It is estimated that about 15–30% of the variants causing inherited diseases affect splicing 1, 2, 3, 4, 5. FRASER is easy to use and freely available. Applying FRASER to rare disease diagnostics is demonstrated by reprioritizing a pathogenic aberrant exon truncation in TAZ from a published dataset. Moreover, FRASER is based on a count distribution and multiple testing correction, thus reducing the number of calls by two orders of magnitude over commonly applied z score cutoffs, with a minor loss of sensitivity. FRASER automatically controls for latent confounders, which are widespread and affect sensitivity substantially. This typically doubles the number of detected aberrant events and identified a pathogenic intron retention in MCOLN1 causing mucolipidosis. Unlike existing methods, FRASER captures not only alternative splicing but also intron retention events. Here, we develop FRASER, an algorithm to detect aberrant splicing from RNA sequencing data. Recently, RNA sequencing has proven to be an effective complementary avenue to detect aberrant splicing.
However, its prediction from genome sequence alone remains in most cases inconclusive. Aberrant splicing is a major cause of rare diseases.
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