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CPC+AC0-Gene DNA Methylation Data from Illumina 450k

ABSTRACT: DNA methylation profile for the samples from 143 prostate cancer patients are provided.

ORGANISM(S): Homo sapiens

PROVIDER: GSE55479 | GEO | 2015/12/31

SECONDARY ACCESSION(S): PRJNA242638

REPOSITORIES: GEO

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CPC+AC0-Gene DNA Methylation Data from Illumina 450k

Project description:DNA methylation profile for the samples from 143 prostate cancer patients are provided. DNA methylation profiling of 143 prostate cancer patients. *** Clinical data will be provided when the data are open to the public.

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Project description:Abstract The proper identification of differentially methylated CpGs is central in most epigenetic studies. The Illumina Human Methylation 450k BeadChip is widely used to quantify DNA methylation, nevertheless the design of an appropriate analysis pipeline faces severe challenges due to the convolution of biological and technical variability and the presence of a signal bias between Infinium I and II probe design types. Despite recent attempts to investigate how to analyze DNA methylation data with such an array design, it has not been possible to perform a comprehensive comparison between different bioinformatics pipelines due to the lack of appropriate datasets having both large sample size and sufficient number of technical replicates. Here we perform such a comparative analysis, targeting the problems of reducing the technical variability, eliminating the probe design bias and reducing the batch effect by exploiting two unpublished datasets, which included technical replicates and were profiled for DNA methylation either on peripheral blood, monocytes or muscle biopsies. The blood samples included individuals with Multiple Sclerosis (MS). We evaluated the performance of different analysis pipelines and demonstrated that a) it is critical to correct for the probe design type, since the amplitude of the measured methylation change depends on the underlying chemistry; b) the effect of different normalization schemes is mixed, and the most effective method in our hands were quantile normalization and Beta Mixture Quantile dilation (BMIQ); c) it is beneficial to correct for batch effects. In conclusion, our comparative analysis using a comprehensive dataset suggests an efficient pipeline for proper identification of differentially methylated CpGs using the Illumina 450k arrays.

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