Technical and biological sources of unreliability of Infinium probes on Illumina methylation microarrays.

Nazarenko, T.; Vavourakis, CD.; Jones, A.; Evans, I.; Schreiberhuber, L.; Kastner, C.; Ishaq-Parveen, I.; Redl, E.; Watson, AW.; Brandt, K.; Carter, C.; Zaikin, A.; Herzog, CMS.; Widschwendter, M.

Technical and biological sources of unreliability of Infinium probes on Illumina methylation microarrays.

All Authors

Nazarenko, T.

Vavourakis, CD.

Jones, A.

Evans, I.

Schreiberhuber, L.

Kastner, C.

Ishaq-Parveen, I.

Redl, E.

Watson, AW.

Brandt, K.

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LTHT Author

Carter, Clive

LTHT Department

Pathology
Transplant Immunology

Non Medic

Clinical Scientist

Publication Date

2024

Item Type

Journal Article

Abstract

The Illumina Methylation array platform has facilitated countless epigenetic studies on DNA methylation (DNAme) in health and disease, yet relatively few studies have so studied its reliability, i.e., the consistency of repeated measures. Here we investigate the reliability of both type I and type II Infinium probes. We propose a method for excluding unreliable probes based on dynamic thresholds for mean intensity (MI) and 'unreliability', estimated by probe-level simulation of the influence of technical noise on methylation beta values using the background intensities of negative control probes. We validate our method in several datasets, including newly generated Illumina MethylationEPIC BeadChip v1.0 data from paired whole blood samples taken six weeks apart and technical replicates spanning multiple sample types. Our analysis revealed that specifically probes with low MI exhibit higher beta value variability between repeated samples. MI was associated with the number of C-bases in the respective probe sequence and correlated negatively with unreliability scores. The unreliability scores were substantiated through validation in a new EPIC v1.0 (blood and cervix) and a publicly available 450k (blood) dataset, as they effectively captured the variability observed in beta values between technical replicates. Finally, despite promising higher robustness, the newer version v2.0 of the MethylationEPIC BeadChip retained a substantial number of probes with poor unreliability scores. To enhance current pre-processing pipelines, we developed an R package to calculate MI and unreliability scores and provide guidance on establishing optimal dynamic score thresholds for a given dataset.