In clinical variant interpretation, we still tend to default to the canonical transcript when assessing the effect of a variant. While this simplifies workflows, it risks missing biologically relevant consequences on non-canonical but functionally important isoforms. This is especially true in genes with tissue-specific expression or developmental regulation. I’ve been trying to push our lab to adopt a more isoform-aware review process, especially for cases involving neurodevelopmental disorders and rare diseases. But the challenge, as always, is time and clarity — most tools don't make it easy to quickly compare multiple transcripts or identify which ones are relevant in specific contexts. Has anyone here successfully shifted toward a more transcript-sensitive interpretation model in routine practice? If so, how did you build it into your workflow, and are there tools you’d recommend for helping non-computational colleagues engage with the data more easily?
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Incorporating isoform-aware interpretation into standard genetic workflows
Incorporating isoform-aware interpretation into standard genetic workflows
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