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

被引:1416
作者
Du, Pan [1 ,3 ]
Zhang, Xiao [2 ]
Huang, Chiang-Ching [2 ]
Jafari, Nadereh [4 ]
Kibbe, Warren A. [1 ,3 ]
Hou, Lifang [2 ,3 ]
Lin, Simon M. [1 ,3 ]
机构
[1] Northwestern Univ, Feinberg Sch Med, NUCATS, NUBIC, Chicago, IL 60611 USA
[2] Northwestern Univ, Feinberg Sch Med, Dept Prevent Med, Chicago, IL 60611 USA
[3] Northwestern Univ, Robert H Lurie Comprehens Canc Ctr, Chicago, IL 60611 USA
[4] Northwestern Univ, Feinberg Sch Med, Ctr Genet Med, Chicago, IL 60611 USA
来源
BMC BIOINFORMATICS | 2010年 / 11卷
关键词
DNA METHYLATION; HYPERMETHYLATION; PLATFORMS; REVEALS; ARRAYS;
D O I
10.1186/1471-2105-11-587
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
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.
引用
收藏
页数:9
相关论文
共 24 条
  • [1] Experimental comparison and cross-validation of the Affymetrix and Illumina gene expression analysis platforms
    Barnes, M
    Freudenberg, J
    Thompson, S
    Aronow, B
    Pavlidis, P
    [J]. NUCLEIC ACIDS RESEARCH, 2005, 33 (18) : 5914 - 5923
  • [2] Genome-wide DNA methylation analysis for diabetic nephropathy in type 1 diabetes mellitus
    Bell, Christopher G.
    Teschendorff, Andrew E.
    Rakyan, Vardhman K.
    Maxwell, Alexander P.
    Beck, Stephan
    Savage, David A.
    [J]. BMC MEDICAL GENOMICS, 2010, 3
  • [3] High-throughput DNA methylation profiling using universal bead arrays
    Bibikova, M
    Lin, ZW
    Zhou, LX
    Chudin, E
    Garcia, EW
    Wu, B
    Doucet, D
    Thomas, NJ
    Wang, YH
    Vollmer, E
    Goldmann, T
    Seifart, C
    Jiang, W
    Barker, DL
    Chee, MS
    Floros, J
    Fan, JB
    [J]. GENOME RESEARCH, 2006, 16 (03) : 383 - 393
  • [4] Bibikova Marina, 2009, V507, P149, DOI 10.1007/978-1-59745-522-0_12
  • [5] Prenatal Tobacco Smoke Exposure Affects Global and Gene-specific DNA Methylation
    Breton, Carrie V.
    Byun, Hyang-Min
    Wenten, Made
    Pan, Fei
    Yang, Allen
    Gilliland, Frank D.
    [J]. AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE, 2009, 180 (05) : 462 - 467
  • [6] Davis S, 2010, METHYLUMI HANDLE ILL
  • [7] lumi:: a pipeline for processing Illumina microarray
    Du, Pan
    Kibbe, Warren A.
    Lin, Simon M.
    [J]. BIOINFORMATICS, 2008, 24 (13) : 1547 - 1548
  • [8] Durbin B P, 2002, Bioinformatics, V18 Suppl 1, pS105
  • [9] CpG island hypermethylation and tumor suppressor genes: a booming present, a brighter future
    Esteller, M
    [J]. ONCOGENE, 2002, 21 (35) : 5427 - 5440
  • [10] EBV transformation and cell culturing destabilizes DNA methylation in human lymphoblastoid cell lines
    Grafodatskaya, D.
    Choufani, S.
    Ferreira, J. C.
    Butcher, D. T.
    Lou, Y.
    Zhao, C.
    Scherer, S. W.
    Weksberg, R.
    [J]. GENOMICS, 2010, 95 (02) : 73 - 83