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Dataset Information

Benchmarking splice variant prediction algorithms using massively parallel splicing assays.


ABSTRACT:

Background

Variants that disrupt mRNA splicing account for a sizable fraction of the pathogenic burden in many genetic disorders, but identifying splice-disruptive variants (SDVs) beyond the essential splice site dinucleotides remains difficult. Computational predictors are often discordant, compounding the challenge of variant interpretation. Because they are primarily validated using clinical variant sets heavily biased to known canonical splice site mutations, it remains unclear how well their performance generalizes.

Results

We benchmarked eight widely used splicing effect prediction algorithms, leveraging massively parallel splicing assays (MPSAs) as a source of experimentally determined ground-truth. MPSAs simultaneously assay many variants to nominate candidate SDVs.

SUBMITTER: Smith C 

PROVIDER: S-EPMC10187268 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature