ArticleAmerican journal of human genetics2008
Accommodating linkage disequilibrium in genetic-association analyses via ridge regression.
Article in American journal of human genetics, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 81 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
81 citing papers in PubMed.
- TCF7L2 genetic variants modulate the effect of dietary fat intake on changes in body composition during a weight-loss intervention.The American journal of clinical nutrition · 2012Trial
- Improving genetic variant identification for quantitative traits using ensemble learning-based approaches.BMC genomics · 2025Article
- BLUPmrMLM: A Fast mrMLM Algorithm in Genome-wide Association Studies.Genomics, proteomics & bioinformatics · 2024Article
- Heritability of complex traits in sub-populations experiencing bottlenecks and growth.Journal of human genetics · 2024Article
- Pyroptosis-Derived Long Noncoding RNA Profiles Reveal a Novel Signature for Evaluating the Prognosis of Patients With Lung Adenocarcinoma.JCO precision oncology · 2024Article
- Evaluation of penalized and machine learning methods for asthma disease prediction in the Korean Genome and Epidemiology Study (KoGES).BMC bioinformatics · 2024Article
- Potential application of elastic nets for shared polygenicity detection with adapted threshold selection.The international journal of biostatistics · 2023Article
- A Novel Algorithm for Feature Selection Using Penalized Regression with Applications to Single-Cell RNA Sequencing Data.Biology · 2022Article
- Elastic Correlation Adjusted Regression (ECAR) scores for high dimensional variable importance measuring.Scientific reports · 2021Article
- Estimating Genetic Similarity Matrices Using Phylogenies.Journal of computational biology : a journal of computational molecular cell biology · 2021Article
- Genome-wide Modeling of Polygenic Risk Score in Colorectal Cancer Risk.American journal of human genetics · 2020Article
- Detecting PCOS susceptibility loci from genome-wide association studies via iterative trend correlation based feature screening.BMC bioinformatics · 2020Article
- Using Genetic Risk Score Approaches to Infer Whether an Environmental Factor Attenuates or Exacerbates the Adverse Influence of a Candidate Gene.Frontiers in genetics · 2020Article
- A multiple coefficient of determination-based method for parsing SNPs that correlate with mRNA expression.Scientific reports · 2019Article
- Leveraging allelic imbalance to refine fine-mapping for eQTL studies.PLoS genetics · 2019Article
- Joint Analysis of Multiple Phenotypes in Association Studies based on Cross-Validation Prediction Error.Scientific reports · 2019Article
- Machine learning identifies interacting genetic variants contributing to breast cancer risk: A case study in Finnish cases and controls.Scientific reports · 2018Article
- Improved estimation of SNP heritability using Bayesian multiple-phenotype models.European journal of human genetics : EJHG · 2018Article
- A novel linkage-disequilibrium corrected genomic relationship matrix for SNP-heritability estimation and genomic prediction.Heredity · 2018Article
- Efficient Prioritization of Multiple Causal eQTL Variants via Sparse Polygenic Modeling.Genetics · 2017Article
21 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Large-scale genetic-association studies that take advantage of an extremely dense set of genetic markers have begun to produce very compelling statistical associations between multiple makers exhibiting strong linkage disequilibrium (LD) in a single genomic region and a phenotype of interest. However, the ultimate biological or "functional" significance of these multiple associations has been difficult to discern. In fact, the LD relationships between not only the markers found to be associated with the phenotype but also potential functionally or causally relevant genetic variations that reside near those markers have been exploited in such studies. Unfortunately, LD, especially strong LD, between variations at neighboring loci can make it difficult to distinguish the functionally relevant variations from nonfunctional variations. Although there are (rare) situations in which it is impossible to determine the independent phenotypic effects of variations in LD, there are strategies for accommodating LD between variations at different loci, and they can be used to tease out their independent effects on a phenotype. These strategies make it possible to differentiate potentially causative from noncausative variations. We describe one such approach involving ridge regression. We showcase the method by using both simulated and real data. Our results suggest that ridge regression and related techniques have the potential to distinguish causative from noncausative variations in association studies.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.