---
title: "Import Nightingale Metabolomic Data"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{Import Nightingale Metabolomic Data}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
```


## Import Nightingale data directly into a Omiprep object

Read in the Nightingale Health data using the `read_nightingale` function. Here we will read in the example data provided with the package, and convert it directly into a Omiprep S7 object.


```{r setup}
library(omiprep)

# example file
filepath <- system.file("extdata", "nightingale_v1_example.xlsx", package = "omiprep")

# import
mydata <- read_nightingale(filepath, return_Omiprep = TRUE)

```


## Quick look at data structure of the imported data

```{r data_str}
str(mydata)
```


## QC Nightingale

Perform the QC steps using the `quality_control` function.

```{r qc}
mydata <- mydata |>
  quality_control(source_layer        = "input", 
                  sample_missingness  = 0.2, 
                  feature_missingness = 0.2, 
                  total_sum_abundance_sd  = 5, 
                  outlier_udist       = 5, 
                  outlier_treatment   = "leave_be", 
                  winsorize_quantile  = 1.0, 
                  tree_cut_height     = 0.5, 
                  pc_outlier_sd       = 5, 
                  feature_selection   = "max_var_exp",
                  features_exclude_but_keep = NULL,
                  cores               = 1
                  )
```


## Quick summary of the Omiprep object following QC

```{r summary_after_qc}
summary(mydata)
```