Predicting Autoimmune Disease Risk SNPs

We selected 11 autoimmune traits enriched in Th1 H3K27Ac as shown in Fig 3 of Ref. ^{28 (link)}. We made predictions for 413 lead SNPs associated with 11 autoimmune diseases enriched in Th1 H3K27Ac regions (T1D: Type 1 Diabetes, CRO: Crohn’s Disease, MS: Multiple Sclerosis, CEL: Celiac Disease, PBC: Primary Biliary Cirrhosis, RA: Rheumatoid Arthritis, Allergy, ATD: Autoimmune Thyroid Disease, UC: Ulcerative Colitis, VIT: Vitiligo, SLE: Systemic Lupus Erythematosus)^{28 (link)}. We trained a gkm-SVM on the top 10,000 500 bp Th1 DHS regions, after excluding regions that were DHS in more than 30% of human ENCODE cell lines, or near promoters (< 2 kb from TSS), against an equal size GC and repeat matched training set. We scored the lead SNP and all flanking off-lead candidates in LD as defined by (R² > .5 and PICS^{28 (link)} probability > .0275), yielding 3113 total SNPs. Since the significance of the maximum deltaSVM score in a locus will depend on the number of SNPs in that locus, as a random control we scored random SNPs and equal size flanking sets. To determine the cutoff, we first determined 2^nd percentile deltaSVM score from 10,000 random permutations for each number of flanking SNPs (1~30), and then calculated mean and standard deviation of the 100 repeated experiments as the final cutoff. We identified 17 high scoring deltaSVM SNPs which we predict to be expression perturbing SNPs with high confidence (P < .02), while at this threshold random sampling produced 8 SNPs (binomial test P < 0.004, Supplementary Figure 4). deltaSVM scores for all 3113 SNPs are provided as Supplementary Table 6.