Comparison of Beta-value and M-value methods for quantifying methylation levels by microarray analysis

By Pan Du, Xiao Zhang, Chiang-Ching Huang, N. Jafari, Warren A. Kibbe, Lifang Hou, Simon M. Lin. BMC Bioinformatics, 2010

1,953 citations recorded by the source corpus.

BackgroundHigh-throughput profiling of DNA methylation status of CpG islands is crucial to understand the epigenetic regulation of genes. The microarray-based Infinium methylation assay by Illumina is one platform for low-cost high-throughput methylation profiling. Both Beta-value and M-value statistics have been used as metrics to measure methylation levels. However, there are no detailed studies of their relations and their strengths and limitations.ResultsWe demonstrate that the relationship between the Beta-value and M-value methods is a Logit transformation, and show that the Beta-value method has severe heteroscedasticity for highly methylated or unmethylated CpG sites. In order to evaluate the performance of the Beta-value and M-value methods for identifying differentially methylated CpG sites, we designed a methylation titration experiment. The evaluation results show that the M-value method provides much better performance in terms of Detection Rate (DR) and True Positive Rate (TPR) for both highly methylated and unmethylated CpG sites. Imposing a minimum threshold of difference can improve the performance of the M-value method but not the Beta-value method. We also provide guidance for how to select the threshold of methylation differences.ConclusionsThe Beta-value has a more intuitive biological interpretation, but the M-value is more statistically valid for the differential analysis of methylation levels. Therefore, we recommend using the M-value method for conducting differential methylation analysis and including the Beta-value statistics when reporting the results to investigators.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/f1bcbe5845406cf32742e8d2219498c23337f9a5

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Citations in the corpus

Comprehensive molecular characterization of gastric adenocarcinoma (2014, neutral): “32 (15) PTPRD (1) CDKN2A (1) PTEN (4) 10q22.”
Low-level processing of Illumina Infinium DNA Methylation BeadArrays (2013, neutral): “Beta)) with unrestricted boundaries (12).”
Tobacco Smoking Leads to Extensive Genome-Wide Changes in DNA Methylation (2013, neutral): “unmethylated probe [51].”
A data-driven approach to preprocessing Illumina 450K methylation array data (2013, background): “An alternative index not bounded by 0 and 1 is M = log2((M + α)/(U + α)), which is essentially equivalent to a logit transformation of β [4].”
Analysing and interpreting DNA methylation data (2012, methodology): “Several more advanced methods have been described that aim to improve DMR detection using mixture models 90 , Shannon entropy 91 , logistic M values 49 , feature selec‑ tion 92 , stratification of t tests 93 , aggregation of genomic regions by type 94 , statistical correction for copy‑number…”
SeSAMe: reducing artifactual detection of DNA methylation by Infinium BeadChips in genomic deletions (2018, methodology): “We also observed a reduction in the within-institute variation of the DNA methylation M value (50) with SeSAMe preprocessing compared to the TCGA Legacy dataset, particularly for the Type II probes (Supplementary Figure S18).”
A Six Months Exercise Intervention Influences the Genome-wide DNA Methylation Pattern in Human Adipose Tissue (2013, neutral): “b-values were converted to Mvalues (M = log(2)(b/(1-b))), a more statistically valid method for conducting differential methylation analysis [58].”
Differential DNA Methylation in Purified Human Blood Cells: Implications for Cell Lineage and Studies on Disease Susceptibility (2012, methodology): “The M-value is calculated as the log2 ratio of the intensities of methylated probe versus unmethylated probe and describes a measurement of how much more a probe is methylated compared to unmethylated [46].”
SWAN: Subset-quantile Within Array Normalization for Illumina Infinium HumanMethylation450 BeadChips (2012, neutral): “[35].”