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

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 stat...

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Autores principales: Du, Pan, Zhang, Xiao, Huang, Chiang-Ching, Jafari, Nadereh, Kibbe, Warren A, Hou, Lifang, Lin, Simon M
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3012676/
https://www.ncbi.nlm.nih.gov/pubmed/21118553
http://dx.doi.org/10.1186/1471-2105-11-587
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author Du, Pan
Zhang, Xiao
Huang, Chiang-Ching
Jafari, Nadereh
Kibbe, Warren A
Hou, Lifang
Lin, Simon M
author_facet Du, Pan
Zhang, Xiao
Huang, Chiang-Ching
Jafari, Nadereh
Kibbe, Warren A
Hou, Lifang
Lin, Simon M
author_sort Du, Pan
collection PubMed
description 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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spelling pubmed-30126762011-01-10 Comparison of Beta-value and M-value methods for quantifying methylation levels by microarray analysis Du, Pan Zhang, Xiao Huang, Chiang-Ching Jafari, Nadereh Kibbe, Warren A Hou, Lifang Lin, Simon M BMC Bioinformatics Research Article 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. BioMed Central 2010-11-30 /pmc/articles/PMC3012676/ /pubmed/21118553 http://dx.doi.org/10.1186/1471-2105-11-587 Text en Copyright ©2010 Du et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<url>http://creativecommons.org/licenses/by/2.0</url>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Du, Pan
Zhang, Xiao
Huang, Chiang-Ching
Jafari, Nadereh
Kibbe, Warren A
Hou, Lifang
Lin, Simon M
Comparison of Beta-value and M-value methods for quantifying methylation levels by microarray analysis
title Comparison of Beta-value and M-value methods for quantifying methylation levels by microarray analysis
title_full Comparison of Beta-value and M-value methods for quantifying methylation levels by microarray analysis
title_fullStr Comparison of Beta-value and M-value methods for quantifying methylation levels by microarray analysis
title_full_unstemmed Comparison of Beta-value and M-value methods for quantifying methylation levels by microarray analysis
title_short Comparison of Beta-value and M-value methods for quantifying methylation levels by microarray analysis
title_sort comparison of beta-value and m-value methods for quantifying methylation levels by microarray analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3012676/
https://www.ncbi.nlm.nih.gov/pubmed/21118553
http://dx.doi.org/10.1186/1471-2105-11-587
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