---
title: "Generate QC Report"
output: rmarkdown::html_vignette
vignette: >
%\VignetteIndexEntry{Generate QC Report}
%\VignetteEngine{knitr::rmarkdown}
%\VignetteEncoding{UTF-8}
---
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
```
## Import example metabolomics data
```{r render}
library(metaboprep)
# import data directly as a Metaboprep object
mydata <- read_metabolon(system.file("extdata", "metabolon_v1.1_example.xlsx", package = "metaboprep"),
sheet="OrigScale",
return_Metaboprep = TRUE)
```
## Identify the Xenobiotics to exclude from the QC steps
```{r xeno_identification}
xenos <- mydata@features[mydata@features$pathway == "xenobiotic", "feature_id"]
## how many xenobiotics identified
length(xenos)
```
## QC the example Metabolon data
```{r qc}
mydata <- mydata |>
quality_control(source_layer = "input",
sample_missingness = 0.2,
feature_missingness = 0.2,
total_peak_area_sd = 5,
outlier_udist = 5,
outlier_treatment = "leave_be",
winsorize_quantile = 1.0,
tree_cut_height = 0.5,
pc_outlier_sd = 5,
feature_selection = "least_missingness",
features_exclude_but_keep = xenos
)
```
## Generate the metaboprep report
```{r}
# render report
generate_report(mydata,
project = "myproject",
output_dir = getwd(),
output_filename = NULL,
format = "html",
template = "qc_report")
```
```{r, echo=FALSE}
file.copy(file.path(getwd(), "myproject_metaboprep_qc_report.html"),
file.path(getwd(), "../docs/articles/myproject_metaboprep_qc_report.html"), overwrite = TRUE)
```
```{r, echo=FALSE, results="asis"}
cat('
')
```