All Data
It is highly recommended that you download the dataset using a dedicated FTP tool, such as FileZilla Client .
Host address: ftp://download.big.ac.cn/ewas/datahub/EWAS_db/
Baseline Data
It is highly recommended that you download the dataset using a dedicated FTP tool, such as FileZilla Client .
Host address: ftp://download.big.ac.cn/ewas/datahub/download/
| Description | Download (.txt & .RData) | File Size |
|---|---|---|
| DNA methylation profiles of 31 organism parts | tissue_methylation.zip | 7.7 GB |
| Sample information of DNA methylation profiles of 31 organism parts | sample_tissue_methylation.zip | 62.2 KB |
| DNA methylation profiles of of 25 brain parts | brain_methylation.zip | 2.77 GB |
| Sample information of DNA methylation profiles of of 25 brain parts | sample_brain_methylation.zip | 27.2 KB |
| DNA methylation profiles 25 blood cell types | blood_methylation.zip | 4.86 GB |
| Sample information of DNA methylation profiles 25 blood cell types | sample_blood_methylation.zip | 41.8 KB |
| DNA methylation profiles of male and female in 24 tissues | sex_methylation.zip | 4.33 GB |
| Sample information of DNA methylation profiles of male and female in 24 tissues | sample_sex_methylation.zip | 38 KB |
| DNA methylation changes with age | age_methylation.zip | 11.73 GB |
| Sample information of DNA methylation changes with age | sample_age_methylation.zip | 89.3 KB |
| DNA methylation profiles of 6 ancestry categories | ancestry_category_methylation.zip | 1.96 GB |
| Sample information of DNA methylation profiles of 6 ancestry categories | sample_ancestry_category_methylation.zip | 20.9 KB |
| DNA methylation changes with BMI | bmi_methylation.zip | 3.06 GB |
| Sample information of DNA methylation changes with BMI | sample_bmi_methylation.zip | 28.4 KB |
| DNA methylation profiles of 39 cancers | cancer_methylation.zip | 16.07 GB |
| Sample information of DNA methylation profiles of 39 cancers | sample_cancer_methylation.zip | 117.3 KB |
| DNA methylation profiles of 28 diseases | disease_methylation.zip | 20.11 GB |
| Sample information of DNA methylation profiles of 28 diseases | sample_disease_methylation.zip | 154.1 KB |
To remove the batch effects and other unwanted noise, we develop Gaussian Mixture Quantile Normalization (GMQN), a reference based method that removes unwanted technical variations at signal intensity level. GMQN adjusts batch effects as well as bias associated with type II probe values in 450k and EPIC/850K studies. The principle behind this method is that the signal intensity of each channel displays a Gaussian mixture distribution. The first component is the background signal which has a mean slightly greater than 0. The second component is the signal from probes which have been hybridized to input DNA successfully. Variance of the second component is much larger than the first component because the degrees of hybridization are different among probes.
The object of GMQN is to rescale the signal intensity to make the two Gaussian component from different array have the same mean and variance. There are four steps to perform GMQN.