Discover Community Create You

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

Using the optimal robust receiver operating characteristic (ROC) curve for predictive genetic tests.

Biometrics - 1 Jun 2010

Lu Qing, Obuchowski Nancy, Won Sungho, Zhu Xiaofeng, Elston Robert C

Abstract excerpt

Current ongoing genome-wide association (GWA) studies represent a powerful approach to uncover common unknown genetic variants causing common complex diseases. The discovery of these genetic variants offers an important opportunity for early disease prediction, prevention, and individualized trea...

Read the complete abstract on PubMed

Topics

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

Share to Diabetes Mellitus, Type 1
Share to Genetic Predisposition to Disease
Share to Genetic Testing

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Genome-Wide Association Study

Share to Logistic Models

Share to Polymorphism, Single Nucleotide

Share to Predictive Value of Tests

Share to ROC Curve

Source

Open in PubMed Open full text

Identifiers

PMID: 19508241
DOI: 10.1111/j.1541-0420.2009.01278.x
PMCID: PMC3039874

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 2 Sept 2026. Prepared record publication-19508241-2026-09-02.2. Manifest publication-graph-cohort-2026-09-02.2.

Source receipt: PubMed via Helena Literature Corpus, retrieved 2 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Using the optimal robust receiver operating characteristic (ROC) curve for predictive genetic tests.PMID 19508241Read ↗

Using the optimal receiver operating characteristic curve to design a predictive genetic test, exemplified with type 2 diabetes.Semantic proximity Read ↗

A unifying framework for evaluating the predictive power of genetic variants based on the level of heritability explained.Semantic proximity Read ↗

Bagging optimal ROC curve method for predictive genetic tests, with an application for rheumatoid arthritis.Semantic proximity Read ↗

From disease association to risk assessment: an optimistic view from genome-wide association studies on type 1 diabetes.Semantic proximity Read ↗

R2ROC: An efficient method of comparing two or more correlated AUC from out-of-sample prediction using polygenic scoresSemantic proximity Read ↗

Assessing the performance of genome-wide association studies for predicting disease riskSemantic proximity Read ↗

R2ROC: an efficient method of comparing two or more correlated AUC from out-of-sample prediction using polygenic scores.Semantic proximity Read ↗

Assessing the performance of genome-wide association studies for predicting disease risk.Semantic proximity Read ↗

Bridge: a GUI package for genetic risk prediction.Semantic proximity Read ↗

PredictABEL: an R package for the assessment of risk prediction models.Semantic proximity Read ↗

Predicting the Onset of Type 2 Diabetes (T2D) Based on Genetic and Clinical Risk Factors Using XGBoost ML ModelSemantic proximity Read ↗

The impact of genotype frequencies on the clinical validity of genomic profiling for predicting common chronic diseases.Semantic proximity Read ↗

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