Input of DMPs into eFORGE can be in any of two forms: as Illumina 450k/27k probe IDs or as BED format (BED format should be zero based and the chromosome should be given as chrN, as genomic location on human genome assembly GRCh37). Genome coordinates are sufficient to identify probe IDs if these are not provided in BED format. We suggest a minimum of 20 and a maximum of 1,000 probes. If a DMP is not present on the 450k array (or the 27k array probes shared with the 450k array), it is excluded from the analysis. We added a 1-kb proximity filter in order to avoid the biases of testing groups of proximal probes in eFORGE: methylation correlation among closely located CpGs could mean we would be testing the same change more than once. Probes from input are selected at random by the filter, and any probe within 1 kb of any already selected probe is excluded. The choice of selecting 1 kb as a limit for filtering was based on previous data showing strong correlation of DNA methylation levels between CpGs fewer than 1 kb apart (Eckhardt et al., 2006 (link)).
Overlaps are retrieved from the eFORGE database for each analyzable probe in the input set. The tool records a count of total hotspot overlaps for each DNase I sample (cell) for the test probe set. eFORGE selects 1,000 matching background probe sets that contain an equal number of probes to the test probe set, matching for gene annotation and CpG island annotation as described above. Retrieval of overlaps from the database for each of the probes in each of the background probe sets then occurs. The tool records an overlap count for each background set in each DNase I sample. For each test probe set, eFORGE obtains the binomial p value for the test set overlap count. This binomial p value is calculated for the test set overlap count relative to the total number of tested probe sets. The binomial test was chosen over the hypergeometric test due to the important computational speed advantages it offers, which are further highlighted considering the high number of tests performed by eFORGE.
Overlaps are retrieved from the eFORGE database for each analyzable probe in the input set. The tool records a count of total hotspot overlaps for each DNase I sample (cell) for the test probe set. eFORGE selects 1,000 matching background probe sets that contain an equal number of probes to the test probe set, matching for gene annotation and CpG island annotation as described above. Retrieval of overlaps from the database for each of the probes in each of the background probe sets then occurs. The tool records an overlap count for each background set in each DNase I sample. For each test probe set, eFORGE obtains the binomial p value for the test set overlap count. This binomial p value is calculated for the test set overlap count relative to the total number of tested probe sets. The binomial test was chosen over the hypergeometric test due to the important computational speed advantages it offers, which are further highlighted considering the high number of tests performed by eFORGE.
Free full text: Click here
