Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

OPENING THE DOOR TO THE LARGE SCALE USE OF CLINICAL LAB MEASURES FOR ASSOCIATION TESTING: EXPLORING DIFFERENT METHODS FOR DEFINING PHENOTYPES.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing - 1 Jan 2017

Bauer Christopher R, Lavage Daniel, Snyder John, Leader Joseph, Mahoney J Matthew, Pendergrass Sarah A

Abstract excerpt

The past decade has seen exponential growth in the numbers of sequenced and genotyped individuals and a corresponding increase in our ability of collect and catalogue phenotypic data for use in the clinic. We now face the challenge of integrating these diverse data in new ways new that can provide useful diagnostics and precise medical interventions for individual patients. One of the first steps in this process...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Cluster Analysis
Share to Cohort Studies

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Computational Biology

Share to Databases, Genetic

Share to Electronic Health Records

Share to Genetic Association Studies

Share to Genome-Wide Association Study

Share to Principal Component Analysis

Source

Identifiers

PMID: 27896989
DOI: 10.1142/9789813207813_0034

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 2 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

OPENING THE DOOR TO THE LARGE SCALE USE OF CLINICAL LAB MEASURES FOR ASSOCIATION TESTING: EXPLORING DIFFERENT METHODS FOR DEFINING PHENOTYPES.PMID 27896989Read ↗

Informatics and machine learning to define the phenotype.Semantic proximity Read ↗

The role of phenotype in gene discovery in the whole genome sequencing era.Semantic proximity Read ↗

Genome-wide association studies and polygenic risk score phenome-wide association studies across complex phenotypes in the human phenotype project.Semantic proximity Read ↗

Phenomics: expanding the role of clinical evaluation in genomic studies.Semantic proximity Read ↗

INTEGRATING CLINICAL LABORATORY MEASURES AND ICD-9 CODE DIAGNOSES IN PHENOME-WIDE ASSOCIATION STUDIES.Semantic proximity Read ↗

Analysis of biomarkers in the Human Phenotype Project using disease models from UK Biobank.Semantic proximity Read ↗

Computationally efficient, exact, covariate-adjusted genetic principal component analysis by leveraging individual marker summary statistics from large biobanks.Semantic proximity Read ↗

Optimized phenotype definitions boost GWAS power.Semantic proximity Read ↗

Analysis of multiple diverse phenotypes via semiparametric canonical correlation analysis.Semantic proximity Read ↗

Selecting Covariates for Genome-Wide Association StudiesSemantic proximity Read ↗

Optimized phenotype definitions boost GWAS powerSemantic proximity Read ↗

Gene set analysis of SNP data: benefits, challenges, and future directions.Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.