ArticleStatistical applications in genetics and molecular biology2012
Fast identification of biological pathways associated with a quantitative trait using group lasso with overlaps.
Article in Statistical applications in genetics and molecular biology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.
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Who cites it
24 citing papers in PubMed, 1 synthesis or guideline pooled it, 44 citations in OpenAlex.
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- Detecting Biomarkers of Alzheimer's Disease Based on Multi-constrained Uncertainty-Aware Adaptive Sparse Multi-view Canonical Correlation Analysis.Journal of molecular neuroscience : MN · 2022Article
- Identification of high-dimensional omics-derived predictors for tumor growth dynamics using machine learning and pharmacometric modeling.CPT: pharmacometrics & systems pharmacology · 2021Article
- A Structured Brain-wide and Genome-wide Association Study Using ADNI PET Images.The Canadian journal of statistics = Revue canadienne de statistique · 2021Article
- Genome-wide association studies of brain imaging data via weighted distance correlation.Bioinformatics (Oxford, England) · 2020Article
- Detecting genetic associations with brain imaging phenotypes in Alzheimer's disease via a novel structured SCCA approach.Medical image analysis · 2020Article
- Brain Imaging Genomics: Integrated Analysis and Machine Learning.Proceedings of the IEEE. Institute of Electrical and Electronics Engineers · 2020Article
- A Novel Three-Stage Framework for Association Analysis Between SNPs and Brain Regions.Frontiers in genetics · 2020Article
- A multivariable approach for risk markers from pooled molecular data with only partial overlap.BMC medical genetics · 2019Article
- Gsslasso Cox: a Bayesian hierarchical model for predicting survival and detecting associated genes by incorporating pathway information.BMC bioinformatics · 2019Article
- Jackknife Model Averaging Prediction Methods for Complex Phenotypes with Gene Expression Levels by Integrating External Pathway Information.Computational and mathematical methods in medicine · 2019Article
- Group spike-and-slab lasso generalized linear models for disease prediction and associated genes detection by incorporating pathway information.Bioinformatics (Oxford, England) · 2018Article
- Machine learning shows association between genetic variability inProceedings of the National Academy of Sciences of the United States of America · 2017Article
- Possible relationship between common genetic variation and white matter development in a pilot study of preterm infants.Brain and behavior · 2016Article
- Partitioning of genomic variance reveals biological pathways associated with udder health and milk production traits in dairy cattle.Genetics, selection, evolution : GSE · 2015Article
- 2014 Update of the Alzheimer's Disease Neuroimaging Initiative: A review of papers published since its inception.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2015Review
- Sparse models for correlative and integrative analysis of imaging and genetic data.Journal of neuroscience methods · 2014Review
- Pathways-driven sparse regression identifies pathways and genes associated with high-density lipoprotein cholesterol in two Asian cohorts.PLoS genetics · 2013Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Where causal SNPs (single nucleotide polymorphisms) tend to accumulate within biological pathways, the incorporation of prior pathways information into a statistical model is expected to increase the power to detect true associations in a genetic association study. Most existing pathways-based methods rely on marginal SNP statistics and do not fully exploit the dependence patterns among SNPs within pathways.We use a sparse regression model, with SNPs grouped into pathways, to identify causal pathways associated with a quantitative trait. Notable features of our "pathways group lasso with adaptive weights" (P-GLAW) algorithm include the incorporation of all pathways in a single regression model, an adaptive pathway weighting procedure that accounts for factors biasing pathway selection, and the use of a bootstrap sampling procedure for the ranking of important pathways. P-GLAW takes account of the presence of overlapping pathways and uses a novel combination of techniques to optimise model estimation, making it fast to run, even on whole genome datasets.In a comparison study with an alternative pathways method based on univariate SNP statistics, our method demonstrates high sensitivity and specificity for the detection of important pathways, showing the greatest relative gains in performance where marginal SNP effect sizes are small.
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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.