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

Pan Du; Xiao Zhang; Chiang Ching Huang; Nadereh Jafari; Warren A. Kibbe; Lifang Hou; Simon M. Lin

doi:10.1186/1471-2105-11-587

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

Pan Du^*, Xiao Zhang, Chiang Ching Huang, Nadereh Jafari, Warren A. Kibbe, Lifang Hou, Simon M. Lin

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

1467 Scopus citations

Abstract

Background: High-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.Results: We 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.Conclusions: The 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.

Original language	English (US)
Article number	587
Journal	BMC bioinformatics
Volume	11
DOIs	https://doi.org/10.1186/1471-2105-11-587
State	Published - Nov 30 2010

Funding

We appreciate the very constructive critique and insightful comments of the reviewers. This work was supported in part by the NIH award 1RC1ES018461-01 to LH. PD, SML and WAK acknowledge the support of P30CA060553 and UL1RR025741. We would like to thank Vivi Frangidakis for conducting the Illumina BeadChip experiments, Leming Shi for discussing the “FC-ranking” paradigm. We would also like to acknowledge other participants in the “DNA Methylation Alterations in Response to Pesticides Exposure” project meetings for their inputs and support: Hehuang Xie, Min Wang, Yue Yu and Marcelo Bento Soares.

ASJC Scopus subject areas

Structural Biology
Biochemistry
Molecular Biology
Computer Science Applications
Applied Mathematics

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10.1186/1471-2105-11-587

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@article{0a6f7daed0c2488c9929de622cf14bb2,

title = "Comparison of Beta-value and M-value methods for quantifying methylation levels by microarray analysis",

abstract = "Background: High-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.Results: We 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.Conclusions: The 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.",

author = "Pan Du and Xiao Zhang and Huang, {Chiang Ching} and Nadereh Jafari and Kibbe, {Warren A.} and Lifang Hou and Lin, {Simon M.}",

note = "Funding Information: We appreciate the very constructive critique and insightful comments of the reviewers. This work was supported in part by the NIH award 1RC1ES018461-01 to LH. PD, SML and WAK acknowledge the support of P30CA060553 and UL1RR025741. We would like to thank Vivi Frangidakis for conducting the Illumina BeadChip experiments, Leming Shi for discussing the “FC-ranking” paradigm. We would also like to acknowledge other participants in the “DNA Methylation Alterations in Response to Pesticides Exposure” project meetings for their inputs and support: Hehuang Xie, Min Wang, Yue Yu and Marcelo Bento Soares.",

year = "2010",

month = nov,

day = "30",

doi = "10.1186/1471-2105-11-587",

language = "English (US)",

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journal = "BMC bioinformatics",

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T1 - Comparison of Beta-value and M-value methods for quantifying methylation levels by microarray analysis

AU - Du, Pan

AU - Zhang, Xiao

AU - Huang, Chiang Ching

AU - Jafari, Nadereh

AU - Kibbe, Warren A.

AU - Hou, Lifang

AU - Lin, Simon M.

N1 - Funding Information: We appreciate the very constructive critique and insightful comments of the reviewers. This work was supported in part by the NIH award 1RC1ES018461-01 to LH. PD, SML and WAK acknowledge the support of P30CA060553 and UL1RR025741. We would like to thank Vivi Frangidakis for conducting the Illumina BeadChip experiments, Leming Shi for discussing the “FC-ranking” paradigm. We would also like to acknowledge other participants in the “DNA Methylation Alterations in Response to Pesticides Exposure” project meetings for their inputs and support: Hehuang Xie, Min Wang, Yue Yu and Marcelo Bento Soares.

PY - 2010/11/30

Y1 - 2010/11/30

N2 - Background: High-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.Results: We 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.Conclusions: The 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.

AB - Background: High-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.Results: We 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.Conclusions: The 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.

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JO - BMC bioinformatics

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

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