epic-methylation-workflow

Project-specific workflow for EPIC methylaytion analysis included in the publication LINK.

Methodology description

Array data and quality control

All analysis was performed in R [1] (version 3.6.3). R functions are referenced in the following format packageName::functionName().

Methylation data was generated using Infinium methylation EPIC array. The samples included in this study were a subset of a larger cohort of 96 sample, processed collectively. EPIC methylation array IDAT files for all 96 samples were jointly loaded using the minfi package (version 1.32.0) [2]. Both sample quality and probe position quality was assessed using the minifi::detectionP() function and samples or positions with estimated p-values equal to or greater than 0.05 were excluded. The full array of 96 samples were normalised collectively using the minfi::preprocessFunnorm() method to regress out known variability detected in the control probes. Probes overlapping with SNP positions (MAF >= 0.05) were excluded using the minfi::dropLociWithSnps() function. Probes on non-autosomal chromosomes were also exlcuded as they were not considered necessary for the analysis and may have led to unintended stratification of samples. Known cross-reactive probes were excluded by probe name using the list generated by Pidsley et al. [3]. After sample and probe exclusion, a subset of samples corresponding to the PCC/PGL samples described in the publication were extracted for analysis.

Methylation comparisons

Probe beta values were calculated using the minfi::getBeta() function which extracts beta values as Beta = Meth / (Meth + Unmeth + offset), where offset is utilised to avoid division by small numerical values. Mean beta values for each sample were then computed across all probes included in a given method (full, top 20% variance etc.) and compared between wild-type and mutant PCC/PPGL samples using a Mann-whitney U test (stats::wilcox.test() function).

Gene loci and promotor CpG island data for KDM4A, KDM4B, and KDM4C loci was downloaded from the UCSC genome track browser [4]. Regions were intersected with methylation data using the package GenomicRanges package (version 1.38.0) [6] and beta values between wild-type and mutant PCC/PPGL samples at CpG islands spanning the gene loci and CpG islands attributable to the promotor region (2kb upstream of the start codon), using a Mann-whitney U test (stats::wilcox.test() function).

Differential methylation

Differentially methylated region analysis was performed using the bumphunter package (version 1.28.0) [5]. Differential methylation was tested between wild-type and mutant PCC/PPGL samples using a methylation cutoff of 0.2 and 100 permutations. Identified bumps were intersected with annotated gene loci using bumphunter::matchGenes() function, where gene annotation data was extracted from the TxDb.Hsapiens.UCSC.hg19.knownGene package (version 3.2.2) [7].

Metabolic correlations

Correlations between mean beta values and empirically-determined succinate concentrations was performed using a spearmans rank correlation test (stats::cor.test() function).

Implemenation guide

To be added on data archive submission.

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