We prioritized variants in high LD using scoring algorithms such as RegulomeDB (Boyle et al., 2012; Dong and Boyle, 2019) and IW scoring system (Wang et al., 2018). The first is an online database combining data from the ENCODE project, manual annotations and algorithms to predict the effect of a single-base mutation on chromatin accessibility and TF binding (Boyle et al., 2012). Just like RegulomeDB, a number of similar algorithms have been published and made publicly available. IW scoring system pools together a number of published algorithms with experimental chromatin data available on ENCODE and Ensembl. The output gives an overall score helping the ranking of genetic variants. To prioritize SNPs, we used IW score (K10), which combines data from CADD score, DeepSEA, EIGEN, FATHMM, FunSeq2, GWAVA, ReMM, ENCODE, Ensembl and FANTOM5 (Wang et al., 2018).

Scores were normalized in R, reversing Regulome and DeepSEA scales and standardizing each score's vertical height by setting minimum to zero and maximum to one. Each score was then centered using its median.

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