Figure 1

Overview of MBASED algorithm (one-sample analysis). The two-sample approach is similar and is described in the text. (A) When true haplotypes are unknown, MBASED pseudo-phases SNVs within a gene by creating a major haplotype out of the alleles with larger RNA read counts at each SNV. A meta-analytic approach is then used to aggregate ASE information across individual SNVs to produce a meta-analysis estimate of major haplotype frequency (MAF), T _FT . (B) Keeping total read counts at each SNV constant, we simulate reference allele counts from a null distribution with an underlying haplotype frequency ratio of 1:1, and then pseudo-phase the alleles into haplotypes based on simulated read counts. Repeating this process 10⁶ times we obtain an estimate of null distribution of T _FT and assign a final ASE P-value, p_g,ASE, to gene g as the observed fraction of simulated estimates that are as extreme as or more extreme than T _FT .