omiprep
Metabolomics & proteomics data preparation and quality control pipeline for R
Overview
omiprep supports the full data-preparation workflow for untargeted and targeted omics data:
-
Import raw data from Metabolon, Nightingale Health, Olink, and SomaLogic platforms (Excel / flat-text)
-
Summarise sample- and feature-level statistics
-
Filter using a standard QC pipeline with user-defined thresholds
-
Report results as an interactive HTML or PDF document
- Export cleaned data for downstream analysis
Installation
# install.packages("pak")
pak::pak("MRCIEU/omiprep")Quick start
library(omiprep)
# 1. Read data
mydata <- read_metabolon(
system.file("extdata", "metabolon_v1.1_example.xlsx", package = "omiprep"),
sheet = "OrigScale",
return_Omiprep = TRUE
)
# 2. Run QC pipeline
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"
)
# 3. Summarise
summary(mydata)
# 4. Generate HTML report
generate_report(mydata, output_dir = ".")Articles
Importing Data
Metabolon
Import untargeted metabolomics data from Metabolon Excel sheets.
Nightingale Health
Import NMR-based metabolomic data from Nightingale Health.
Olink
Import proximity extension assay proteomic data from Olink.
SomaLogic
Import aptamer-based proteomic data from SomaLogic SomaScan.
Summaries & QC
Sample Summary
Compute per-sample statistics: missingness, total peak area, and PCA-based outlier detection.
Feature Summary
Compute per-feature statistics: missingness, variance, and independent feature trees.
QC Pipeline
Run the full quality control pipeline with configurable thresholds for missingness, outliers, and more.
Reports & Export
Generate HTML / PDF Report
Produce a fully annotated, interactive QC report in HTML or PDF format.
Export Data
Export processed data and summary tables to Excel or tab-delimited flat files.
Batch Normalisation
Correct for run-order and batch effects using quantile or rank-based normalisation.