000007855 001__ 7855
000007855 005__ 20231208181613.0
000007855 0247_ $$2DOI$$a10.6083/7p88cg990
000007855 037__ $$aETD
000007855 245__ $$aElectronic health record phenotyping to facilitate the categorization of genetic variants of uncertain significance
000007855 260__ $$bOregon Health and Science University
000007855 269__ $$a2020
000007855 336__ $$aCapstone
000007855 502__ $$bM.S.
000007855 520__ $$aMany genetic variants are of unknown significance (VUS). Efficient and accurate electronic health record (EHR) phenotyping, having facilitated genome-wide association studies, could identify patients with VUSs who exhibit phenotypic features that might indicate pathogenicity of those variants. Identifying and following up with these patients could improve their healthcare, and assist in improving genetic variant categorization. With further assessment, these methods, combined with other data, could be used to identify phenotypes in patients with VUSs, URVs, or CPVs, which in turn could facilitate the functional categorization of those variants as either pathogenic or benign.
000007855 650__ $$aElectronic Health Records$$038928
000007855 650__ $$aLipoproteins, LDL$$021559
000007855 650__ $$aHumans$$020376
000007855 650__ $$aGenotype$$019486
000007855 650__ $$aAlgorithms$$014437
000007855 650__ $$aPhenotype$$023948
000007855 691__ $$aSchool of Medicine$$041369
000007855 692__ $$aDepartment of Medical Informatics and Clinical Epidemiology$$041422
000007855 7001_ $$aPacheco, Jennifer$$uOregon Health and Science University$$041354
000007855 8564_ $$97a4a25ba-f821-4b6e-91c4-1bbc103cd588$$s977533$$uhttps://digitalcollections.ohsu.edu/record/7855/files/Pacheco.Jennifer.2020.pdf
000007855 905__ $$a/rest/prod/7p/88/cg/99/7p88cg990
000007855 909CO $$ooai:digitalcollections.ohsu.edu:7855$$pstudent-work
000007855 980__ $$aTheses and Dissertations