Infinium DNA 甲基化 BeadChip 广泛用于群体规模的全基因组 DNA 甲基化分析。最近对 EPIC 版本 2 (EPICv2) 阵列中的探测内容和命名约定进行的更新使新数据与以前的 Infinium 阵列平台（例如 MmethylationEPIC (EPIC) 和 HumanMmethylation450 (HM450) BeadChip）的集成变得复杂。友好的工具，可协调不同 Infinium 平台上的探针 ID、甲基化水平和信号强度数据。它管理探针重复、缺失数据插补和特定于平台的偏差，以实现准确的数据转换。我们通过将基于 HM450 的癌症分类器应用于 EPICv2 癌症数据来验证该工具，实现了高精度。此外，我们成功地将 EPICv2 健康组织数据与传统 HM450 数据集成以进行组织身份分析，并在癌细胞中生成一致的拷贝数图谱。mLiftOver 在 R 中实现，可在 Bioconductor 包 SeSAMe（版本 1.21.13）中使用：https://bioconductor .org/packages/release/bioc/html/sesame.html。有关 EPIC 和 EPICv2 平台特定偏差和高置信度映射的分析，请访问 https://github.com/zhou-lab/InfiniumAnnotationV1/raw/main/Anno/EPICv2/EPICv2ToEPIC_conversion.tsv.gz。源代码可在 MIT 许可下在 https://github.com/zwdzwd/sesame/blob/devel/R/mLiftOver.R 上获取。补充数据可在 Bioinformatics online 上获取。© 作者 2024。出版者牛津大学出版社。

Infinium DNA methylation BeadChips are widely used for genome-wide DNA methylation profiling at the population scale. Recent updates to probe content and naming conventions in the EPIC version 2 (EPICv2) arrays have complicated integrating new data with previous Infinium array platforms, such as the MethylationEPIC (EPIC) and the HumanMethylation450 (HM450) BeadChip.We present mLiftOver, a user-friendly tool that harmonizes probe ID, methylation level, and signal intensity data across different Infinium platforms. It manages probe replicates, missing data imputation, and platform-specific bias for accurate data conversion. We validated the tool by applying HM450-based cancer classifiers to EPICv2 cancer data, achieving high accuracy. Additionally, we successfully integrated EPICv2 healthy tissue data with legacy HM450 data for tissue identity analysis and produced consistent copy number profiles in cancer cells.mLiftOver is implemented R and available in the Bioconductor package SeSAMe (version 1.21.13+): https://bioconductor.org/packages/release/bioc/html/sesame.html. Analysis of EPIC and EPICv2 platform-specific bias and high-confidence mapping is available at https://github.com/zhou-lab/InfiniumAnnotationV1/raw/main/Anno/EPICv2/EPICv2ToEPIC_conversion.tsv.gz. The source code is available at https://github.com/zwdzwd/sesame/blob/devel/R/mLiftOver.R under the MIT license.Supplementary data are available at Bioinformatics online.© The Author(s) 2024. Published by Oxford University Press.