Feber Andrew, Guilhamon Paul, Lechner Matthias, Fenton Tim, Wilson Gareth A, Thirlwell Christina, Morris Tiffany J, Flanagan Adrienne M, Teschendorff Andrew E, Kelly John D, Beck Stephan
Genome Biol. 2014 Feb 3;15(2):R30. doi: 10.1186/gb-2014-15-2-r30.
The integration of genomic and epigenomic data is an increasingly popular approach for studying the complex mechanisms driving cancer development. We have developed a method for evaluating both methylation and copy number from high-density DNA methylation arrays. Comparing copy number data from Infinium HumanMethylation450 BeadChips and SNP arrays, we demonstrate that Infinium arrays detect copy number alterations with the sensitivity of SNP platforms. These results show that high-density methylation arrays provide a robust and economic platform for detecting copy number and methylation changes in a single experiment. Our method is available in the ChAMP Bioconductor package: http://www.bioconductor.org/packages/2.13/bioc/html/ChAMP.html.
整合基因组和表观基因组数据是研究驱动癌症发展的复杂机制的一种越来越流行的方法。我们已经开发出一种从高密度DNA甲基化阵列评估甲基化和拷贝数的方法。通过比较来自Infinium HumanMethylation450 BeadChips和SNP阵列的拷贝数数据,我们证明Infinium阵列检测拷贝数改变的灵敏度与SNP平台相当。这些结果表明,高密度甲基化阵列在单个实验中为检测拷贝数和甲基化变化提供了一个强大且经济的平台。我们的方法可在ChAMP Bioconductor软件包中获取:http://www.bioconductor.org/packages/2.13/bioc/html/ChAMP.html。