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Article

Clinical pertinence metric enables hypothesis-independent genome-phenome analysis for neurologic diagnosis.

Journal of child neurology - 1 Jun 2015

Segal Michael M, Abdellateef Mostafa, El-Hattab Ayman W, Hilbush Brian S, De La Vega Francisco M, Tromp Gerard, Williams Marc S, Betensky Rebecca A, Gleeson Joseph

Abstract excerpt

We describe an "integrated genome-phenome analysis" that combines both genomic sequence data and clinical information for genomic diagnosis. It is novel in that it uses robust diagnostic decision support and combines the clinical differential diagnosis and the genomic variants using a "pertinence" metric. This allows the analysis to be hypothesis-independent, not requiring assumptions about mode of inheritance,...

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Identifiers

PMID: 25156663
DOI: 10.1177/0883073814545884
PMCID: PMC4339658

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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