Fig. 6

Prediction of effects of GWAS-SNPs on TF binding using ΔMOCCS2score profiles. A Schematic overview of the data processing procedures used to calculate the ΔMOCCS2score for k-mers overlapping GWAS-SNPs. B Combinations of SLE GWAS-SNPs and ChIP-seq samples with high ΔMOCCS2scores (ΔMOCCS2score > 75 (left) or ΔMOCCS2score < –100 (right), q < 0.05). Bar colors represent the cell type classes of the ChIP-seq samples. C Combinations of CD GWAS-SNPs and ChIP-seq samples with high ΔMOCCS2scores (ΔMOCCS2score > 100 (left) or ΔMOCCS2score < –100 (right), q < 0.05). Bar colors represent the TFs of the ChIP-seq samples. D Prediction of the effect of a CD GWAS-SNP, rs17293632 (C > T), on TF binding using the ΔMOCCS2score profile. The ChIP-seq samples with large positive ΔMOCCS2scores are shown (ΔMOCCS2score > 100, q < 0.05). Bar colors represent TFs. The top three ChIP-seq samples with high absolute values of the ΔMOCCS2score were FOS. E GWAS-SNPs predicted to affect FOS binding using ΔMOCCS2score profiles in Crohn’s disease. The CD risk variant, rs17293632 (C > T), may strongly affect the binding of FOS, as shown in D