uM")),
         rep_conc = paste0(replicate, "_", conc)) %>% 
  arrange(conc)
```

Quick overview of some concentrations.

```{r fig.width=10, warning=FALSE, message=FALSE}
all_data_df %>% 
  filter(conc == "1nM" |
           conc == "5nM" |
           conc == "10nM" |
           conc == "25nM") %>% 
  ggplot() +
  geom_line(aes(x = rt,
                y = intensity,
                color = conc,
                group = rep_conc)) +
  scale_y_continuous(labels = scales::scientific) +
  facet_grid(rows = vars(conc),
             cols = vars(sim),
             scales = "free") +
  # lims(x = c(3.5, 4)) +
  theme_minimal()
```

Zoom in on leu-enk peak.

```{r fig.width=10, warning=FALSE, message=FALSE}
all_data_df %>% 
  filter(conc == "1nM" |
           conc == "5nM" |
           conc == "10nM" |
           conc == "25nM") %>% 
  ggplot() +
  geom_line(aes(x = rt,
                y = intensity,
                color = conc,
                group = rep_conc)) +
  scale_y_continuous(labels = scales::scientific) +
  facet_grid(rows = vars(conc),
             cols = vars(sim),
             scales = "free") +
  lims(x = c(3.5, 4)) +
  theme_minimal()
```

# SIM

## 25nM

```{r}
raw_data <- read_files(files = mzml_files[23])
```

Show the SIM's present.

```{r}
get_all_sim(data = raw_data)
```

There are 2 SIM's present for leu-enk.

```{r}
# define the name of the SIM traces
sim_names <- c("120", "136")
# the index of the SIM traces
sim_ids <- c(1, 2)

sim_data <- extract_sim_data(data = raw_data,
                             sim_names = sim_names,
                             sim_ids = sim_ids)
```

```{r}
plot_sims(sim_data = sim_data,
          rt_line = 3.7,
          title = "Leu-enk fragments [25 nM]") + 
  lims(x = c(0, 9))
```

```{r}
# define the noise level for each trace
noise <- c(2e6, 8e5)

# do the actual peak picking
my_peaks <- find_peaks(data = raw_data,
                       sim_ids = sim_ids,
                       sim_names = sim_names,
                       noise = noise,
                       peakwidth = c(0.05, 0.1))
```


```{r warning=FALSE, message=FALSE}
plot_sims(sim_data = sim_data,
          rt_line = 3.7,
          title = "Leu-enk fragments [25 nM]",
          peak_data = my_peaks) + 
  lims(x = c(0, 9))
```

Group the peaks over the two traces. Group the peaks of the different traces if they are elute with a difference of smaller then 5 seconds.

```{r}
my_peaks <- group_peaks(peak_list = my_peaks,
                        rt_diff = 5)
```


Clean up the peak list, only keep a peak group if it has a peak in each trace.

```{r}
my_peaks_clean <- my_peaks %>% 
  filter(num_peaks == 2)
```

Show the SIM’s in combination with the cleaned peak list.

```{r}
plot_sims(sim_data = sim_data,
          rt_line = 3.7,
          title = "Leu-enk fragments [25 nM]",
          peak_data = my_peaks_clean) +
  lims(x = c(0, 9))
```

Plot the CIM chromatogram

```{r}
plot_cim(sim_data = sim_data,
         peak_list = my_peaks_clean,
          title = "Leu-enk fragments [25 nM]",
         select_sim = "120",
         rt_line = 3.7)
```

## 10nM

```{r}
raw_data <- read_files(files = mzml_files[8])
```

Show the SIM's present.

```{r}
get_all_sim(data = raw_data)
```

There are 2 SIM's present for leu-enk.

```{r}
# define the name of the SIM traces
sim_names <- c("120", "136")
# the index of the SIM traces
sim_ids <- c(1, 2)

sim_data <- extract_sim_data(data = raw_data,
                             sim_names = sim_names,
                             sim_ids = sim_ids)
```

```{r}
plot_sims(sim_data = sim_data,
          rt_line = 3.75,
          title = "Leu-enk fragments [10 nM]") + 
  lims(x = c(0, 9))
```

```{r}
# define the noise level for each trace
noise <- c(1e6, 4e5)

# do the actual peak picking
my_peaks <- find_peaks(data = raw_data,
                       sim_ids = sim_ids,
                       sim_names = sim_names,
                       noise = noise,
                       peakwidth = c(0.05, 0.1))
```


```{r warning=FALSE, message=FALSE}
plot_sims(sim_data = sim_data,
          rt_line = 3.75,
          title = "Leu-enk fragments [10 nM]",
          peak_data = my_peaks) + 
  lims(x = c(0, 9))
```

Group the peaks over the two traces. Group the peaks of the different traces if they are elute with a difference of smaller then 5 seconds.

```{r}
my_peaks <- group_peaks(peak_list = my_peaks,
                        rt_diff = 5)
```


Clean up the peak list, only keep a peak group if it has a peak in each trace.

```{r}
my_peaks_clean <- my_peaks %>% 
  filter(num_peaks == 2)
```

Show the SIM’s in combination with the cleaned peak list.

```{r}
plot_sims(sim_data = sim_data,
          rt_line = 3.75,
          title = "Leu-enk fragments [10 nM]",
          peak_data = my_peaks_clean) +
  lims(x = c(0, 9))
```

Plot the CIM chromatogram

```{r}
plot_cim(sim_data = sim_data,
         peak_list = my_peaks_clean,
          title = "Leu-enk fragments [10 nM]",
         select_sim = "120",
         rt_line = 3.75)
```

## 5nM

```{r}
raw_data <- read_files(files = mzml_files[41])
```

Show the SIM's present.

```{r}
get_all_sim(data = raw_data)
```

There are 2 SIM's present for leu-enk.

```{r}
# define the name of the SIM traces
sim_names <- c("120", "136")
# the index of the SIM traces
sim_ids <- c(1, 2)

sim_data <- extract_sim_data(data = raw_data,
                             sim_names = sim_names,
                             sim_ids = sim_ids)
```

```{r}
plot_sims(sim_data = sim_data,
          rt_line = 3.7,
          title = "Leu-enk fragments [5 nM]") + 
  lims(x = c(0, 9))
```

```{r}
# define the noise level for each trace
noise <- c(5e5, 2e5)

# do the actual peak picking
my_peaks <- find_peaks(data = raw_data,
                       sim_ids = sim_ids,
                       sim_names = sim_names,
                       noise = noise,
                       peakwidth = c(0.05, 0.1))
```


```{r warning=FALSE, message=FALSE}
plot_sims(sim_data = sim_data,
          rt_line = 3.7,
          title = "Leu-enk fragments [5 nM]",
          peak_data = my_peaks) + 
  lims(x = c(0, 9))
```

Group the peaks over the two traces. Group the peaks of the different traces if they are elute with a difference of smaller then 5 seconds.

```{r}
my_peaks <- group_peaks(peak_list = my_peaks,
                        rt_diff = 5)
```


Clean up the peak list, only keep a peak group if it has a peak in each trace.

```{r}
my_peaks_clean <- my_peaks %>% 
  filter(num_peaks == 2)
```

Show the SIM’s in combination with the cleaned peak list.

```{r warning=FALSE, message=FALSE}
plot_sims(sim_data = sim_data,
          rt_line = 3.7,
          title = "Leu-enk fragments [5 nM]",
          peak_data = my_peaks_clean) +
  lims(x = c(0, 9))
```

Plot the CIM chromatogram

```{r warning=FALSE, message=FALSE}
plot_cim(sim_data = sim_data,
         peak_list = my_peaks_clean,
          title = "Leu-enk fragments [5 nM]",
         select_sim = "120",
         rt_line = 3.7)
```

# MRM and SIM

Combine MRM and SIM

```{r}
all_mzml_files <- list.files(path = here(work_dir, "Data", "mzML"),
                             pattern = ".*\\.mzML",
                             recursive = TRUE,
                             full.names = TRUE)
```

## 25 nM

```{r}
mrm_raw <- read_files(files = all_mzml_files[23])
sim_raw <- read_files(files = all_mzml_files[119])
```

Show the MRM's and SIM's present.

```{r}
get_all_sim(data = mrm_raw)
get_all_sim(data = sim_raw)
```

Extract the data for the MRM and SIM.

```{r}
# MRM
mrm_names <- c("556")
mrm_ids <- 2
mrm_data <- extract_sim_data(data = mrm_raw,
                             sim_names = mrm_names,
                             sim_ids = mrm_ids)


sim_names <- c("120", "136")
sim_ids <- c(1, 2)
sim_data <- extract_sim_data(data = sim_raw,
                             sim_names = sim_names,
                             sim_ids = sim_ids)

mrm_sim_data <- rbind(mrm_data, sim_data)
```

```{r warning=FALSE, message=FALSE}
plot_sims(sim_data = mrm_sim_data,
          rt_line = 3.72,
          title = "Leu-enk [25 nM]") +
  lims(x = c(0, 10))
  # lims(x = c(3, 4.5))
```

```{r}
# define the noise level for each trace
noise_mrm <- c(1e6)

# do the actual peak picking
my_peaks_mrm <- find_peaks(data = mrm_raw,
                       sim_ids = mrm_ids,
                       sim_names = mrm_names,
                       noise = noise_mrm,
                       peakwidth = c(0.05, 0.1))

# define the noise level for each trace
noise_sim <- c(2e6, 5e5)

# do the actual peak picking
my_peaks_sim <- find_peaks(data = sim_raw,
                       sim_ids = sim_ids,
                       sim_names = sim_names,
                       noise = noise_sim,
                       peakwidth = c(0.05, 0.1))

my_peaks <- rbind(my_peaks_mrm, my_peaks_sim)
```

```{r warning=FALSE, message=FALSE}
plot_sims(sim_data = mrm_sim_data,
          rt_line = 3.72,
          title = "Leu-enk [25 nM]",
          peak_data = my_peaks) + 
  lims(x = c(0, 9))
```

Group the peaks over the three traces. Group the peaks of the different traces if they are elute with a difference of smaller then 5 seconds.

```{r}
my_peaks <- group_peaks(peak_list = my_peaks,
                        rt_diff = 5)
```


Clean up the peak list, only keep a peak group if it has a peak in each trace.

```{r}
my_peaks_clean <- my_peaks %>% 
  filter(num_peaks == 3)
```

Show the SIM’s in combination with the cleaned peak list.

```{r warning=FALSE, message=FALSE}
plot_sims(sim_data = mrm_sim_data,
          rt_line = 3.72,
          title = "Leu-enk [25 nM]",
          peak_data = my_peaks_clean) +
  lims(x = c(0, 9))
```

Plot the CIM chromatogram. Created from trace 120. 

```{r warning=FALSE, message=FALSE}
plot_cim(sim_data = mrm_sim_data,
         peak_list = my_peaks_clean,
          title = "Leu-enk [25 nM]",
         select_sim = "120",
         rt_line = 3.7)
```

Plot the CIM chromatogram. Created from trace 556.

```{r warning=FALSE, message=FALSE}
plot_cim(sim_data = mrm_sim_data,
         peak_list = my_peaks_clean,
          title = "Leu-enk [25 nM]",
         select_sim = "556",
         rt_line = 3.72)
```

## 10 nM

```{r}
mrm_raw <- read_files(files = all_mzml_files[7])
sim_raw <- read_files(files = all_mzml_files[104])
```

Show the MRM's and SIM's present.

```{r}
get_all_sim(data = mrm_raw)
get_all_sim(data = sim_raw)
```

Extract the data for the MRM and SIM.

```{r}
# MRM
mrm_names <- c("556")
mrm_ids <- 2
mrm_data <- extract_sim_data(data = mrm_raw,
                             sim_names = mrm_names,
                             sim_ids = mrm_ids)


sim_names <- c("120", "136")
sim_ids <- c(1, 2)
sim_data <- extract_sim_data(data = sim_raw,
                             sim_names = sim_names,
                             sim_ids = sim_ids)

mrm_sim_data <- rbind(mrm_data, sim_data)
```

```{r warning=FALSE, message=FALSE}
plot_sims(sim_data = mrm_sim_data,
          rt_line = 3.72,
          title = "Leu-enk [10 nM]") +
  lims(x = c(0, 10))
  # lims(x = c(3, 4.5))
```

```{r}
# define the noise level for each trace
noise_mrm <- c(7.5e5)

# do the actual peak picking
my_peaks_mrm <- find_peaks(data = mrm_raw,
                       sim_ids = mrm_ids,
                       sim_names = mrm_names,
                       noise = noise_mrm,
                       peakwidth = c(0.05, 0.1))

# define the noise level for each trace
noise_sim <- c(1e6, 4e5)

# do the actual peak picking
my_peaks_sim <- find_peaks(data = sim_raw,
                       sim_ids = sim_ids,
                       sim_names = sim_names,
                       noise = noise_sim,
                       peakwidth = c(0.05, 0.1))

my_peaks <- rbind(my_peaks_mrm, my_peaks_sim)
```

```{r warning=FALSE, message=FALSE}
plot_sims(sim_data = mrm_sim_data,
          rt_line = 3.72,
          title = "Leu-enk [10 nM]",
          peak_data = my_peaks) + 
  lims(x = c(0, 9))
```

Group the peaks over the three traces. Group the peaks of the different traces if they are elute with a difference of smaller then 5 seconds.

```{r}
my_peaks <- group_peaks(peak_list = my_peaks,
                        rt_diff = 5)
```


Clean up the peak list, only keep a peak group if it has a peak in each trace.

```{r}
my_peaks_clean <- my_peaks %>% 
  filter(num_peaks == 3)
```

Show the SIM’s in combination with the cleaned peak list.

```{r warning=FALSE, message=FALSE}
plot_sims(sim_data = mrm_sim_data,
          rt_line = 3.75,
          title = "Leu-enk [10 nM]",
          peak_data = my_peaks_clean) +
  lims(x = c(0, 9))
```

Plot the CIM chromatogram. Created from trace 120. 

```{r warning=FALSE, message=FALSE}
plot_cim(sim_data = mrm_sim_data,
         peak_list = my_peaks_clean,
          title = "Leu-enk [10 nM]",
         select_sim = "120",
         rt_line = 3.7)
```

Plot the CIM chromatogram. Created from trace 556.

```{r warning=FALSE, message=FALSE}
plot_cim(sim_data = mrm_sim_data,
         peak_list = my_peaks_clean,
          title = "Leu-enk [10 nM]",
         select_sim = "556",
         rt_line = 3.72)
```

## 2 nM

```{r}
mrm_raw <- read_files(files = all_mzml_files[29])
sim_raw <- read_files(files = all_mzml_files[125])
```

Show the MRM's and SIM's present.

```{r}
get_all_sim(data = mrm_raw)
get_all_sim(data = sim_raw)
```

Extract the data for the MRM and SIM.

```{r}
# MRM
mrm_names <- c("556")
mrm_ids <- 2
mrm_data <- extract_sim_data(data = mrm_raw,
                             sim_names = mrm_names,
                             sim_ids = mrm_ids)


sim_names <- c("120", "136")
sim_ids <- c(1, 2)
sim_data <- extract_sim_data(data = sim_raw,
                             sim_names = sim_names,
                             sim_ids = sim_ids)

mrm_sim_data <- rbind(mrm_data, sim_data)
```

```{r warning=FALSE, message=FALSE}
plot_sims(sim_data = mrm_sim_data,
          rt_line = 3.72,
          title = "Leu-enk [2 nM]") +
  lims(x = c(0, 10))
  # lims(x = c(3, 4.5))
```

```{r}
# define the noise level for each trace
noise_mrm <- c(0.5e5)

# do the actual peak picking
my_peaks_mrm <- find_peaks(data = mrm_raw,
                       sim_ids = mrm_ids,
                       sim_names = mrm_names,
                       noise = noise_mrm,
                       peakwidth = c(0.05, 0.1))

# define the noise level for each trace
noise_sim <- c(4e5, 1e5)

# do the actual peak picking
my_peaks_sim <- find_peaks(data = sim_raw,
                       sim_ids = sim_ids,
                       sim_names = sim_names,
                       noise = noise_sim,
                       peakwidth = c(0.05, 0.1))

my_peaks <- rbind(my_peaks_mrm, my_peaks_sim)
```

```{r warning=FALSE, message=FALSE}
plot_sims(sim_data = mrm_sim_data,
          rt_line = 3.7,
          title = "Leu-enk [2 nM]",
          peak_data = my_peaks) + 
  lims(x = c(0, 9))
```

Group the peaks over the three traces. Group the peaks of the different traces if they are elute with a difference of smaller then 5 seconds.

```{r}
my_peaks <- group_peaks(peak_list = my_peaks,
                        rt_diff = 5)
```


Clean up the peak list, only keep a peak group if it has a peak in each trace.

```{r}
my_peaks_clean <- my_peaks %>% 
  filter(num_peaks == 3)
```

Show the SIM’s in combination with the cleaned peak list.

```{r warning=FALSE, message=FALSE}
plot_sims(sim_data = mrm_sim_data,
          rt_line = 3.7,
          title = "Leu-enk [2 nM]",
          peak_data = my_peaks_clean) +
  lims(x = c(0, 9))
```

Plot the CIM chromatogram. Created from trace 120. 

```{r warning=FALSE, message=FALSE}
plot_cim(sim_data = mrm_sim_data,
         peak_list = my_peaks_clean,
          title = "Leu-enk [2 nM]",
         select_sim = "120",
         rt_line = 3.7) 
```

Plot the CIM chromatogram. Created from trace 556 

```{r warning=FALSE, message=FALSE}
plot_cim(sim_data = mrm_sim_data,
         peak_list = my_peaks_clean,
          title = "Leu-enk [2 nM]",
         select_sim = "556",
         rt_line = 3.72) 
```

## 1 nM

```{r}
mrm_raw <- read_files(files = all_mzml_files[14])
sim_raw <- read_files(files = all_mzml_files[110])
```

Show the MRM's and SIM's present.

```{r}
get_all_sim(data = mrm_raw)
get_all_sim(data = sim_raw)
```

Extract the data for the MRM and SIM.

```{r}
# MRM
mrm_names <- c("556")
mrm_ids <- 2
mrm_data <- extract_sim_data(data = mrm_raw,
                             sim_names = mrm_names,
                             sim_ids = mrm_ids)


sim_names <- c("120", "136")
sim_ids <- c(1, 2)
sim_data <- extract_sim_data(data = sim_raw,
                             sim_names = sim_names,
                             sim_ids = sim_ids)

mrm_sim_data <- rbind(mrm_data, sim_data)
```

```{r warning=FALSE, message=FALSE}
plot_sims(sim_data = mrm_sim_data,
          rt_line = 3.75,
          title = "Leu-enk [1 nM]") +
  lims(x = c(0, 10))
  # lims(x = c(3, 4.5))
```

```{r}
# define the noise level for each trace
noise_mrm <- c(0.5e5)

# do the actual peak picking
my_peaks_mrm <- find_peaks(data = mrm_raw,
                       sim_ids = mrm_ids,
                       sim_names = mrm_names,
                       noise = noise_mrm,
                       peakwidth = c(0.05, 0.1))

# define the noise level for each trace
noise_sim <- c(3.5e5, 1.2e5)

# do the actual peak picking
my_peaks_sim <- find_peaks(data = sim_raw,
                       sim_ids = sim_ids,
                       sim_names = sim_names,
                       noise = noise_sim,
                       peakwidth = c(0.03, 0.1))

my_peaks <- rbind(my_peaks_mrm, my_peaks_sim)
```

```{r warning=FALSE, message=FALSE}
plot_sims(sim_data = mrm_sim_data,
          rt_line = 3.75,
          title = "Leu-enk [1 nM]",
          peak_data = my_peaks) + 
  lims(x = c(0, 9))
```

Group the peaks over the three traces. Group the peaks of the different traces if they are elute with a difference of smaller then 5 seconds.

```{r}
my_peaks <- group_peaks(peak_list = my_peaks,
                        rt_diff = 3)
```


Clean up the peak list, only keep a peak group if it has a peak in each trace.

```{r}
my_peaks_clean <- my_peaks %>% 
  filter(num_peaks == 3)
```

Show the SIM’s in combination with the cleaned peak list.

```{r warning=FALSE, message=FALSE}
plot_sims(sim_data = mrm_sim_data,
          rt_line = 3.75,
          title = "Leu-enk [1 nM]",
          peak_data = my_peaks_clean) +
  lims(x = c(0, 9))
```

Plot the CIM chromatogram. Created from trace 120. 

```{r warning=FALSE, message=FALSE}
plot_cim(sim_data = mrm_sim_data,
         peak_list = my_peaks_clean,
          title = "Leu-enk [1 nM]",
         select_sim = "120",
         rt_line = 3.75) 
```

Plot the CIM chromatogram. Created from trace 556 

```{r warning=FALSE, message=FALSE}
plot_cim(sim_data = mrm_sim_data,
         peak_list = my_peaks_clean,
          title = "Leu-enk [1 nM]",
         select_sim = "556",
         rt_line = 3.8) 
```


# Session info

```{r}
sessioninfo::session_info()
```