Methylation data for 27,720 Illumina 450K arrays retrieved from GEO
This data accompanies the manuscript 'Integration of public DNA methylation and expression networks via eQTMs improves prediction of functional gene-gene association' by Shuang Li et al, 2021. In this manuscript, we generate a co-methylation network using 27,720 Illumina 450K arrays, which have been jointly harmonized and normalized. We use the resulting co-methylation network, and eQTMs from a cross-tissue eQTM meta-analysis to determine links between methylated sites in the genome and gene expression levels from a RNA-seq based co-regulation network. The DNA methylation dataset for the harmonized 450K arrays is available for download below.
- complete_public_450_values.dupGSMDeleted.QuantileNormalized.ProbesCentered.SamplesZTransformed.cols.txt - column descriptors
- complete_public_450_values.dupGSMDeleted.QuantileNormalized.ProbesCentered.SamplesZTransformed.npy.gz - data represented as numpy arrays
- complete_public_450_values.dupGSMDeleted.QuantileNormalized.ProbesCentered.SamplesZTransformed.rows.txt - row descriptors
- MD5 sums
- README.txt - README to convert npy.gz file to .tsv.gz file
- transform_to_tsv.py - script to convert .npy.gz to .tsv.gz file
The download size is approximately 90Gb. We note that storage on this server is likely temporary: We intend to publish this dataset on Zenodo as well.
The discovered and predicted eQTMs, the corresponding CCA components and the trained prediction models in a Zenodo repository (https://zenodo.org/deposit/4666994). We provide notebooks to facilitate use of the proposed pipeline in a GitHub repository (https://github.com/molgenis/methylationnetwork).
Citation
Li, S; 2021; Integration of public DNA methylation and expression networks via eQTMs improves prediction of functional gene-gene association
