Package: omiprep 1.0.0

Import example metabolomics data | Identify the Xenobiotics to exclude from the QC steps | QC the example Metabolon data | Generate the Omiprep report

Create Omiprep object | Run batch normalisation | Accessing data | Raw input data | Batch normalised data | Now any quality control step should be run on the "batch_normalised" layer. | QC data | Quick view of omiprep object | data array layers | omiprep summary

Create Omiprep object | Summary of Omiprep object | Run standard quality control | Feature Summary | View feature summary from the QC pipeline | Manually run feature summary | Table of feature summary | Run feature summary on subset | Table of feature summary for subset | Additional feature_summary() attributes | hierarchical cluster dendrogram | Run sample & feature summaries together | Table of feature summary from summarise() function

Import Metabolon data | Quick look at data structure of the imported data | Create Omiprep object | Quick summary of the Omiprep object | Identify the Xenobiotics to exclude from the QC steps | QC Metabolon | Quick summary of the Omiprep object following QC

Identify the Xenobiotics to exclude from the QC steps | Run the quality control pipeline | View a summary of the Omiprep object

Create Omiprep object | Summary of Omiprep object | Run standard quality control | Sample Summary | View sample summary from the QC pipeline | Manually run sample summary | Table of sample summary | Run sample summary on subset | Table of sample summary on subset | Principal Componet Analysis | View PCs from the QC pipeline | Manually run PCA analysis | Table of PCA analysis results | PCA plot | Additional pc_and_outliers() attributes | Run sample & feature summaries together

Setup | load the omiprep library | Read in the data and make a Omiprep object | Run the quality control | Export Omiprep | Export to Comets format | Export to Metaboanalyst format

Import Nightingale data directly into a Omiprep object | Quick look at data structure of the imported data | QC Nightingale | Quick summary of the Omiprep object following QC

Import Olink data | Quick look to identify the types of data imported | Create Omiprep object | Quick summary of the Omiprep object | QC Olink data | Quick summary of the Omiprep object following QC

Import SomaLogic data | Quick look to identify the types of data imported | Create Omiprep object | Quick summary of the Omiprep object | QC Olink data | Quick summary of the Omiprep object following QC

Upper limit of quantification (skewness) | 1) Simulate Data (1000 Samples x 500 Features) | 2) What skewness means (per feature) | What the threshold means | 3) Apply a skewness filtering rule | 4) Post-filtering impact on distributions | 4a) Feature-skewness distribution before vs after filtering | 4b) Feature retention by simulated type | 4c) Skewness profiles by feature type (pre vs post)